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{1576} |
ref: -0
tags: GFlowNet Bengio probabilty modelling reinforcement learing
date: 10-29-2023 19:17 gmt
revision:3
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{1574} |
ref: -0
tags: ocaml application functional programming
date: 10-11-2022 21:36 gmt
revision:2
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https://stackoverflow.com/questions/26475765/ocaml-function-with-variable-number-of-arguments From this I learned that in ocaml you can return not just functions (e.g. currying) but appliations of yet-to-be named functions. let sum f = f 0 ;; let arg a b c = c ( b + a ) ;; let z a = a ;; then sum (arg 1) ;; is well-typed as (int -> `a) -> `a = <fun> e.g. an application of a function that converts int to `a. Think of it as the application of Xa to argument ( 0 + 1 ), where Xa is the argument (per type signature). Zero is supplied by the definition of 'sum'. sum (arg 1) (arg 2);; can be parsed as (sum (arg 1)) (arg 2) ;; '(arg 2)' outputs an application of an int & a yet-to be determined function to 'a, E.g. it's typed as int -> (int -> `a) -> `a = <fun>. So, you can call it Xa passed to above. Or, Xa = Xb( ( 0 + 1 ) + 2) where, again, Xb is a yet-to-be defined function that is supplied as an argument. Therefore, you can collapse the whole chain with the identity function z. But, of course, it could be anything else -- square root perhaps for MSE? All very clever. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{1571} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
One model for the learning of language
A more interesting result is Deep symbolic regression for recurrent sequences, where the authors (facebook/meta) use a Transformer -- in this case, directly taken from Vaswini 2017 (8-head, 8-layer QKV w/ a latent dimension of 512) to do both symbolic (estimate the algebraic recurrence relation) and numeric (estimate the rest of the sequence) training / evaluation. Symbolic regression generalizes better, unsurprisingly. But both can be made to work even in the presence of (log-scaled) noise! While the language learning paper shows that small generative programs can be inferred from a few samples, the Meta symbolic regression shows that Transformers can evince either amortized memory (less likely) or algorithms for perception -- both new and interesting. It suggests that 'even' abstract symbolic learning tasks are sufficiently decomposable that the sorts of algorithms available to an 8-layer transformer can give a useful search heuristic. (N.B. That the transformer doesn't spit out perfect symbolic or numerical results directly -- it also needs post-processing search. Also, the transformer algorithm has search (in the form of softmax) baked in to it's architecture.) This is not a light architecture: they trained the transformer for 250 epochs, where each epoch was 5M equations in batches of 512. Each epoch took 1 hour on 16 Volta GPUs w 32GB of memory. So, 4k GPU-hours x ~10 TFlops = 1.4e20 Flops. Compare this with grammar learning above; 7 days on 32 cores operating at ~ 3Gops/sec is 1.8e15 ops. Much, much smaller compute. All of this is to suggest a central theme of computer science: a continuum between search and memorization.
Most interesting for a visual neuroscientist (not that I'm one per se, but bear with me) is where on these axes (search, heuristic, memory) visual perception is. Clearly there is a high degree of recurrence, and a high degree of plasticity / learning. But is there search or local optimization? Is this coupled to the recurrence via some form of energy-minimizing system? Is recurrence approximating E-M? | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{1572} |
ref: -2019
tags: Piantadosi cogntion combinators function logic
date: 09-05-2022 01:57 gmt
revision:0
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{1569} |
ref: -2022
tags: symbolic regression facebook AI transformer
date: 05-17-2022 20:25 gmt
revision:0
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Deep symbolic regression for recurrent sequences Surprisingly, they do not do any network structure changes; it’s Vaswini 2017w/ a 8-head, 8 layer transformer (sequence to sequence, not decoder only) with a latent dimension of 512. Significant work was in feature / representation engineering (e.g. base-10k representations of integers and fixed-precision representations of floating-point numbers. (both of these involve a vocabulary size of ~10k ... amazing still that this works..)) + the significant training regimen they worked with (16 Turing GPUs, 32gb ea). Note that they do perform a bit of beam-search over the symbolic regressions by checking how well each node fits to the starting sequence, but the models work even without this degree of refinement. (As always, there undoubtedly was significant effort spent in simply getting everything to work) The paper does both symbolic (estimate the algebraic recurence relation) and numeric (estimate the rest of the sequence) training / evaluation. Symbolic regression generalizes better, unsurprisingly. But both can be made to work even in the presence of (log-scaled) noise! Analysis of how the transformers work for these problems is weak; only one figure showing that the embeddings of the integers follows some meandering but continuous path in t-SNE space. Still, the trained transformer is able to usually best hand-coded sequence inference engine(s) in Mathematica, and does so without memorizing all of the training data. Very impressive and important result, enough to convince that this learned representation (and undiscovered cleverness, perhaps) beats human mathematical engineering, which probably took longer and took more effort. It follows, without too much imagination (but vastly more compute), that you can train an 'automatic programmer' in the very same way. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{1566} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Interactions between learning and evolution
Altogether (historically) interesting, but some of these ideas might well have been anticipated by some simple hand calculations. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{842} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Distilling free-form natural laws from experimental data
Since his Phd, Michael Schmidt has gone on to found Nutonian, which produced Eurequa software, apparently without dramatic new features other than being able to use the cloud for equation search. (Probably he improved many other detailed facets of the software..). Nutonian received $4M in seed funding, according to Crunchbase. In 2017, Nutonian was acquired by Data Robot (for an undisclosed amount), where Michael has worked since, rising to the title of CTO. Always interesting to follow up on the authors of these classic papers! | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{1559} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Some investigations into denoising models & their intellectual lineage: Deep Unsupervised Learning using Nonequilibrium Thermodynamics 2015
Generative Modeling by Estimating Gradients of the Data Distribution July 2019
Denoising Diffusion Probabilistic Models June 2020
Improved Denoising Diffusion Probabilistic Models Feb 2021
Diffusion Models Beat GANs on Image Synthesis May 2021
In all of above, it seems that the inverse-diffusion function approximator is a minor player in the paper -- but of course, it's vitally important to making the system work. In some sense, this 'diffusion model' is as much a means of training the neural network as it is a (rather inefficient, compared to GANs) way of sampling from the data distribution. In Nichol & Dhariwal Feb 2021, they use a U-net convolutional network (e.g. start with few channels, downsample and double the channels until there are 128-256 channels, then upsample x2 and half the channels) including multi-headed attention. Ho 2020 used single-headed attention only at the 16x16 level. Ho 2020 in turn was based on PixelCNN++
which is an improvement to (e.g. add selt-attention layers) Conditional Image Generation with PixelCNN Decoders
Most recently, GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models
Added text-conditional generation + many more parameters + much more compute to yield very impressive image results + in-painting. This last effect is enabled by the fact that it's a full generative denoising probabilistic model -- you can condition on other parts of the image! | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{1556} |
ref: -0
tags: concept net NLP transformers graph representation knowledge
date: 11-04-2021 17:48 gmt
revision:0
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Symbolic Knowledge Distillation: from General Language Models to Commonsense Models
Human-designed knowledge graphs are described here: ConceptNet 5.5: An Open Multilingual Graph of General Knowledge And employed for profit here: https://www.luminoso.com/ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{1554} |
ref: -2021
tags: FIBSEM electron microscopy presynaptic plasticity activity Funke
date: 10-12-2021 17:03 gmt
revision:0
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Ultrastructural readout of in vivo synaptic activity for functional connectomics
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{1544} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
The HSIC Bottleneck: Deep learning without Back-propagation In this work, the authors use a kernelized estimate of statistical independence as part of a 'information bottleneck' to set per-layer objective functions for learning useful features in a deep network. They use the HSIC, or Hilbert-schmidt independence criterion, as the independence measure. The information bottleneck was proposed by Bailek (spikes..) et al in 1999, and aims to increase the mutual information between the layer representation and the labels while minimizing the mutual information between the representation and the input:
Where is the hidden representation at layer i (later output), is the layer input, and are the labels. By replacing with the HSIC, and some derivation (?), they show that
Where are samples and labels, and -- that is, it's the kernel function applied to all pairs of (vectoral) input variables. H is the centering matrix. The kernel is simply a Gaussian kernel, . So, if all the x and y are on average independent, then the inner-product will be mean zero, the kernel will be mean one, and after centering will lead to zero trace. If the inner product is large within the realm of the derivative of the kernel, then the HSIC will be large (and negative, i think). In practice they use three different widths for their kernel, and they also center the kernel matrices. But still, the feedback is an aggregate measure (the trace) of the product of two kernelized (a nonlinearity) outer-product spaces of similarities between inputs. it's not unimaginable that feedback networks could be doing something like this... For example, a neural network could calculate & communicate aspects of joint statistics to reward / penalize weights within a layer of a network, and this is parallelizable / per layer / adaptable to an unsupervised learning regime. Indeed, that was done almost exactly by this paper: Kernelized information bottleneck leads to biologically plausible 3-factor Hebbian learning in deep networks albeit in a much less intelligible way. Robust Learning with the Hilbert-Schmidt Independence Criterion Is another, later, paper using the HSIC. Their interpretation: "This loss-function encourages learning models where the distribution of the residuals between the label and the model prediction is statistically independent of the distribution of the instances themselves." Hence, given above nomenclature, (I'm not totally sure about the weighting, but might be required given the definition of the HSIC.) As I understand it, the HSIC loss is a kernellized loss between the input, output, and labels that encourages a degree of invariance to input ('covariate shift'). This is useful, but I'm unconvinced that making the layer output independent of the input is absolutely essential (??) | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{1552} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Modularizing Deep Learning via Pairwise Learning With Kernels
I think in general this is an important result, even if its not wholly unique / somewhat anticipated (it's a year old at the time of writing). Modular training of neural networks is great for efficiency, parallelization, and biological implementations! Transport of weights between layers is hence non-essential. Classes still are, but I wonder if temporal continuity can solve some of these problems? (There is plenty of other effort in this area -- see also {1544}) | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{1551} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cell-based reporters reveal in vivo dynamics of dopamine and norepinephrine release in murine cortex
Referenced -- and used by the recent paper Reinforcement learning links spontaneous cortical dopamine impulses to reward, which showed that dopamine signaling itself can come under volitional, operant-conditioning (or reinforcement type) modulation. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{1548} |
ref: -2021
tags: gated multi layer perceptrons transformers ML Quoc_Le Google_Brain
date: 08-05-2021 06:00 gmt
revision:4
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Pretty remarkable that an industrial lab freely publishes results like this. I guess the ROI is that they get the resultant improved ideas? Or, perhaps, Google is in such a dominant position in terms of data and compute that even if they give away ideas and code, provided some of the resultant innovation returns to them, they win. The return includes trained people as well as ideas. Good for us, I guess! | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{1449} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
This was compiled from searching papers which referenced Olshausen and Field 1996 PMID-8637596 Emergence of simple-cell receptive field properties by learning a sparse code for natural images.
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{1546} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Local synaptic learning rules suffice to maximize mutual information in a linear network
x = randn(1000, 10); Q = x' * x; a = 0.001; Y = randn(10, 1); y = zeros(10, 1); for i = 1:1000 y = Y + (eye(10) - a*Q)*y; end y - pinv(Q)*Y / a % should be zero.
To this is added a 'sensing' learning and 'noise' unlearning phase -- one optimizes , the other minimizes . Everything is then applied, similar to before, to a gaussian-filtered one-dimensional white-noise stimuli. He shows this results in bandpass filter behavior -- quite weak sauce in an era where ML papers are expected to test on five or so datasets. Even if this was 1992 (nearly forty years ago!), it would have been nice to see this applied to a more realistic dataset; perhaps some of the following papers? Olshausen & Field came out in 1996 -- but they applied their algorithm to real images. In both Olshausen & this work, no affordances are made for multiple layers. There have to be solutions out there... | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Self-organizaton in a perceptual network
One may critically challenge the infomax idea: we very much need to (and do) throw away spurious or irrelevant information in our sensory streams; what upper layers 'care about' when making decisions is certainly relevant to the lower layers. This credit-assignment is neatly solved by backprop, and there are a number 'biologically plausible' means of performing it, but both this and infomax are maybe avoiding the problem. What might the upper layers really care about? Likely 'care about' is an emergent property of the interacting local learning rules and network structure. Can you search directly in these domains, within biological limits, and motivated by statistical reality, to find unsupervised-learning networks? You'll still need a way to rank the networks, hence an objective 'care about' function. Sigh. Either way, I don't per se put a lot of weight in the infomax principle. It could be useful, but is only part of the story. Otherwise Linsker's discussion is accessible, lucid, and prescient. Lol. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Two Routes to Scalable Credit Assignment without Weight Symmetry This paper looks at five different learning rules, three purely local, and two non-local, to see if they can work as well as backprop in training a deep convolutional net on ImageNet. The local learning networks all feature forward weights W and backward weights B; the forward weights (+ nonlinearities) pass the information to lead to a classification; the backward weights pass the error, which is used to locally adjust the forward weights. Hence, each fake neuron has locally the forward activation, the backward error (or loss gradient), the forward weight, backward weight, and Hebbian terms thereof (e.g the outer product of the in-out vectors for both forward and backward passes). From these available variables, they construct the local learning rules:
Each of these serves as a "regularizer term" on the feedback weights, which governs their learning dynamics. In the case of backprop, the backward weights B are just the instantaneous transpose of the forward weights W. A good local learning rule approximates this transpose progressively. They show that, with proper hyperparameter setting, this does indeed work nearly as well as backprop when training a ResNet-18 network. But, hyperparameter settings don't translate to other network topologies. To allow this, they add in non-local learning rules:
In "Symmetric Alignment", the Self and Decay rules are employed. This is similar to backprop (the backward weights will track the forward ones) with L2 regularization, which is not new. It performs very similarly to backprop. In "Activation Alignment", Amp and Sparse rules are employed. I assume this is supposed to be more biologically plausible -- the Hebbian term can track the forward weights, while the Sparse rule regularizes and stabilizes the learning, such that overall dynamics allow the gradient to flow even if W and B aren't transposes of each other. Surprisingly, they find that Symmetric Alignment to be more robust to the injection of Gaussian noise during training than backprop. Both SA and AA achieve similar accuracies on the ResNet benchmark. The authors then go on to explain the plausibility of non-local but approximate learning rules with Regression discontinuity design ala Spiking allows neurons to estimate their causal effect. This is a decent paper,reasonably well written. They thought trough what variables are available to affect learning, and parameterized five combinations that work. Could they have done the full matrix of combinations, optimizing just they same as the metaparameters? Perhaps, but that would be even more work ... Regarding the desire to reconcile backprop and biology, this paper does not bring us much (if at all) closer. Biological neural networks have specific and local uses for error; even invoking 'error' has limited explanatory power on activity. Learning and firing dynamics, of course of course. Is the brain then just an overbearing mess of details and overlapping rules? Yes probably but that doesn't mean that we human's can't find something simpler that works. The algorithms in this paper, for example, are well described by a bit of linear algebra, and yet they are performant. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{1526} |
ref: -0
tags: neuronal assemblies maass hebbian plasticity simulation austria fMRI
date: 02-23-2021 18:49 gmt
revision:1
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PMID-32381648 A model for structured information representation in neural networks in the brain
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Up until reading this, I had thought that the Balwin effect refers to the fact that when animals gain an ability to learn, this allows them to take new ecological roles without genotypic adaptation. This is a component of the effect, but is not the original meaning, which is opposite: when species adapt to a novel environment through phenotypic adptation (say adapting to colder weather through within-lifetime variation), evolution tends to push these changes into the germ line. This is something to the effect of Lamarkian evolution. In the case of house finches, as discussed in the link above, this pertains to increased brood variability and sexual dimorphism due to varied maternal habits and hormones due to environmental stress. This variance is then rapidly operated on by natural selection to tune the finch to it's new enviroment, including Montana, where the single author did most of his investigation. There are of course countless other details here, but still this is an illuminating demonstration of how evolution works to move information into the genome. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{1530} |
ref: -2017
tags: deep neuroevolution jeff clune Uber genetic algorithms
date: 02-18-2021 18:27 gmt
revision:1
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Deep Neuroevolution: genetic algorithms are a competitive alternative for training deep neural networks for reinforcement learning* Uber AI labs; Jeff Clune.
The result is indeed surprising, but it also feels lazy -- the total effort or information that they put into writing the actual algorithm is small; as mentioned in the introduction, this is a case of old algorithms with modern levels of compute. Analogously, compare Go-Explore, also by Uber AI labs, vs Agent57 by DeepMind; the Agent57 paper blithely dismisses the otherwise breathless Go-Explore result as feature engineering and unrealistic free backtracking / game-resetting (which is true..) It's strange that they did not incorporate crossover aka recombination, as David MacKay clearly shows that recombination allows for much higher mutation rates and much better transmission of information through a population. (Chapter 'Why have sex'). They also perhaps more reasonably omit developmental encoding, where network weights are tied or controlled through development, again in an analogy to biology. A better solution, as they point out, would be some sort of hybrid GA / ES / A3C system which used both gradient-based tuning, random stochastic gradient-based exploration, and straight genetic optimization, possibly all in parallel, with global selection as the umbrella. They mention this, but to my current knowledge this has not been done. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Discovering hidden factors of variation in deep networks
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{1527} |
ref: -0
tags: inductive logic programming deepmind formal propositions prolog
date: 11-21-2020 04:07 gmt
revision:0
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Learning Explanatory Rules from Noisy Data
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PMID-21527931 Two-photon absorption properties of fluorescent proteins
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Schema networks: zero-shot transfer with a generative causal model of intuitive physics
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PMID-26621426 Causal Inference and Explaining Away in a Spiking Network
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{1512} |
ref: -0
tags: rutherford journal computational theory neumann complexity wolfram
date: 05-05-2020 18:15 gmt
revision:0
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The Structures for Computation and the Mathematical Structure of Nature
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PMID-31942076 A distributional code for value in dopamine based reinforcement learning
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Finding frequent items in data streams
Mission: Ultra large-scale feature selection using Count-Sketches
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PMID-30420685 Fast in-vivo voltage imaging using a red fluorescent indicator
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PMID-18204458 High-speed, low-photodamage nonlinear imaging using passive pulse splitters
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Accelerated FRET-PAINT Microscopy
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Optimization and functionalization of red-shifted rhodamine dyes
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Why multifactor?
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PMID-29123069 A neural algorithm for a fundamental computing problem
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PMID: Spiking neurons can discover predictive features by aggregate-label learning
Editorializing a bit: I said this was interesting, but why? The first part of the paper is another form of SGD, albeit in a spiking neural network, where the gradient is harder compute hence is done numerically. It's the aggregate part that is new -- pulling in repeated patterns through synaptic learning rules. Of course, to do this, the full trace of pre and post synaptic activity must be recorded (??) for estimating the STS (i think). An eligibility trace moves in the right direction as a biologically plausible approximation, but as always nothing matches the precision of SGD. Can the eligibility trace be amended with e.g. neuromodulators to push the performance near that of SGD? The next step of adding self supervised singular and multiple features is perhaps toward the way the brain organizes itself -- small local feedback loops. These features annotate repeated occurrences of stimuli, or tile a continuous feature space. Still, the fact that I haven't seen any follow-up work is suggestive... Editorializing further, there is a limited quantity of work that a single human can do. In this paper, it's a great deal of work, no doubt, and the author offers some good intuitions for the design decisions. Yet still, the total complexity that even a very determined individual can amass is limited, and likely far below the structural complexity of a mammalian brain. This implies that inference either must be distributed and compositional (the normal path of science), or the process of evaluating & constraining models must be significantly accelerated. This later option is appealing, as current progress in neuroscience seems highly technology limited -- old results become less meaningful when the next wave of measurement tools comes around, irrespective of how much work went into it. (Though: the impedtus for measuring a particular thing in biology is only discovered through these 'less meaningful' studies...). A third option, perhaps one which many theoretical neuroscientists believe in, is that there are some broader, physics-level organizing principles to the brain. Karl Friston's free energy principle is a good example of this. Perhaps at a meta level some organizing theory can be found, or likely a set of theories; but IMHO, you'll need at least one theory per brain area, at least, just the same as each area is morphologically, cytoarchitecturaly, and topologically distinct. (There may be only a few theories of the cortex, despite all the areas, which is why so many are eager to investigate it!) So what constitutes a theory? Well, you have to meaningfully describe what a brain region does. (Why is almost as important; how more important to the path there.) From a sensory standpoint: what information is stored? What processing gain is enacted? How does the stored information impress itself on behavior? From a motor standpoint: how are goals selected? How are the behavioral segments to attain them sequenced? Is the goal / behavior even a reasonable way of factoring the problem? Our dual problem, building the bridge from the other direction, is perhaps easier. Or it could be a lot more money has gone into it. Either way, much progress has been made in AI. One arm is deep function approximation / database compression for fast and organized indexing, aka deep learning. Many people are thinking about that; no need to add to the pile; anyway, as OpenAI has proven, the common solution to many problems is to simply throw more compute at it. A second is deep reinforcement learning, which is hideously sample and path inefficient, hence ripe for improvement. One side is motor: rather than indexing raw motor variables (LRUD in a video game, or joint torques with a robot..) you can index motor primitives, perhaps hierarchically built; likewise, for the sensory input, the model needs to infer structure about the world. This inference should decompose overwhelming sensory experience into navigable causes ... But how can we do this decomposition? The cortex is more than adept at it, but now we're at the original problem, one that the paper above purports to make a stab at. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{1489} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{1488} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-30588295 Subcellular spatial resolution achieved for deep-brain imaging in vivo using a minimally invasive multimode fiber | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{1487} |
ref: -0
tags: adaptive optics sensorless retina fluorescence imaging optimization zernicke polynomials
date: 11-15-2019 02:51 gmt
revision:0
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PMID-26819812 Wavefront sensorless adaptive optics fluorescence biomicroscope for in vivo retinal imaging in mice
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{1486} |
ref: -2019
tags: non degenerate two photon excitation fluorophores fluorescence OPO optical parametric oscillator
date: 10-31-2019 20:53 gmt
revision:0
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Efficient non-degenerate two-photon excitation for fluorescence microscopy | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{1483} |
ref: -0
tags: Lucy Flavin mononucelotide FAD FMN fluorescent protein reporter
date: 10-17-2019 19:54 gmt
revision:1
[0] [head]
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PMID-25906065 LucY: A Versatile New Fluorescent Reporter Protein
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{1482} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Rapid learning or feature reuse? Towards understanding the effectiveness of MAML
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{99} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-15928412[0] Naive coadaptive Control May 2005. see notes ____References____ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{331} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-17021028[0] Correlations Between the Same Motor Cortex Cells and Arm Muscles During a Trained Task, Free Behavior, and Natural Sleep in the Macaque Monkey
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{1477} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-31495645 Can One Concurrently Record Electrical Spikes from Every Neuron in a Mammalian Brain?
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{1476} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-22831554 Swept field laser confocal microscopy for enhanced spatial and temporal resolution in live-cell imaging.
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{1473} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-17179937 Major signal increase in fluorescence microscopy through dark-state relaxation (2007)
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{1469} |
ref: -2016
tags: fluorescent proteins photobleaching quantum yield piston GFP
date: 06-19-2019 14:33 gmt
revision:0
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PMID-27240257 Quantitative assessment of fluorescent proteins.
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{1468} |
ref: -2013
tags: microscopy space bandwidth product imaging resolution UCSF
date: 06-17-2019 14:45 gmt
revision:0
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How much information does your microscope transmit?
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{1418} |
ref: -0
tags: nanophotonics interferometry neural network mach zehnder interferometer optics
date: 06-13-2019 21:55 gmt
revision:3
[2] [1] [0] [head]
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Deep Learning with Coherent Nanophotonic Circuits
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{1460} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
A friend postulated using the triplet state phosphorescence as a magnetically-modulatable dye. E.g. magnetically slice a scattering biological sample, rather than slicing optically (light sheet, 2p) or mechanically. After a little digging:
I'd imagine that it should be possible to design a molecule -- a protein cage, perhaps a (fully unsaturated) terpine -- which isolates the excited state from oxygen quenching. Adam Cohen at Harvard has been working a bit on this very idea, albeit with fluorescence not phosphorescence --
Yet! Magnetic field effects do exist in solution:
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{1461} |
ref: -2019
tags: super-resolution microscopy fluorescent protein molecules
date: 05-28-2019 16:02 gmt
revision:3
[2] [1] [0] [head]
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PMID-30997987 Chemistry of Photosensitive Fluorophores for Single-Molecule Localization Microscopy
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{1459} |
ref: -2018
tags: Michael Levin youtube talk NIPS 2018 regeneration bioelectricity organism patterning flatworm
date: 04-09-2019 18:50 gmt
revision:1
[0] [head]
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What Bodies Think About: Bioelectric Computation Outside the Nervous System - NeurIPS 2018
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{1455} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Conducting credit assignment by aligning local distributed representations
Lit review.
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{1441} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Assessing the Scalability of Biologically-Motivated Deep Learning Algorithms and Architectures
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{1452} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-22325196 How Does the Brain Solve Visual Object Recognition
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{305} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-101388[0] Fine control of operantly conditioned firing patterns of cortical neurons.
____References____ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{1450} |
ref: -2015
tags: conjugate light electron tomography mouse visual cortex fluorescent label UNC cryoembedding
date: 03-11-2019 19:37 gmt
revision:1
[0] [head]
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PMID-25855189 Mapping Synapses by Conjugate Light-Electron Array Tomography
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{1420} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-22278062 Conditional modulation of spike-timing-dependent plasticity for olfactory learning.
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{1446} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-29074582 A generative vision model that trains with high data efficiency and breaks text-based CAPTCHAs
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{1440} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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{1439} |
ref: -2006
tags: hinton contrastive divergence deep belief nets
date: 02-20-2019 02:38 gmt
revision:0
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PMID-16764513 A fast learning algorithm for deep belief nets.
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{1438} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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{1437} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-21280920 Optically sectioned in vivo imaging with speckle illumination HiLo microscopy
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{1434} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Audio AI: isolating vocals from stereo music using Convolutional Neural Networks
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{1426} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Training neural networks with local error signals
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{1433} |
ref: -2008
tags: representational similarity analysis fMRI
date: 02-15-2019 02:27 gmt
revision:1
[0] [head]
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PMID-19104670 Representational Similarity Analysis – Connecting the Branches of Systems Neuroscience
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{1415} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-28777724 Active inference, curiosity and insight. Karl J. Friston, Marco Lin, Christopher D. Frith, Giovanni Pezzulo,
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{1432} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Direct Feedback alignment provides learning in deep neural nets
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PMID-27824044 Random synaptic feedback weights support error backpropagation for deep learning.
Our proof says that weights W0 and W evolve to equilibrium manifolds, but simulations (Fig. 4) and analytic results (Supple- mentary Proof 2) hint at something more specific: that when the weights begin near 0, feedback alignment encourages W to act like a local pseudoinverse of B around the error manifold. This fact is important because if B were exactly W + (the Moore- Penrose pseudoinverse of W ), then the network would be performing Gauss-Newton optimization (Supplementary Proof 3). We call this update rule for the hidden units pseudobackprop and denote it by ∆hPBP = W + e. Experiments with the linear net- work show that the angle, ∆hFA ]∆hPBP quickly becomes smaller than ∆hFA ]∆hBP (Fig. 4b, c; see Methods). In other words feedback alignment, despite its simplicity, displays elements of second-order learning. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{1419} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
All-optical machine learning using diffractive deep neural networks
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{1430} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-28650477 Video rate volumetric Ca2+ imaging across cortex using seeded iterative demixing (SID) microscopy
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PMID-29375323 Fear learning regulates cortical sensory representation by suppressing habituation
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Curiosity-driven exploration by Self-supervised prediction
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Learning data manifolds with a Cutting Plane method
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PMID-24711417 Evidence for a causal inverse model in an avian cortico-basal ganglia circuit
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{1412} |
ref: -0
tags: deeplabcut markerless tracking DCN transfer learning
date: 10-03-2018 23:56 gmt
revision:0
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Markerless tracking of user-defined features with deep learning
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Structure discovery in Nonparametric Regression through Compositional Kernel Search
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Coevolution of Fitness Predictors
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LDMNet: Low dimensional manifold regularized neural nets.
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PMID-21896383 Effect of Insertion Speed on Tissue Response and Insertion Mechanics of a Chronically Implanted Silicon-Based Neural Probe
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PMID-28246640 Ultraflexible nanoelectronic probes form reliable, glial scar–free neural integration
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PMID-21204405 Soft, Fuzzy, and Bioactive Conducting Polymers for Improving the Chronic Performance of Neural Prosthetic Devices.
____References____
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{1400} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-29220192 Fluidic Microactuation of Flexible Electrodes for Neural Recording.
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PMID-23451719 Synthetic Nanoelectronic Probes for Biological Cells and Tissue
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IEEE-6170092 (pdf) An ultra-compliant, scalable neural probe with molded biodissolvable delivery vehicle
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{1236} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-23580530 Injectable, cellular-scale optoelectronics with applications for wireless optogenetics.
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{1057} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-19666051[0] Insertion shuttle with carboxyl terminated self-assembled monolayer coatings for implanting flexible polymer neural probes in the brain.
____References____
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{1398} |
ref: -0
tags: platinum parylene electrodes brush dissolving stiffener gelatin
date: 12-28-2017 02:44 gmt
revision:0
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PMID-27159159 Embedded Ultrathin Cluster Electrodes for Long-Term Recordings in Deep Brain Centers.
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{1397} |
ref: -0
tags: polyimide electrodes immune response foreign body inflammation stiffener steiglitz
date: 12-28-2017 02:37 gmt
revision:0
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PMID-27534649 Intracortical polyimide electrodes with a bioresorbable coating.
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{1396} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-27791052 Ultrathin, transferred layers of thermally grown silicon dioxide as biofluid barriers for biointegrated flexible electronic systems
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{1394} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Materials and technologies for soft implantable neuroprostheses
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{1393} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-11327505 Flexible polyimide-based intracortical electrode arrays with bioactive capability.
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{1392} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-29109247 Highly scalable multichannel mesh electronics for stable chronic brain electrophysiology
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{1356} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-27705958 Chronic in vivo stability assessment of carbon fiber microelectrode arrays.
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{1387} |
ref: -1977
tags: polyethylene surface treatment plasma electron irradiation mechanical testing saline seawater accelerated lifetime
date: 04-15-2017 06:06 gmt
revision:0
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Enhancement of resistance of polyethylene to seawater-promoted degradation by surface modification
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{1383} |
ref: -0
tags: carbon nanotube densification conductivity strength
date: 02-23-2017 02:52 gmt
revision:2
[1] [0] [head]
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Super-strong and highly conductive carbon nanotube ribbons from post-treatment methods
High-strength carbon nanotube fibre-like ribbon with high ductility and high electrical conductivity | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{1378} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-25803728 Neural stimulation and recording with bidirectional, soft carbon nanotube fiber microelectrodes.
PMID-23307737 Strong, light, multifunctional fibers of carbon nanotubes with ultrahigh conductivity.
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{1374} |
ref: -0
tags: nanoprobe transmembrane intracellular thiol gold AFM juxtacellular
date: 02-06-2017 23:45 gmt
revision:3
[2] [1] [0] [head]
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PMID-20212151 Fusion of biomimetic stealth probes into lipid bilayer cores
PMID-21469728 '''Molecular Structure Influences the Stability of Membrane Penetrating Biointerfaces.
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{1377} |
ref: -0
tags: nanopore membrane nanostraws melosh surface adhesion intracellular
date: 02-06-2017 23:34 gmt
revision:0
[head]
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PMID-22166016 Nanostraws for Direct Fluidic Intracellular Access
PMID-24710350, Quantification of nanowire penetration into living cells.
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{1373} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Contenders for high-modulus pitch-based carbon fiber: "
Tensile and Flextural Prperties of single carbon fibers
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{1372} |
ref: -0
tags: bone marrow transplant chimera immune response to indwelling electrode implant capadona inflammation
date: 02-02-2017 23:24 gmt
revision:1
[0] [head]
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PMID-24973296 The roles of blood-derived macrophages and resident microglia in the neuroinflammatory response to implanted intracortical microelectrodes.
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{1371} |
ref: -0
tags: nanotube tracking extracellular space fluorescent
date: 02-02-2017 22:13 gmt
revision:0
[head]
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PMID-27870840 Single-nanotube tracking reveals the nanoscale organization of the extracellular space in the live brain
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{1355} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-25705966 Robust and fragile aspects of cortical blood flow in relation to the underlying angioarchitecture.
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{927} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-18672003[0] Neurotrophic electrode: method of assembly and implantation into human motor speech cortex.
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{1360} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-22750248 In vivo effects of L1 coating on inflammation and neuronal health at the electrode-tissue interface in rat spinal cord and dorsal root ganglion.
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{1357} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Physical Metallurgy of Refactory Metals and Alloys Properties of tungsten-rhenium alloys
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{1353} |
ref: -0
tags: PEDOT electropolymerization electroplating gold TFB borate counterion acetonitrile
date: 10-18-2016 07:49 gmt
revision:3
[2] [1] [0] [head]
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PMID-20715789 Investigation of near ohmic behavior for poly(3,4-ethylenedioxythiophene): a model consistent with systematic variations in polymerization conditions.
PMID-24576579 '''Improving the performance of poly(3,4-ethylenedioxythiophene) for brain–machine interface applications"
PEDOT-modified integrated microelectrodes for the detection of ascorbic acid, dopamine and uric acid
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{1354} |
ref: -0
tags: David Kleinfeld penetrating arterioles perfusion cortex vasculature
date: 10-17-2016 23:24 gmt
revision:1
[0] [head]
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PMID-17190804 Penetrating arterioles are a bottleneck in the perfusion of neocortex.
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{1352} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-27571550 Stable long-term chronic brain mapping at the single-neuron level.
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{1350} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
A Wireless 32-Channel Implantable Bidirectional Brain Machine Interface
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{1348} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Heller Lecture - Prof. David Kleinfeld
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{1347} |
ref: -0
tags: laser induced breakdown spectroscopy for surgery tissue differentiation
date: 09-22-2016 19:26 gmt
revision:0
[head]
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PMID-25426327 Laser induced breakdown spectroscopy for bone and cartilage differentiation - ex vivo study as a prospect for a laser surgery feedback mechanism.
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{1346} |
ref: -0
tags: super resolution imaging PALM STORM fluorescence
date: 09-21-2016 05:57 gmt
revision:0
[head]
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PMID-23900251 Parallel super-resolution imaging
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{1337} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Useful numbers for estimating molecular mean-free-path in vacuum systems: "
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{1335} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
What are the concentrations of the monoamines in the brain? (Purpose: estimate the required electrochemical sensing area & efficiency)
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{1333} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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{1330} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
META II: Digital Vellum in the Digital Scriptorium: Revisiting Schorre's 1962 compiler-compiler
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{1204} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-21867803[0] Can histology solve the riddle of the nonfunctioning electrode? Factors influencing the biocompatibility of brain machine interfaces.
____References____
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{1325} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
https://mitpress.mit.edu/sites/default/files/titles/free_download/9780262526548_Art_of_Insight.pdf | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{1323} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{1318} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{1306} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-18640155 Characterization of flexible ECoG electrode arrays for chronic recording in awake rats.
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{1315} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Central Neuroanatomy of Electrosensory Systems in Fish
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{1311} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-11889591 Spontaneous nerve activity and sensitivity in catfish ampullary electroreceptor organs after tetanus toxin application
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{1309} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
The physiology of low-frequency electrosensory systems
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{1251} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
IEEE-938305 (pdf) High Density Interconnects and flexible hybrid assemblies for active biomedical implants
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{1308} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Kinetics of Alkaline Hydrolysis of a Polyimide Surface
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{1302} |
ref: -0
tags: kevlar electrodes flexible polymer 12um McNaughton Utah
date: 10-11-2014 00:19 gmt
revision:0
[head]
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PMID-8982987 Metallized polymer fibers as leadwires and intrafascicular microelectrodes
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{1300} |
ref: -0
tags: Peter Ledochowitsch ECoG parylene fabrication MEMS
date: 09-25-2014 16:54 gmt
revision:0
[head]
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IEEE-5734604 (pdf) Fabrication and testing of a large area, high density, parylene MEMS µECoG array
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{1299} |
ref: -0
tags: wirebonding finishes gold nickel palladium electroless electrolytic
date: 09-21-2014 02:53 gmt
revision:3
[2] [1] [0] [head]
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Why palladium? To prevent black nickel: http://tayloredge.com/reference/Electronics/PWB/BlackPad_ITRI_Round1.PD Introduction The use of electroless nickel / immersion gold (E.Ni/I.Au) as a circuit board finish has grown significantly in the last few years. It provides a flat board finish, is very solderable, provides a precious metal contact surface and the nickel strengthens the plated holes. However, as the usage of E.Ni/I.Au increased, a problem was found on BGA (Ball Grid Array) components. An open or fractured solder joint sometimes appears after board assembly on the occasional BGA pad. The solder had wet and dissolved the gold and formed a weak intermetallic bond to the nickel. This weak bond to the nickel readily fractures under stress or shock, leaving an open circuit. The incidence of this problem appears to be very sporadic and a low ppm level problem, but it is very unpredictable. A BGA solder joint cannot be touched-up without the component being removed. After the BGA component is removed, a black pad is observed at the affected pad site. This black pad is not readily solderable, but it can be repaired. From: http://www.smtnet.com/Forums/index.cfm?fuseaction=view_thread&Thread_ID=4430 You don't have enough gold. Your 2uin is too porous and is allowing the nickel to corrode. Prove that this by hand soldering to these pads with a more active flux, like a water soluble solder paste, than you are using. You must have at least 3uin of immersion gold. Seriously consider >5uin. Your nickel thickness is fine. Although if you wanted to trade costs, consider giving-up nickel to 150uin thickness, while increasing the gold thickness. Gold over electroless nickel creates brittle joints because of phosphorous in the nickel plating bath. The phosphorous migrates into the over-plating. Electrolytic nickel and gold plating should not be a problem. If you stay with the electroless nickel, keep the phosphorous at a mid [7 - 9%] level. Just as important, don't let the immersion gold get too aggressive. The immersion gold works by corroding the nickel. If it is too aggressive it takes away the nickel and leave phosphorous behind. This makes it look like the phosphorous level is too high in the nickel bath. Gold purity is very important for any type of wire bonding process. For aluminum wedge bonding, gold should have a purity of 99. 99% [no thalium] and the nickel becomes critical. No contaminates and the nickel wants to be plated a soft as possible. This requires good control of Ph and plating chemicals in the nickel-plating bath. Harman "Wire Bonding In Microelectronics" McGraw-Hill is a good resource for troubleshooting wire bonding. I reviewed it in the SMTnet Newsletter a couple of months ago. That said, electrolytic nickel + electrolytic gold does work well -- perhaps even better than ENEPIG: | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{1298} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-13539663 Subcortical threshold voltages as a function of sine wave frequencies Brown and Brackett
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{1297} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-4550167[1] Sensory responses elicited by subcortical high frequency electrical stimulation in man. -- everything innovative has already been done in the 70s!
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{875} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
One of the goals/needs of the lab is to be able to stimluate and record nervous tissue at the same time. We do not have immediate access to optogenetic methods, but what about lower frequency EM stimulation? The idea: if you put the stimulation frequency outside the recording system bandwidth, there is no need to switch, and indeed no reason you can't stimulate and record at the same time. Hence, I very briefly checked for the effects of RF stimulation on nervous tissue.
Conclusion: worth a shot, especially given the paper by Alberts et al 1972.
____References____
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{1296} |
ref: -0
tags: physical principles of scalable neural recording marblestone
date: 08-25-2014 20:21 gmt
revision:0
[head]
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PMID-24187539 Physical principles for scalable neural recording.
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{1295} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Pretty solid hike yesterday. 25.25 miles (or likely more, given the limited resolution of my tracing) in about 7.5 hours for an average speed of 3.4 mph. Lots of different terrain and eosystems along the way -- redwoods to lakeside to golden grassy hilltops to manzanita / scrub forest. Would be good for mountain biking. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{1292} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-1937509 A silicon-based, three-dimensional neural interface: manufacturing processes for an intracortical electrode array. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{1293} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-24216311 Failure mode analysis of silicon-based intracortical microelectrode arrays in non-human primates
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{1290} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-270699 Local control of neurite development by nerve growth factor.
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{1289} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
images/1289_1.pdf -- Debugging reinvented: Asking and Answering Why and Why not Questions about Program Behavior.
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{1288} |
ref: -0
tags: automatic programming inductive functional igor
date: 07-29-2014 02:07 gmt
revision:0
[head]
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Inductive Rule Learning on the Knowledge Level.
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{1286} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Biomechanics of substrate boring by fig wasps
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{1280} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Preparation of uniaxially oriented polyamide films by vacuum deposition polymerization
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{1278} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-23860226 A carbon-fiber electrode array for long-term neural recording.
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{1275} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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{1273} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Frequency-domain techniques for tissue spectroscopy and imaging
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{1271} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Community & housing links for San Francisco.
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{1203} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-17027251[0] Flexible polyimide microelectrode array for in vivo recordings and current source density analysis.
____References____
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{1267} |
ref: -0
tags: stretchable nanoparticle conductors gold polyurethane flocculation
date: 12-13-2013 02:12 gmt
revision:5
[4] [3] [2] [1] [0] [head]
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PMID-23863931 Stretchable nanoparticle conductors with self-organized conductive pathways.
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{1264} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-23852172 A comparison of polymer substrates for photolithographic processing of flexible bioelectronics
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{1258} |
ref: -0
tags: polyimide platinum electrodes Spain longitudinal intrafasicular adhesion delamination
date: 10-05-2013 22:24 gmt
revision:4
[3] [2] [1] [0] [head]
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PMID-17278585 Assessment of biocompatibility of chronically implanted polyimide and platinum intrafascicular electrodes. 2007
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{1259} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-24062716 A highly compliant serpentine shaped polyimide interconnect for front-end strain relief in chronic neural implants.
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{1248} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Improved polyimide/metal adhesion by chemical modification approaches
IEEE-4936772 (pdf) Studies of adhesion of metal films to polyimide
IEEE-670747 (pdf) Adhesion evaluation of adhesiveless metal/polyimide substrate for MCM and high density packaging
On polyimide-polyimide interlayer adhesion: Diffusion and self-adhesion of the polyimide PMDA-ODA (1987)
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{1257} |
ref: -0
tags: Anna Roe optogenetics artificial dura monkeys intrinisic imaging
date: 09-30-2013 19:08 gmt
revision:3
[2] [1] [0] [head]
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PMID-23761700 Optogenetics through windows on the brain in nonhuman primates
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{1249} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-21273316 Physiological clustering of visual channels in the mouse retina
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{1242} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
We're making parylene electrodes for neural recording, and one critical step is connecting them to recording electronics. Currently Berkeley uses ACF (anisotropic conductive film) for connection, which is widely used for connecting flex tape to LCD panels, or for connecting driver chips to LCD glass. According to the internet, pitches can be as low as 20um, with pad areas as low as 800um^2. source However, this does not seem to be a very reliable nor compact process with platinum films on parylene, possibly because ACF bonding relies on raised areas between mated conductors (current design has the Pt recessed into the parylene), and on rigid substrates. ACF consists of springy polymer balls coated in Ni and Au and embedded in a thermoset epoxy resin. The ACF film is put under moderate temperature (180C) and pressure (3mpa, 430psi), which causes the epoxy to cure in a state that leaves the gold/nickel/polymer balls to be compressed between the two conductors. Hence, even if the conductors move slightly due to thermal cycling, the small balls maintain good mechanical and electrical contact. The balls are dispersed sufficiently in the epoxy matrix that there is little to no chance of conduction between adjacent pads. (Or so I have learned from the internet.) Now, as mentioned, this is an imperfect method for joining Pt on parylene films, possibly because the parylene is so flexible, and the platinum foil is very thin (200-300 nm). Indeed, platinum does not bond very strongly to parylene, hence care must be taken to allow sufficient overlap to prevent water ingress. My proposed solution -- to be tested shortly -- is to use a low-melting temperature metal with strong wetting ability -- such as Field's metal (bismuth, tin, indium, melting point 149F, see http://www.gizmology.net/fusiblemetals.htm) to low-temperature solder the platinum to a carrier board (initially) or to a custom amplifier ASIC (later!). Parylene is stable to 200C (392F), so this should be safe. One worry is that the indium/bismuth will wet the parylene or polyimide, too; however I consider this unlikely due to the difficulty in attaching parylene to any metal. That said, there must be good reason why ACF is so popular, so perhaps a better ultimate solution is to stiffen the parylene (or ultimately polyimide) substrate so that it can support both the temperature/pressure of ACF bonding and the stress of a continued electrical/mechanical bond to polyimide fan-out board or ASIC. It may also be possible to gold or nickel electroplate the connector pads to be slightly raised instead of recessed. Update: ACF bond to rigid 1/2 oz copper, 4mil trace / space connector (3mil trace/space board): Note that the copper traces are raised, and the parylene is stretched over the uneven surface (this is much easier to see with the stereo microscope). To the left of the image, the ACF paste has been sqeezed out from between the FR4 and parylene. Also note that the platinum can make potential contact with vias in the PCB. Update 7/2: Fields metal (mentioned above) does stick to platinum reasonably well, but it also sticks to parylene (somewhat), and glass (exceptionally well!). In fact, I had a difficult time removing traces of field's metal from the Pyrex beakers that I was melting the metal with. These beakers were filled with boiling water, which may have been the problem. When I added flux (Kester flux-pen 951 No-clean MSDS), the metal became noticeably more shiny, and the contact angle increased on the borosilicate glass (e.g. looked more like mercury); this leads me to believe that it is not the metal itself that attaches to glass, but rather oxides of indium and bismuth. Kester 951 flux consists of:
After coating the parylene/platinum sample with flux, I raised the field's metal to the flux activation point, which released some smoke and left brown organic residues on the bottom of the glass dish. Then I dipped the parylene probe into the molten metal, causing the flux again to be activated, and partially wetting the platinum contacts. The figure below shows the result: Note the incomplete wetting, all the white solids left from the process, and how the field's metal caused the platinum to delaminate from the parylene when the cable was (accidentally) flexed. Tests with platinum foil revealed that the metal bond was not actually that strong, significantly weaker than that made with a flux-core SnPb solder. also, I'm not sure of the activation temperature of this flux, and think I may have overheated the parylene. Update 7/10: Am considering electrodeless Ni / Pt / Au deposition, which occurs in aqueous solution, hence at much lower temperatures than e-beam evaporation Electrodeless Ni ref. On polyimide substrates, there is extensive literature describing how to activate the surface for plating: Polyimides and Other High Temperature Polymers: Synthesis ..., Volume 4. Parylene would likely need a different possibly more aggressive treatment, as it does not have imide bonds to open. Furthermore, if the parylene / polyimide surface is *not* activated, the electrodeless plating could be specific to the exposed electrode and contact sites, which could help to solve the connector issue by strengthening & thickening the contact areas. The second fairly obvious solution is to planarize the contact site on the PCB, too, as seen above. ACF bonds can be quite reliable; last night I took apart (and successfully re-assembled) my 32" Samsung LCD monitor, and none of the flex-on-glass or chip-on-flex binds failed (despite my clumsy hands!). | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{1246} |
ref: -0
tags: parylene microchannel micromolding glass transition temperature microfluidics
date: 06-28-2013 17:34 gmt
revision:3
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Parylene micromolding, a rapid low-cost fabrication method for parylene microchannel
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PMID-23010756[0] Comprehensive characterization and failure modes of tungsten microwire arrays in chronic neural implants.
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So, a year and a half ago I bought a green 1995 900 SE convertible for $600. At that time, it didn't move or go in reverse. Since then, I've been fixing up random things here an there (or just straight modifying / breaking the car by other standards) and recently realized that I had better start keeping track of everything that's been done, in case my memory lapses or i need to know where some random part came from. I doubt this will be useful to anyone else - next time, pictures! Things that I've done to the green convertible, in approximate chronological order:
Things that need to be done to the 'vert:
Now, wonders of wonders, I have another of these cars - though a sedan, not a convertible. It cost much more (about 8x as much), and is hence in much better shape. That said, I've had to do the following:
And now the blue 1998 saab 900, sold to Adam:
Next, the saab 9000 aero:
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PMID-1601445 Factors influencing the biocompatibility of insertable silicon microshafts in cerebral cortex.
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PMID-21228307 Ultrasmall and customizable multichannel electrodes for extracellular recordings
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PMID-23428842 Chronic intracortical microelectrode arrays induce non-uniform, depth-related tissue responses.
This result is supported by previous papers:
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{1230} |
ref: -0
tags: dissertation interconnect parylene flexible electrodes
date: 02-26-2013 00:30 gmt
revision:2
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http://docs.lib.purdue.edu/dissertations/AAI3444877/
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PMID-11327505 Flexible Polyimide-Based Intracortical Electrode Arrays with Bioactive Capability
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PMID-19255461[0] Development and characterization of in vivo flexible electrodes compatible with large tissue displacements.
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Things to read! decoding:
electrodes:
other random scribblings: Vascularization {1027} histology {736},{737} and size {1028},{747},{1026}, insulation {1033}. How very very important -- as important or moreso than the recording technology. What has happened to {149} ? | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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PMID-17946847[0] Preliminary study of multichannel flexible neural probes coated with hybrid biodegradable polymer. ____References____
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{1177} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
IEEE-1196780 (pdf) 3D flexible multichannel neural probe array
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PMID-14741588[0] Chronic response of adult rat brain tissue to implants anchored to the skull.
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PMID-22170970[0] A system for recording neural activity chronically and simultaneously from multiple cortical and subcortical regions in non-human primates. ____References____
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PMID-20153370[0] A bio-friendly and economical technique for chronic implantation of multiple microelectrode arrays ____References____
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{78} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-17067683[0] A floating metal microelectrode array for chronic implantation
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PMID-9350963 A floating microwire technique for multichannel neural recording and stimulation in the awake rat
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PMID-10906696[0] Tissue response to single-polymer fibers of varying diameters: evaluation of fibrous encapsulation and macrophage density.
"
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PMID-9723616[0] Signal-dependent noise determines motor planning.
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!:
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PMID-21867802[0] Reducing surface area while maintaining implant penetrating profile lowers the brain foreign body response to chronically implanted planar silicon microelectrode arrays.
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{1198} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-22049097[0] Mechanically adaptive intracortical implants improve the proximity of neuronal cell bodies.
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{1207} |
ref: -0
tags: Shenoy eye position BMI performance monitoring
date: 01-25-2013 00:41 gmt
revision:1
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PMID-18303802 Cortical neural prosthesis performance improves when eye position is monitored.
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{1206} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-19164034 Cortical recording with polypyrrole microwire electrodes.
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{1202} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-22254391 Chronic intracortical implantation of saccharose-coated flexible shaft electrodes into the cortex of rats. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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PMID-17409479[0] Thin microelectrodes reduce GFAP expression in the implant site in rodent somatosensory cortex.
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{1192} |
ref: -2002
tags: sea slugs flexible electrodes polymide Washington
date: 01-04-2013 18:46 gmt
revision:0
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IEEE-1002325 (pdf) Silicon micro-needles with flexible interconnections
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{1102} |
ref: Gilletti-2006.09
tags: electrode micromotion histology GFAP variable reluctance
date: 01-04-2013 02:28 gmt
revision:2
[1] [0] [head]
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PMID-16921202[0] Brain micromotion around implants in the rodent somatosensory cortex.
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{1189} |
ref: -0
tags: microelectrode array flexible PDMS via interconnect Georgia
date: 01-04-2013 00:33 gmt
revision:0
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IEEE-6197244 (pdf) A PDMS-Based Integrated Stretchable Microelectrode Array (isMEA) for Neural and Muscular Surface Interfacing | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{1188} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
IEEE-906517 (pdf) Flexible microelectrode arrays with integrated insertion devices
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PMID-23160191 Novel flexible Parylene neural probe with 3D sheath structure for enhancing tissue integration
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{1187} |
ref: -0
tags: neural recording topologies circuits operational transconductance amplifiers
date: 01-02-2013 20:00 gmt
revision:0
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PMID-22163863 Recent advances in neural recording microsystems. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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PMID-20622860 Imaging brain electric signals with genetically targeted voltage-sensitive fluorescent proteins.
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PMID-22308458 Optically monitoring voltage in neurons by photo-induced electron transfer through molecular wires.
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Demonstration of cortical recording using novel flexible polymer neural probes
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{1169} |
ref: -0
tags: artificial intelligence projection episodic memory reinforcement learning
date: 08-15-2012 19:16 gmt
revision:0
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Projective simulation for artificial intelligence
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A frequent task in the lab is to sort spikes (extracellular neural action potentials) from background noise. In the lab we are working on doing this wirelessly; to minimize power consumption, spike sorting is done before the radio. In this way only times of spikes need be transmitted, saving bandwidth and power. (This necessitates a bidirectional radio protocol, but this is a worthy sacrifice). In most sorting programs (e.g. Plexon), the raw signal is first thresholded, then waveform snippets (typically 32 samples long) are compared to a template to accept/reject them, or to sort them into different units. The comparison metric is usually the mean-squared error, MSE, aka the L2 norm. This makes sense, as the spike shapes are assumed to be stereotyped (they may very well not be), and the noise white / uncorrelated (another debatable assumption). On the headstage we are working with for wireless neural recording, jumps and memory moves are expensive operations, hence we've elected to do no waveform extraction, and instead match continuously match. By using the built-in MPEG compression opcodes, we can compute the L1 norm at a rate of 4 samples / clock -- very efficient. However, this was more motivated by hardware considerations an not actual spike sorting practice. Literature suggests that for isolating a fixed-pattern signal embedded in noise, the best solution is instead a matched filter. Hence, a careful study of spike-sorting was attempted in matlab, given the following assumptions: fixed spike shape (this was extracted from real data), and uncorrelated band-limited noise. The later was just white noise passed through a bandpass filter, e.g. cheby1(3, 2, [500/15e3 7.5/15]) Where the passband edges are 500 Hz and 15kHz, at a sampling rate of 30kHz. (Actual rate is 31.25kHz). Since the spike times are known, we can rigorously compare the Receiver Operating Characteristic (ROC) and the area under curve (AUC) for different sorting algorithms. Four were tried: L1 (as mentioned above, motivated by the MPEG opcodes), L2 (Plexon), FIR matched filter, and IIR matched filter. The latter was very much an experiment -- IIR filters are efficiently implemented on the blackfin processor, and they generally require fewer taps than their equivalent FIR implementation. To find an IIR equivalent to a given FIR matched filter (whose impulse response closely looks like the actual waveshape, just time-reversed), the filter parameters were simply optimized to match the two impulse responses. To facilitate the search, the denominator was specified in terms of complex conjugate pole locations (thereby constraining the form of the filter), while the numerator coefficients were individually optimized. Note that this is not optimizing given the objective to maximize sorting quality -- rather, it is to make the IIR filter impulse response as close as possible to the FIR matched filter, hence computationally light. And yet: the IIR filter outperforms the FIR matched filter, even though the IIR filter has 1/3 the coefficients (10 vs 32)! Below is the AUC quality metric for the four methods. And here are representative ROC curves at varying spike SNR ratios. The remarkable thing is that even at very low SNR, the matched IIR filter can reliably sort cells from noise. (Note that the acceptable false positive here should be weighted more highly; in the present analysis true positive and false positive are weighted equally, which is decidedly non-Bayesian given most of the time there is no spike.) The matched IIR filter is far superior to the normal MSE to template / L2 norm method -- seems we've been doing it wrong all along? As for reliably finding spikes / templates / filters when the SNR < 0, the tests above - which assume an equal number of spike samples and non-spike samples -- are highly biased; spikes are not normally sortable when the SNR < 0. Upon looking at the code again, I realized three important things:
Including #1 above, as expected, dramatically increased the false positive rate, which is to be expected and how the filters will be used in the real world. #2 did not dramatically impact any of the discriminators, which is good. #3 alleviated the gap between the IIR and FIR filters, and indeed the FIR matched filter performance now slightly exceeds the IIR matched filer. Below, AUC metric for 4 methods. And corresponding ROC for 6 different SNR ratios (note the SNRs sampled are slightly different, due to the higher false positive rate). One thing to note: as implemented, the IIR filter requires careful matching of poles and zeros, and is may not work with 1.15 fixed-point math on the Blackfin. The method really deserves to be tested in vivo, which I shall do shortly. More updates: See www.aicit.org/jcit/ppl/JCIT0509_05.pdf -- they add an 'adjustment' function to the matched filter due to variance in the amplitude of spikes, which adds a little performance at low SNRs.
Sigma is the standard deviation of x(t), n and k determine 'zoom intensity and zoom center'. The paper is not particularly well written - there are some typos, and their idea seems unjustified. Still the references are interesting:
Update: It is not to difficult to convert FIR filters to IIR filters using simple numerical optimization. Within my client program, this is done using simulated annealing; have tested this using fminsearch in matlab. To investigate the IIR-filter fitting problem more fully, I sliced the 10-dimensional optimization space along pairs of dimensions about the optimum point as found using fminsearch. The parameters are as follows:
The figure below plots the +-1 beyond the optimum for each axis pair. Click for full resolution image. Note that the last parameter is discrete, hence steps in the objective function. Also note that the problem is perfectly quadratic for the numerator, as expected, which is why LMS works so well. Note that for the denominator pole locations, the volume of the optimum is small, and there are interesting features beyond this. Some spaces have multiple optima. The next figure plots +-0.1 beyond the optimum for each axis vs. every other one. It shows that, at least on a small scale, the problem becomes very quadratic in all axes hence amenable to line or conjugate gradient search. Moving away from planes that pass through a found optima, what does the space look like? E.g. From a naive start, how hard is it to find at least one workable solution? To test this, I perturbed the found optimum with white noise in the parameters std 0.2, and plotted the objective function as before, albeit at higher resolution (600 x 600 points for each slice). These figures show that there can be several optima in the denominator, but again it appears that a very rough exploration followed by gradient descent should arrive at an optima. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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PMID-14634657[0]Inference of hand movements from local field potentials in monkey motor cortex
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PMID-22157115 Decoding 3D reach and grasp from hybrid signals in motor and premotor cortices: spikes, multiunit activity, and local field potentials.
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Just to my left, a woman in a walker rolled into the library, and promptly complained to the police officer on duty about chest pains. The library faces a square in the middle of Springfield where teenagers, shirtless hippies, skateboarders, and other non-mainstream people kill time in the warm afternoon. The library as such is a cool haven to read and access the internet -- several teenagers were playing WoW on the library computers, and I too am tapping into the resource. A possibly adrift artsy-type man of about my age similarly came to conduct his wayward business, having 'just ended up in Springfield', saying it as both and excuse and a badge of pride evincing his free spirit. The woman is one of the classic types of hypochondriac, and though I'm only listening to them the EMT and police men know this, but they also know that on the off chance of being wrong, not taking the situation seriously could be a disaster. And so they administered simple blood pressure and pulse rate tests, both which seemed normal, then went about convincing her that she needed to be taken to the hospital to be completely checked out, thereby shifting the burden of liability to a place better protected by the standard operating procedure of a battery of tests. The woman immediately protested, worried about the heavy cost of a ambulance ride, coupled with a paranoia that she would lose her walker. To this the EMT -- a short woman with her practical ponytail shoved through a baseball cap, as often they do -- let glints of irritation show through, asking her repeatedly to decide which hospital she wished to go to, and then asking her to arrange another means to the hospital. The woman protested, but the EMT could scarecly be blamed -- she is stuck in a system not of her design -- and somehow the smooth-souled librarian, who before had been placating library customers by putting holds on books, convinced both parties to go to the nearest hopsital. How exactly this was done I'll forever remain in ignorance, for another ambulance spun through the downtown circle at that instant, scattering sports cars, stopping sedans, and causing the skaters to pause their idling and look. The incident vaguely reminds me when I had similar issues in Brooklyn, when i was sufficiently pained to drive my ass through the dirty orange-lit streets to a hospital in Williamsburg. They proceeded to do drug tests on me, despite my insistences, but everything checked out fine. In retrospect, the pain was likely heartburn antagonized by psychological isolation; this was before I really learned to listen to myself, and take care of the social and more basic physiological needs. The walker woman fell through these same cracks in a likely preventable but now very expensive way. Meanwhile, a large black transsexual and a wrinkly white guy walk hurriedly past the plate glass windows of the library, talking animatedly. They may be in a fissure of sorts, but i doubt they consider it a fall... | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{1159} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
I highly agree with this philosophy / this deconstruction of the flow of information in human structures: http://www.lostgarden.com/2012/04/loops-and-arcs.html On criticism as a meta-arc game: "In the past I've discussed criticism as a game that attempts to revisit an arc repeatedly and embellish it with additional meaning. The game is to generate essays superficially based on some piece of existing art. In turn, other players generate additional essays based off the first essays. This acts as both a referee mechanism and judge. Score is accumulated via reference counts and by rising through an organization hierarchy. It is a deliciously political game of wit that is both impenetrable to outsiders and nearly independent of the actual source arcs. Here creating an arc becomes a move in the larger game. " | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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IEEE-4353634 (pdf) Optimal Operating Frequency in Wireless Power Transmission for Implantable Devices
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PMID-16271465 The basal ganglia: learning new tricks and loving it
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DBS refs (for translating from word to my latex-based build system):
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PMID-19299613[0] Spinal cord stimulation restores locomotion in animal models of Parkinson's disease.
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{1087} |
ref: Timmermann-2003.01
tags: DBS double tremor oscillations DICS beamforming parkinsons
date: 02-29-2012 00:39 gmt
revision:4
[3] [2] [1] [0] [head]
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PMID-12477707[0] The cerebral oscillatory network of parkinsonian resting tremor.
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PMID-15703229[0] Spontaneous pallidal neuronal activity in human dystonia: comparison with Parkinson's disease and normal macaque.
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{1144} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-15242667 Anatomical funneling, sparse connectivity and redundancy reduction in the neural networks of the basal ganglia
PMID-15233923 Coincident but distinct messages of midbrain dopamine and striatal tonically active neurons.
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{1140} |
ref: -0
tags: dopamine reward prediction striatum error striatum orbitofrontal reward
date: 02-24-2012 21:26 gmt
revision:1
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PMID-11105648 Involvement of basal ganglia and orbitofrontal cortex in goal-directed behavior.
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{1141} |
ref: -0
tags: putamen functional organization basal ganglia
date: 02-24-2012 21:01 gmt
revision:0
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PMID-6705861 Single cell studies of the primate putamen. I. Functional organization.
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{1081} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-20855421[0] Mapping Go-No-Go performance within the subthalamic nucleus region.
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{1088} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-18540149[0] Deep brain stimulation: how does it work?
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{206} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-12077209[0][] High-frequency stimulation of the subthalamic nucleus selectively reverses dopamine denervation-induced cellular defects in the output structures of the basal ganglia in the rat.
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{1076} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-17017503[0] Synchronizing activity of basal ganglia and pathophysiology of Parkinson's disease.
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{1071} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-12495873[0] Relationship between oscillations in the basal ganglia and synchronization of cortical activity.
Also, random: the world's highest rate of Parkinson's disease is in the Amish in the NE US. More than twice that of anywhere else; http://www.viartis.net/parkinsons.disease/news/090801.htm ____References____
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{88} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-16549385[0] The effect of subthalamic nucleus deep brain stimulation on precision grip abnormalities in Parkinson's disease
See also PMID-19266149[1] Distal and proximal prehension is differentially affected by Parkinson‘s disease The effect of conscious and subconscious load cues
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PMID-20400953 Dissolvable films of silk fibroin for ultrathin conformal bio-integrated electronics.
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{1125} |
ref: -0
tags: active filter design Netherlands Gerrit Groenewold
date: 02-17-2012 20:27 gmt
revision:0
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IEEE-04268406 (pdf) Noise and Group Delay in Actvie Filters
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{1110} |
ref: -0
tags: Seymour thesis electrode lithography fabrication
date: 02-05-2012 17:35 gmt
revision:4
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Advanced polymer-based microfabricated neural probes using biologically driven designs.
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PMID-16317234 A finite-element model of the mechanical effects of implantable microelectrodes in the cerebral cortex.
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PMID-19286561[0] Human Substantia Nigra Neurons Encode Unexpected Financial Rewards
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PMID-14960502[0] Event-related beta desynchronization in human subthalamic nucleus correlates with motor performance.
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{82} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-16973296[0] Subthalamic nucleus neurones in slices from MPTP-lesioned mice show irregular, dopamine-reversible firing pattern changes, but without synchronous activity
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{204} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-1707079 Subthalamic nucleus of the monkey: connections and immunocytochemical features of afferents.
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PMID-19070616[0] Pathological synchronisation in the subthalamic nucleus of patients with Parkinson's disease relates to both bradykinesia and rigidity.
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{248} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-16280671[0] Deep-brain stimulation in Parkinson's disease: long-term efficacy and safety - What happened this year?
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{165} |
ref: Lehericy-2005.08
tags: fMRI motor_learning basal_ganglia STN subthalamic
date: 01-25-2012 00:20 gmt
revision:2
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PMID-16107540[0] Distinct basal ganglia territories are engaged in early and advanced motor sequence learning
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{566} |
ref: Sakai-2001.06
tags: voltage scensitive fluorescent protein flourophore VSFP1 endoscope
date: 01-24-2012 06:07 gmt
revision:5
[4] [3] [2] [1] [0] [head]
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http://www.blackwell-synergy.com/doi/full/10.1046/j.0953-816x.2001.01617.x PMID-11454036[0]
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{1085} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-21603228[0] Dopaminergic Balance between Reward Maximization and Policy Complexity.
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{1082} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Just fer kicks, I tested what happens to low-order butterworth filters when you maladjust one of the feedback coefficients. [B, A] = butter(2, 0.1); [h, w] = freqz(B,A); A(2) = A(2) * 0.9; [h2, ~] = freqz(B,A); hold off subplot(1,2,1) plot(w,abs(h)) hold on; plot(w,abs(h2), 'r') title('10% change in one FB filter coef 2nd order butterworth') xlabel('freq, rads / sec'); ylabel('filter response'); % do the same for a higher order filter. [B, A] = butter(3, 0.1); [h, w] = freqz(B,A); A(2) = A(2) * 0.9; [h2, ~] = freqz(B,A); subplot(1,2,2) hold on plot(w,abs(h), 'b') plot(w,abs(h2), 'r') title('10% change in one FB filter coef 3rd order butterworth') xlabel('freq, rads / sec'); ylabel('filter response'); The filters show a resonant peak, even though feedback was reduced. Not surprising, really; a lot of systems will show reduced phase margin and will begin to oscillate when poles are moved. Does this mean that a given coefficient (anatomical area) is responsible for resonance? By itself, of course not; one can not extrapolate one effect from one manipulation in a feedback system, especially a higher-order feedback system. This, of course hold in the mapping of digital (or analog) filters to pathology or anatomy. Pathology is likely reflective of how the loop is structured, not how one element functions (well, maybe). For a paper, see {1083} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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PMID-6869036[0] The Piper rhythm--a phenomenon related to muscle resonance characteristics?
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{255} |
ref: BarGad-2003.12
tags: information dimensionality reduction reinforcement learning basal_ganglia RDDR SNR globus pallidus
date: 01-16-2012 19:18 gmt
revision:3
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PMID-15013228[] Information processing, dimensionality reduction, and reinforcement learning in the basal ganglia (2003)
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{1061} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
IEEE-5969351 (pdf) New class of chronic recording multichannel neural probes with post-implant self-deployed satellite recording sites | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{214} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
IEEE-1201998 (pdf) A low-power low-noise CMOS amplifier for neural recording applications
Harrison, R.R. and Charles, C. A low-power low-noise CMOS amplifier for neural recording applications Solid-State Circuits, IEEE Journal of 38 6 958 - 965 (2003) | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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I've recently tried to determine the bit-rate of conveyed by one gaussian random process about another in terms of the signal-to-noise ratio between the two. Assume is the known signal to be predicted, and is the prediction. Let's define where . Note this is a ratio of powers; for the conventional SNR, . is also known as the mean-squared-error (mse). Now, ; assume x and y have unit variance (or scale them so that they do), then
We need the covariance because the mutual information between two jointly Gaussian zero-mean variables can be defined in terms of their covariance matrix: (see http://www.springerlink.com/content/v026617150753x6q/ ). Here Q is the covariance matrix,
Then or This agrees with intuition. If we have a SNR of 10db, or 10 (power ratio), then we would expect to be able to break a random variable into about 10 different categories or bins (recall stdev is the sqrt of the variance), with the probability of the variable being in the estimated bin to be 1/2. (This, at least in my mind, is where the 1/2 constant comes from - if there is gaussian noise, you won't be able to determine exactly which bin the random variable is in, hence log_2 is an overestimator.) Here is a table with the respective values, including the amplitude (not power) ratio representations of SNR. "
Now, to get the bitrate, you take the SNR, calculate the mutual information, and multiply it by the bandwidth (not the sampling rate in a discrete time system) of the signals. In our particular application, I think the bandwidth is between 1 and 2 Hz, hence we're getting 1.6-3.2 bits/second/axis, hence 3.2-6.4 bits/second for our normal 2D tasks. If you read this blog regularly, you'll notice that others have achieved 4bits/sec with one neuron and 6.5 bits/sec with dozens {271}. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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PMID-19199762[0] Optical Detection of Brain Cell Activity Using Plasmonic Gold Nanoparticles
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{315} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-16200750[0] Wireless Multichannel Biopotential Recording Using an Integrated FM Telemetry Circuit Pedram Mohseni, Khalil Najafi, Steven Eliades, Xiaoquin Wang.
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{1049} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
IEEE-4353193 (pdf) A Sub-Microwatt Low-Noise Amplifier for Neural Recording
____References____ Holleman, J. and Otis, B. Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE 3930 -3933 (2007) | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{1051} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
IEEE-5226763 (pdf) An Implantable 64-Channel Wireless Microsystem for Single-Unit Neural Recording
____References____ Sodagar, A.M. and Perlin, G.E. and Ying Yao and Najafi, K. and Wise, K.D. An Implantable 64-Channel Wireless Microsystem for Single-Unit Neural Recording Solid-State Circuits, IEEE Journal of 44 9 2591 -2604 (2009) | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{1055} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
IEEE-5230909 (pdf) A High Resolution Bi-Directional Communication through a Brain-Chip Interface
____References____ Maschietto, M. and Mahmud, M. and Stefano, G. and Vassanelli, S. Advanced Technologies for Enhanced Quality of Life, 2009. AT-EQUAL '09. 32 -35 (2009) | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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IEEE-4358095 (pdf) An Ultra-Low-Power Neural Recording Amplifier and its use in Adaptively-Biased Multi-Amplifier Arrays.
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PMID-3957372[0] Solid-state electrodes for multichannel multiplexed intracortical neuronal recording.
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PMID-95711[0] Spike separation in multiunit records: A multivariate analysis of spike descriptive parameters
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{782} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
IEEE-5067358 (pdf) Wireless, Ultra Low Power, Broadband Neural Recording Microsystem
____References____ Song, Y.-K. and Borton, D.A. and Park, S. and Patterson, W.R. and Bull, C.W. and Laiwalla, F. and Mislow, J. and Simeral, J.D. and Donoghue, J.P. and Nurmikko, A.V. Active Microelectronic Neurosensor Arrays for Implantable Brain Communication Interfaces Neural Systems and Rehabilitation Engineering, IEEE Transactions on 17 4 339 -345 (2009) | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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PMID-18018699[0] HermesB: a continuous neural recording system for freely behaving primates.
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IEEE-1300783 (pdf) Transmission latencies in a telemetry-linked brain-machine interface
____References____ Bossetti, C.A. and Carmena, J.M. and Nicolelis, M.A.L. and Wolf, P.D. Transmission latencies in a telemetry-linked brain-machine interface Biomedical Engineering, IEEE Transactions on 51 6 919 -924 (2004.06) | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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PMID-18923392[0] Direct control of paralysed muscles by cortical neurons.
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PMID-19603074[0] Unscented Kalman filter for brain-machine interfaces.
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PMID-114271[0] Operant control of precentral neurons: the role of reinforcement schedules.
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PMID-7418770[0] Operant control of precentral neurons: the role of audio and visual feedback.
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PMID-7409057[0] Operant control of precentral neurons: comparison of fast and slow pyramidal tract neurons.
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{904} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-6769536[0] Operant control of precentral neurons: Control of modal interspike intervals
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{341} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-4196269[0] Operantly conditioned patterns on precentral unit activity and correlated responses in adjacent cells and contralateral muscles
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{303} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-4974291[0] Operant conditioning of cortical unit activity
PMID-5000088[1] Operant conditioning of specific patterns of neural and muscular activity. In awake monkeys we recorded activity of single "motor" cortex cells, four contralateral arm muscles, and elbow position, while operantly reinforcing several patterns of motor activity. With the monkey's arm held semiprone in a cast hinged at the elbow, we reinforced active elbow movements and tested cell responses to passive elbow movements. With the cast immobilized we reinforced isometric contraction of each of the four muscles in isolation, and bursts of cortical cell activity with and without simultaneous suppression of muscle activity. Correlations between a precentral cell and specific arm muscles consistently appeared under several behavioral conditions, but could be dissociated by reinforcing cell activity and muscle suppression. PMID-4624487[2] Operant conditioning of isolated activity in specific muscles and precentral cells Recorded precentral units in monkeys, trained to contract 4 arm muscles in isolation, under various conditions: passive movements and cutaneous stimulation, active movements and isometric contractions. Some Ss were also reinforced for activity of cortical cells, with no contingency in muscle activity and with simultaneous suppression of all muscular activity. It is concluded that temporal correlations between activity of precentral cells and some other component of the motor response, e.g., muscle activity, force, or position, may depend as strongly on the specific response pattern which is reinforced as on any underlying physiological connection. ____References____ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{918} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-9537321[0] Somatosensory discrimination based on cortical microstimulation.
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{956} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
bibtex: Fetz-1992 Are movement parameters recognizably coded in the activity of single neurons
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{997} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
IEEE-1484848 (pdf) A high-yield IC-compatible multielectrode recording array.
____References____ Najafi, K. and Wise, K.D. and Mochizuki, T. A high-yield IC-compatible multichannel recording array Electron Devices, IEEE Transactions on 32 7 1206 - 1211 (1985) | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{607} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
from the book "Neural Prostheses for Restoration of Sensory and Motor Function" edited by John Chapin and Karen Moxon. Phillip Kennedy's one-channel neurotrophic glass electrode BMI (axons apparently grew into the electrode, and he recorded from them) Pat Wolf on neural amplification / telemetry technology battery technology for powering the neural telemetry | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{349} |
ref: thesis-0
tags: clementine 042007 operant conditioning biofeedback tlh24
date: 01-06-2012 03:08 gmt
revision:4
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channel 29 controlled the X direction: channel 81, the Y direction (this one was very highly modulated, and the monkey could get to a high rate ~60Hz. note that both units are sorted as one -- I ought to do the same on the other channels from now on, as this was rather predictive (this is duplicating Debbie Won's results): However, when I ran a wiener filter on the binned spike rates (this is not the rates as estimated through the polynomial filter), ch 81 was most predictive for target X position; ch 29, Y target position (?). This is in agreement with population-wide predictions of target position: target X was predicted with low fidelity (1.12; cc = 0.35 or so); target Y was, apparently, unpredicted. I don't understand why this is, as I trained the monkey for 1/2 hour on just the opposite. Actually this is because the targets were not in a random sequence - they were in a CCW sequence, hence the neuronal activity was correlated to the last target, hence ch 81 to target X! for reference, here is the ouput of bmi_sql: order of columns: unit,channel, lag, snr, variable ans = 1.0000 80.0000 5.0000 1.0909 7.0000 1.0000 80.0000 4.0000 1.0705 7.0000 1.0000 80.0000 3.0000 1.0575 7.0000 1.0000 80.0000 2.0000 1.0485 7.0000 1.0000 80.0000 1.0000 1.0402 7.0000 1.0000 28.0000 4.0000 1.0318 8.0000 1.0000 76.0000 2.0000 1.0238 11.0000 1.0000 76.0000 5.0000 1.0225 11.0000 1.0000 17.0000 0 1.0209 11.0000 1.0000 63.0000 3.0000 1.0202 8.0000 movies of the performance are here: | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{222} |
ref: neuro notes-0
tags: clementine thesis electrophysiology fit predictions tlh24
date: 01-06-2012 03:07 gmt
revision:4
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ok, so i fit all timestamps from clem022007001 & timarm_log_070220_173947_k.mat to clementine's behavior, and got relatively low SNR for almost everything - despite the fact that I am most likely overfitting. (bin size = 7802 x 1491) the offset is calibrated @ 2587 ms + 50 to center the juice artifact in the first bin. There are 10 lags. There are 21 sorted units. same thing, but with only the sorted units. juice prediction is, of course, worse. now, for file clem022007002 & timarm_log_070220_175636_k.mat. first the unsorted: and the sorted: | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{249} |
ref: notes-0
tags: sorting SNR correlation coefficient expectation maximization tlh24
date: 01-06-2012 03:07 gmt
revision:5
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Description: red is the per-channel cross-validated correlation coeifficent of prediction. Blue is the corresponding number of clusters that the unit was sorted into, divided by 10 to fit on the same axis. The variable being predicted is cartesian X position. note 32 channels were dead (from PP). The last four (most rpedictive) channels were: 71 (1 unit), 64 (5 units), 73 (6 units), 67 (1 unit). data from sql entry: clem 2007-03-08 18:59:27 timarm_log_20070308_185706.out ;Looks like this data came from PMD region. Description: same as above, but for the y-axis. Description: same as above, but for the z-axis. Conclusion: sorting seems to matter & have a non-negligible positive effect on predictive ability. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{175} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{1034} |
ref: Towe-2007.05
tags: RF recording passive backscatter variactors
date: 01-06-2012 02:56 gmt
revision:3
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IEEE-4227238 (pdf) Passive Backscatter Biotelemetry for Neural Interfacing
IEEE-5993487 (pdf) A Fully Passive Wireless Microsystem for Recording of Neuropotentials Using RF Backscattering Methods
____References____ Towe, B.C. Neural Engineering, 2007. CNE '07. 3rd International IEEE/EMBS Conference on 144 -147 (2007) | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{1008} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
IEEE-5946801 (pdf) A low-power implantable neuroprocessor on nano-FPGA for Brain Machine interface applications
____References____ Fei Zhang and Aghagolzadeh, M. and Oweiss, K. Acoustics, Speech and Signal Processing (ICASSP), 2011 IEEE International Conference on 1593 -1596 (2011) | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{949} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-18509337[0] Cortical control of a prosthetic arm for self-feeding
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{990} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-19464514[0] Three-dimensional, automated, real-time video system for tracking limb motion in brain-machine interface studies.
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{482} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-17978021[0] Biomimetic Brain Machine Interfaces for the Control of Movement.
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{97} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
From Uncertain Spikes to Prosthetic Control a powerpoint presentation w/ good overview of all that the Brown group has done | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{995} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
IEEE-936367 (pdf) Single-unit neural recording with active microelectrode arrays
____References____ Qing Bai and Wise, K.D. Single-unit neural recording with active microelectrode arrays Biomedical Engineering, IEEE Transactions on 48 8 911 -920 (2001) | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{996} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
IEEE-1052646 (pdf) An implantable multielectrode array with on-chip signal processing
____References____ Najafi, K. and Wise, K.D. An implantable multielectrode array with on-chip signal processing Solid-State Circuits, IEEE Journal of 21 6 1035 - 1044 (1986) | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{1021} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-4207598[0] Behavioral control of firing patterns of normal and abnormal neurons in chronic epileptic cortex.
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{1011} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
IEEE-4120642 (pdf) Mechanical Factors in the Design of Chronic Recording Intracortical Microelectrodes ____References____ Goldstein, Seth R. and Salcman, Michael Mechanical Factors in the Design of Chronic Recording Intracortical Microelectrodes Biomedical Engineering, IEEE Transactions on BME-20 4 260 -269 (1973) | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{940} |
ref: Fritsch-1870
tags: Fritsch Hitzig 1870 electrical stimulation
date: 01-03-2012 23:31 gmt
revision:2
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PMID-19457461[0] Electric excitability of the cerebrum (Uber die elektrische Erregbarkeit des Grosshirns).
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{288} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-11240278[0] Functions of mammalian spinal interneurons during movement
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{496} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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PMID-17554826[0] A fully integrated mixed-signal neural processor for implantable multichannel cortical recording.
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{902} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
bibtex:Olson-2005 Evidence of a mechanism of neural adaptation in the closed loop control of directions
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{240} |
ref: MolinaLuna-2007.03
tags: ICMS microstimulation cortical thin-film electrodes histology MEA
date: 01-03-2012 22:54 gmt
revision:2
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PMID-17178423[0] Cortical stimulation mapping using epidurally implanted thin-film microelectrode arrays.
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{739} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-2345003[0] Strength characterization of silicon microprobes in neurophysiological tissues.
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{941} |
ref: Penfield-1937
tags: Penfield 1937 motor cortex stimulation ICMS human neurosurgery electrodes
date: 01-03-2012 22:08 gmt
revision:3
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No PMID / bibtex penfield-1937. Somatic motor and sensory representation in the cerebral cortex of man as studied by electrical stimulation
The account of Bartholow (1874) is interesting to say the least and may be cited. His patient was a 30-year old-domestic. As an infant this unfortunate had chanced to fall into the fire, burning her scalp so badly that " hair was never reproduced." A piece of whale bone in the wig she was forced to wear irritated the scarred scalp and, by her statement, three months before she was admitted, an ulcer appeared. When she presented herself for relief, this had eroded the skull over a space 2 in. in diameter " where the pulsations of the brain are plainly seen." Although " rather feeble-minded " Bartholow observed that Mary returned replies to all questions and no sensory or motor loss could be made out in spite of the fact that brain substance apparently had been injured in the process of evacuation of pus from the infected area. The doctor believed, therefore, that fine insulated needles could be introduced without further damage. While the electrodes were in the right side Bartholow decided to try the effect of more current. ' Her countenance exhibited great distress and she began to cry. Very soon the left hand was extended as if in the act of taking hold of some object in front of her; the arm presently was agitated with clonic spasms ; her eyes became fixed with pupils widely dilated ; the lips were blue and she frothed at the mouth ; her breathing became stertorous, she lost conscious-ness and was violently convulsed on the left side. This convulsion lasted for five minutes and was succeeded by coma. She returned to consciousness in twenty minutes from the beginning of the attack and complained of some weakness and vertigo." Three days after this stimulation, following a series of right-sided seizures, the patient died.
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{841} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-20705858[0] Three-Dimensional, Flexible Nanoscale Field-Effect Transistors as Localized Bioprobes
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{972} |
ref: Bures-1968
tags: inferior colliculus stimulation classical conditioning plasticity hebb Bures
date: 01-03-2012 07:08 gmt
revision:5
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bibtex:Bures-1968 Plastic changes of unit activity based on reinforcing properties of extracellular stimulation of single neurons
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PMID-13367871[0] Conditioned reflexes established to electrical stimulation of cat cerebral cortex.
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{981} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-19762428[0] Auditory midbrain implant: a review.
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{366} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-17271187[0] Dynamic control of extracellular environment in in vitro neural recording systems.
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{585} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
LMS-based adaptive decorrelator, xn is the noise, xs is the signal, len is the length of the signal, delay is the delay beyond which the autocorrelation function of the signal is zero but the acf of the noise is non-zero. The filter is very simple, and should be easy to implement in a DSP. function [y,e,h] = lms_test(xn, xs, len, delay) h = zeros(len, 1); x = xn + xs; for k = 1:length(x)-len-delay y(k) = x(k+delay:k+len-1+delay) * h ; e(k) = x(k) - y(k); h = h + 0.0004 * e(k) * x(k+delay:k+len-1+delay)'; endIt works well if the noise source is predictable & stable: (black = sinusoidal noise, red = output, green = error in output) Now, what if the amplitude of the corrupting sinusoid changes (e.g. due to varying electrode properties during movement), and the changes per cycle are larger than the amplitude of the signal? The signal will be swamped! The solution to this is to adapt the decorrelating filter slowly, by adding an extra (multiplicative, nonlinear) gain term to track the error in terms of the absolute values of the signals (another nonlinearity). So, if the input signal is on average larger than the output, the gain goes up and vice-versa. See the code. function [y,e,h,g] = lms_test(xn, xs, len, delay) h = zeros(len, 1); x = xn + xs; gain = 1; e = zeros(size(x)); e2 = zeros(size(x)); for k = 1:length(x)-len-delay y(k) = x(k+delay:k+len-1+delay) * h; e(k) = (x(k) - y(k)); h = h + 0.0002 * e(k) * x(k+delay:k+len-1+delay)'; % slow adaptation. y2(k) = y(k) * gain; e2(k) = abs(x(k)) - abs(y2(k)); gain = gain + 1 * e2(k) ; gain = abs(gain); if (gain > 3) gain = 3; end g(k) = gain; end If, like me, you are interested in only the abstract features of the signal, and not an accurate reconstruction of the waveform, then the gain signal (g above) reflects the signal in question (once the predictive filter has adapted). In my experiments with a length 16 filter delayed 16 samples, extracting the gain signal and filtering out out-of-band information yielded about +45db improvement in SNR. This was with a signal 1/100th the size of the disturbing amplitude-modulated noise. This is about twice as good as the human ear/auditory system in my tests.
It doesn't look like much, but it is just perfect for EMG signals corrupted by time-varying 60hz noise. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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PMID-16859758 Brain-machine interfaces: past, present and future.
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PMID-4966614 Relation of pyramidal tract activity to force exerted during voluntary movement.
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IEEE-01258173 (pdf) Wireless implantable microsystems: high-density electronic interfaces to the nervous system - January 2004.
____References____ WISE, K.D. and ANDERSON, D.J. and HETKE, J.F. and KIPKE, D.R. and NAJAFI, K. Wireless implantable microsystems: high-density electronic interfaces to the nervous system Proceedings of the IEEE 92 1 76 - 97 (2004) | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{928} |
ref: Kennedy-1989.09
tags: Kennedy neurotrophic electrode recording fabrication 1989 electrophysiology
date: 01-03-2012 03:21 gmt
revision:2
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PMID-2796391[0] The cone electrode: a long-term electrode that records from neurites grown onto its recording surface.
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{130} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
http://www.neuroanatomy.wisc.edu/virtualbrain/BrainStem/06Olive.html
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PMID-19668698[0] A low-cost multielectrode system for data acquisition enabling real-time closed-loop processing with rapid recovery from stimulation artifacts
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{788} |
ref: -0
tags: reinforcement learning basis function policy specialization
date: 01-03-2012 02:37 gmt
revision:1
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{760} |
ref: -0
tags: LDA myopen linear discriminant analysis classification
date: 01-03-2012 02:36 gmt
revision:2
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How does LDA (Linear discriminant analysis) work? It works by projecting data points onto a series of planes, one per class of output, and then deciding based which projection plane is the largest. Below, to the left is a top-view of this projection with 9 different classes of 2D data each in a different color. Right is a size 3D view of the projection - note the surfaces seem to form a parabola. Here is the matlab code that computes the LDA (from myopen's ceven % TrainData and TrainClass are inputs, column major here. % (observations on columns) N = size(TrainData,1); Ptrain = size(TrainData,2); Ptest = size(TestData,2); % add a bit of interpolating noise to the data. sc = std(TrainData(:)); TrainData = TrainData + sc./1000.*randn(size(TrainData)); K = max(TrainClass); % number of classes. %%-- Compute the means and the pooled covariance matrix --%% C = zeros(N,N); for l = 1:K; idx = find(TrainClass==l); % measure the mean per class Mi(:,l) = mean(TrainData(:,idx)')'; % sum all covariance matrices per class C = C + cov((TrainData(:,idx)-Mi(:,l)*ones(1,length(idx)))'); end C = C./K; % turn sum into average covariance matrix Pphi = 1/K; Cinv = inv(C); %%-- Compute the LDA weights --%% for i = 1:K Wg(:,i) = Cinv*Mi(:,i); % this is the slope of the plane Cg(:,i) = -1/2*Mi(:,i)'*Cinv*Mi(:,i) + log(Pphi)'; % and this, the origin-intersect. end %%-- Compute the decision functions --%% Atr = TrainData'*Wg + ones(Ptrain,1)*Cg; % see - just a simple linear function! Ate = TestData'*Wg + ones(Ptest,1)*Cg; errtr = 0; AAtr = compet(Atr'); % this compet function returns a sparse matrix with a 1 % in the position of the largest element per row. % convert to indices with vec2ind, below. TrainPredict = vec2ind(AAtr); errtr = errtr + sum(sum(abs(AAtr-ind2vec(TrainClass))))/2; netr = errtr/Ptrain; PeTrain = 1-netr; | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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PMID-16543459[0] Reward Timing in the Primary Visual Cortex
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PMID-9307146[0] Systematic changes in directional tuning of motor cortex cell activity with hand location in the workspace during generation of static isometric forces in constant spatial directions.
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Reinforcement learning in the cortex (a web scour/crawl):
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PMID-6253605[0] Functional classes of primate corticomotoneuronal cells and their relation to active force
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IEEE-1419566 (pdf) A Portable Wireless DSP System for a Brain Machine Interface
____References____ Darmanjian, S. and Morrison, S. and Dang, B. and Gugel, K. and Principe, J. Neural Engineering, 2005. Conference Proceedings. 2nd International IEEE EMBS Conference on 112 -115 (2005) | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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PMID-15132510[0] A fully Integrated Neural Recording Amplifier with DC Input Stabilization
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{744} |
ref: Merletti-2009.02
tags: surface EMG multielectrode recording technology italy
date: 01-03-2012 01:07 gmt
revision:2
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PMID-19042063[0] Technology and instrumentation for detection and conditioning of the surface electromyographic signal: state of the art
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PMID-11491[0] Afferent input to movement-related precentral neurones in conscious monkeys.
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{665} |
ref: Cho-2007.03
tags: SOM self organizing maps Prinicpe neural signal reconstruction recording compression
date: 01-03-2012 00:59 gmt
revision:2
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PMID-17234384[0] Self-organizing maps with dynamic learning for signal reconstruction.
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PMID-19255459[0] A fully implantable 96-channel neural data acquisition system.
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PMID-6492861[0] A simple method for the construction of electrode arrays.
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IEEE-4463150 (pdf) A neural signal processor for an implantable multi-channel cortical recording microsystem
____References____ Sodagar, A.M. and Wise, K.D. and Najafi, K. Engineering in Medicine and Biology Society, 2006. EMBS '06. 28th Annual International Conference of the IEEE 5900 -5903 (2006) | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{1001} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
IEEE-5335132 (pdf) Low-cost wireless neural recording system and software
____References____ Gregory, J.A. and Borna, A. and Roy, S. and Xiaoqin Wang and Lewandowski, B. and Schmidt, M. and Najafi, K. Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE 3833 -3836 (2009) | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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PMID-21240274[0] A wireless multi-channel neural amplifier for freely moving animals.
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{1002} |
ref: Fan-2011.01
tags: TBSI wireless recordings system FM modulation multiplexing poland
date: 01-03-2012 00:55 gmt
revision:5
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PMID-21765934[0] A wireless multi-channel recording system for freely behaving mice and rats.
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PMID-15651568[0] A compact large voltage-compliance high output-impedance programmable current source for implantable microstimulators.
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{998} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
The Coming War on General Computation "M.P.s and Congressmen and so on are elected to represent districts and people, not disciplines and issues. We don't have a Member of Parliament for biochemistry, and we don't have a Senator from the great state of urban planning, and we don't have an M.E.P. from child welfare. " | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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IEEE-717081 (pdf) An Implantable Multichannel Digital neural recording system for a micromachined sieve electrode
____References____ Akin, T. and Najafi, K. and Bradley, R.M. Solid-State Sensors and Actuators, 1995 and Eurosensors IX.. Transducers '95. The 8th International Conference on 1 51 -54 (1995) | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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PMID-21976021[0] Active tactile exploration using a brain-machine-brain interface.
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{974} |
ref: Fitzsimmons-2007.05
tags: Fitzsimmons nicolelis stimluation ICMS owl monkeys
date: 01-01-2012 00:12 gmt
revision:2
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PMID-17522304[0] Primate reaching cued by multichannel spatiotemporal cortical microstimulation.
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{5} |
ref: bookmark-0
tags: machine_learning research_blog parallel_computing bayes active_learning information_theory reinforcement_learning
date: 12-31-2011 19:30 gmt
revision:3
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hunch.net interesting posts:
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PMID-17187065[0] Separate neural substrates for skill learning and performance in the ventral and dorsal striatum.
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PMID-14757341[1] A low power multichannel analog front end for portable neural signal recordings.
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PMID-14090522[0] The Brains record of auditory and visual experience -- A final summary and discussion
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PMID-4598035[0] Operant conditioning of single-unit response patterns in visual cortex.
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{60} |
ref: Douglas-1991.01
tags: functional microcircuit cat visual cortex microstimulation
date: 12-29-2011 05:12 gmt
revision:3
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PMID-1666655[0] A functional microcircuit for cat visual cortex
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{964} |
ref: OLDS-1954.12
tags: Olds Milner operant conditioning electrical reinforcement wireheading BMI
date: 12-29-2011 05:09 gmt
revision:5
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PMID-13233369[0] Positive reinforcement produced by electrical stimulation of septal area and other regions of rat brain.
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PMID-5941514[0] Feeding induced in cats by electrical stimulation of the brain stem.
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{834} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
IEEE-4464125 (pdf) Stimulus-Artifact Elimination in a Multi-Electrode System
Brown EA, Ross JD, Blum RA, Yoonkey N, Wheeler BC, and DeWeerth SP (2008) Stimulus-Artifact Elimination in a Multi-Electrode System. IEEE TRans. Biomed. Circuit Sys. 2. 10-21 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{968} |
ref: Bassett-2009.07
tags: Weinberger congnitive efficiency beta band neuroimagaing EEG task performance optimization network size effort
date: 12-28-2011 20:39 gmt
revision:1
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PMID-19564605[0] Cognitive fitness of cost-efficient brain functional networks.
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PMID-19923243 Complex Spatiotemporal Tuning in Human Upper-Limb Muscles
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PMID-20011034[0] A Wireless Brain-Machine Interface for Real-Time Speech Synthesis
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{832} |
ref: Jimbo-2003.02
tags: MEA microstimulation artifact supression
date: 12-17-2011 01:41 gmt
revision:2
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PMID-12665038[0] A system for MEA-based multisite stimulation.
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PMID-19386759[0] Wireless neural stimulation in freely behaving small animals.
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PMID-16102841[0] An autonomous implantable computer for neural recording and stimulation in unrestrained primates.
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PMID-17057705 Long-term motor cortex plasticity induced by an electronic neural implant.
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PMID-9658025[0] Predictive reward signal of dopamine neurons.
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{154} |
ref: OReilly-2006.02
tags: computational model prefrontal_cortex basal_ganglia
date: 12-07-2011 04:11 gmt
revision:1
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PMID-16378516[0] Making Working Memory Work: A Computational Model of Learning in the Prefrontal Cortex and Basal Ganglia found via: http://www.citeulike.org/tag/basal-ganglia ____References____
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PMID-15537672[0] On the Benefits of not Trying: Brain Activity and Connectivity Reflecting the Interactions of Explicit and Implicit Sequence Learning quote: ünder certain curcumstances, automatic learning may be attenuated by explicit memory processes" : expicit attemps to learn a difficult sequence (compared to a control) produces a failure in implicit learning, and this failure is caused by the supression of learning rather than the expression. There is a deleterious effect of explicit search on implicit learning.
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{199} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-16928796[0] Fast modulation of prefrontal cortex activity by basal forebrain noncholinergic neuronal ensembles in the author's own words:
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{300} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Motor learning by field approximation.
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{323} |
ref: Loewenstein-2006.1
tags: reinforcement learning operant conditioning neural networks theory
date: 12-07-2011 03:36 gmt
revision:4
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PMID-17008410[0] Operant matching is a generic outcome of synaptic plasticity based on the covariance between reward and neural activity
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http://delsys.com/KnowledgeCenter/FAQ_EMGSensor.html
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PMID-15022843[0] A simulation study of information transmission by multi-unit microelectrode recordings key idea:
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{723} |
ref: notes-0
tags: data effectiveness Norvig google statistics machine learning
date: 12-06-2011 07:15 gmt
revision:1
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The unreasonable effectiveness of data.
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PMID-6772272 Operant control of precentral neurons: bilateral single unit conditioning.
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PMID-6457106 Processing visual feedback information for movement control.
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PMID-10681435 Cortical correlates of learning in monkey adapting to a new dynamical environment. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{896} |
ref: Friston-2002.1
tags: neuroscience philosophy feedback top-down sensory integration inference
date: 10-25-2011 23:24 gmt
revision:0
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PMID-12450490 Functional integration and inference in the brain
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{890} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
I'm an avid open-water swimmer, and other than the quarry and beach, I spend many fridays hoping the water in Falls lake is not too choppy. If it's glassy and smooth (and even sometimes when it's not), I can fall into the hypnotic 4/4 chug of stroke-stroke-stroke-breathe, stroke-str ... not hard, since the brown water is featureless, and the above-water scenery doesn't change much either. Several years ago I was out on Falls lake doing my thing, comfortably clear in the middle of the lake, heading back to the beach. In my unawareness I failed to notice that a thunderstorm had grown in the hot summer afternoon. Normally I'm rather debonaire about these things, but have been in places just before they were struck by lightning, and this felt a little like that. So, SOL Tim starts considering the rather limited options (god) (hold breath for as long as possible) (are they the same?). Just then, some Mexican guy on a kayak comes paddling out of ... nowhere ... and asks me if I need help. I bearhug the back of his boat and we get back to shore before the storm breaks. .... Another friday, another season and I set off with a friend clear across Falls lake, which is far, like 3mi round trip. I chat with a Mexican dude before we launch the ships; i guess he seems a bit familiar, but I'm too nervous, eager, and worrying about the thoughts/abilities of my friend to think much. That swim goes fine, minus all the damned speadboats and the ravenous hunger that sets in afterward. Yesterday I had intended to swim at a pool, but some toddling kid chose to contaminate it, and so back to Falls Lake. It's choppy and hard to swim, and I don't make it as far as intended; again before launching, I meet a Mexican dude, and he asks me if I'm crossing the lake again. I tell him no, not enough time; the water envelops, and I'm back in the swim coma, gone to the point when I get back the sun is down and the moon has risen. Surprisingly, when I get back the Mexican guy and his family are still there, slowly cleaning up BBQ debris by the light of highbeams and one crappy flashlight. It's cool and peaceful on the lake, but they probably should have left half an hour ago; as I go to the restroom to change, I wave to the guy and realize two things simultaneously: (1) fuck, it's been the same guy, (2) he may have delayed departure, gracefully and surreptitiously, until I was back. Curiosity makes me want to ask if he had, to see if coincidence licked me again, but that's not right; I did't. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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I love this short story. It tastes like the complexity and frustrating richness of an examined life. It smells like the disparity between being able to understand things and being able to affect things in our incidental, stratified, limited world. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{885} |
ref: -0
tags: entropy life proteonomics transcription factors
date: 07-08-2011 22:42 gmt
revision:0
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Reduction in Structural Disorder and Functional Complexity in the Thermal Adaptation of Prokaryotes -- read the article. These are my disordered, mesothermophylic notes.
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so son why you looking so glum why you not making that symbol with your index finger and thumb? yea boy i know she couldn't kickit for real true true puddin, if fun were a sale then she got quite a steal the thing about the brain is with physical consequence get computed with aplomb, clarity and consonance when emotional matters get sucked into the fray only a fool will guess where the causality will stray it's almost fucking impossible to disentangle yourself which is why im yappin to you rather than to cough cough to myself dissatisfaction with her life is only slightly attached to angst in yer life but blaming yourself is not what she did, so don't do it. externalize events, it's a common adult strategy makes you feel a lot better irrespective of causality titrating the blame like ah chemistry class it's like the assholes are those who don't look at their own ass speakin of which, point your telescope over there, no not the squirrel, check the thing that fills out the chair now amusements can be had, amusements are given the butcher is calling, high time to make a killin you don't need to go to walking the Walden like Thoreau to pick up the coinage that self questioning will throw those who fail this will be a needle-nosed stasis while you me and charley will be making a praxis alright my brother time to show that squirrel who's bonafide self-bootstrapping is best done while physically occupied. just having some fun :-) | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Remembered fragment of a dream, letter never sent. Probably it was ill-fated to ---. Eh. That didn't distract me from having a batshit insane dream last night, feat three army goons, myself, and the vivacious ---. The goons and I were soldiers in charge of some truck-mounted machine gun in a logged and dried-mud hillcountry - probably Serbia - but whenever we tried to get it ready, the part in question would instantly transform into crochet. When the ammunition roll was finally in the yarn gun, all the bullets would fall on the ground; look away and it would resume metallic reality. On cue to amplify our disorganization a officer sped in to harass us in a Honda S2000. Annoyed, I threw gravel at him; it transformed into a lamborghini, then a porsche, a tesla, a toyota. (I've seen a lot of fancy cars this past week). Given the frustrated Daliesque nature of the battlefield, we retreated, I as a restrained but irked soldier. Montage in, montage out, you enter to this scene as an bit-played angry estranged woman, pissed at my lack of caring / perceived neglect. Bitch complain threaten whine, I guilt but look outside and the vegetation is gorgeous, lush, the sky a mild hazy blue. I am a little thirsty. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{864} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Interesting ideas from __This Will Change Everything__
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{859} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Learning by Playing: Video Games in the Classroom
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{858} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Notes & responses to evolutionary psychologists John Toobey and Leda Cosmides' - authors of The Adapted Mind - essay in This Will change Everything
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{855} |
ref: -0
tags: sciences artificial Simon organizations economic rationality
date: 12-01-2010 07:33 gmt
revision:2
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These are notes from reading Herbert A. Simon’s The Sciences of the Artificial, third edition, 1996 (though most of the material seems from the 70s). They are half quoted / half paraphrased (as needed when the original phrasing was clunky). I’ve added a few of my own observations, and reordered the ideas from the book. “A large body of evidence shows that human choices are not consistent and transitive, as they would be if a utility function existed ... In general a large gain along one axis is required to compensate for a small loss along another.†HA Simon. Companies within a capitalist economy make almost negligible use of markets in their internal functioning†- HA Simon. Eg. they are internally command economies. (later, p 40...) We take the frequent movability and indefiniteness of organizational boundaries as evidence that there is often a near balance between the advantages of markets and organizationsâ€
That said: organizations are not highly centralized structures in which all the important decisions are made at the center; this would exceed the limits of procedural rationality and lose many of the advantages attainable from the use of hierarchical authority. Business organizations, like markets, are vast distributed computers whose decision processes are substantially decentralized. In fact, the work of the head of a corporation is a market-like activity: allocating capital to promising or desirable projects. In organizations, uncertainty is often a good reason to shift from markets to hierarchies in making decisions. If two different arms of a corporation - production and marketing - make different decisions on the uncertain number of units to be sold next year, there will be a problem. It is better for the management to share assumptions. “Left to the market, this kind of uncertainty leads directly to the dilemmas of rationality that we described earlier in terms of game theory and rational expectations†I retain vivid memories of the astonishment and disbelief expressed by the architecture students to whom I taught urban land economics many years ago when I pointed to medieval cities as marveluosly patterned systems that had mostly just ‘grown’ in response to myriads of individual human decisions. To my students a pattern implied a planner in whose mind it had been conceived and whose hand it had been implemented. The idea that a city could acquire its patter as naturally as a snowflake was foreign to them ... they reacted to it as many christian fundamentalists responded to Darwin: no design without a Designer! Markets appear to conserve information and calculation by assigning decisions to actors who can make them on the basis of information that is available to them locally. von Hayek: “The most significant fact about this system is the economy of knowledge with which it operates, o how little the individual participants need to know in order to make the right actionâ€. To maintain actual Pareto optimality in the markets would require information and computational requirements that are exceedingly burdensome and unrealistic (from The New Palgrave: A dictionary of Economics) Nelson and winter observe that in economic evolution, in contract to biological evolution, sucessful algorithms (business practices) may be borrowed from one firm to the other. The hypothesized system is Lamarkian, because any new idea can be incorporated in opearting procedures as soon as its success is observed" . Also, it's good as corporations don't have secual reproduction / crossover. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{848} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
http://www.xbdev.net/directx3dx/specialX/Fur/index.php -- for future reference. Simple algorithm that seems to work quite well. Can be done almost entirely in vertex shader... | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{846} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Shuffle lines read in from stdin. I keep this script in /usr/local/bin on my systems, mostly for doing things like ls | shuffle > pls.txt && mplayer -playlist pls.txt #!/usr/bin/perl -w use List::Util 'shuffle'; while (<STDIN>) { push(@lines, $_); } @reordered = shuffle(@lines); foreach (@reordered) { print $_; } | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{839} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
(I'm posting this here as it's easier than putting a image & text in subversion) I'm building a wireless headstage for neural recording. Hence, it has sensitive, high-gain amplifiers (RHA2116) pretty close to a wireless transmitter + serial lines. The transmitter operates intermittently to save power, only sending samples from one continuous channel + threshold crossings for all the other channels. 27 byte-wide samples + channel identifier + 4 bytes threshold crossing are sent in one radio packet; as the radio takes some 130us to start up the PLL, 8 of these packets are chunked together into one frame; one frame is transmitted every 144hz (actually, 1e6/(32*27*8)Hz. At the conclusion of each frame, the continuous channel to be transmitted is incremented. It seems that radio transmission is interfering with the input amplfifiers, as the beginning samples from a frame are corrupted - this is when the previous frame is going out over the air. It could also be noise from the SPI lines, which run under and close to the amplifiers. This may also not be a problem in vivo - it could only be an issue when the input to the amplifiers are floating. Above, a plot of the raw data coming off the headstage radio. Red trace indicates the channel currently being transmitted; blue are the samples. Note that some chanels do not have the artifact - I presume this is because their input is grounded. This will be very tricky to debug, as if we turn off the radio, we'll get no data. Checking if it is a SPI problem is possible by writing the bus at a specified time. Tested with radio PA disabled, it is definitely the SPI bus - routing problem! Stupid. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{838} |
ref: -0
tags: meta learning Artificial intelligence competent evolutionary programming Moshe Looks MOSES
date: 08-07-2010 16:30 gmt
revision:6
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{815} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Jacques Pitrat seems to have many of the same ideas that I've had (only better, and he's implemented them!)-- A Step toward and Artificial Scientist
Artificial beings - his book. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{837} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Hutter's Theorem: for all problems asymptotically large enough, there exists one algorithm that is within a factor of 5 as fast as the fastest algorithm for a particular problem. http://www.hutter1.net/ai/pfastprg.htm | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{836} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{826} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Studies in astronomical time series analysis. II - Statistical aspects of spectral analysis of unevenly spaced data Scargle, J. D.
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{825} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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{821} |
ref: work-0
tags: differential evolution function optimization
date: 07-09-2010 14:46 gmt
revision:3
[2] [1] [0] [head]
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Differential evolution (DE) is an optimization method, somewhat like Neidler-Mead or simulated annealing (SA). Much like genetic algorithms, it utilizes a population of solutions and selection to explore and optimize the objective function. However, it instead of perturbing vectors randomly or greedily descending the objective function gradient, it uses the difference between individual population vectors to update hypothetical solutions. See below for an illustration. At my rather cursory reading, this serves to adapt the distribution of hypothetical solutions (or population of solutions, to use the evolutionary term) to the structure of the underlying function to be optimized. Judging from images/821_1.pdf Price and Storn (the inventors), DE works in situations where simulated annealing (which I am using presently, in the robot vision system) fails, and is applicable to higher-dimensional problems than simplex methods or SA. The paper tests DE on 100 dimensional problems, and it is able to solve these with on the order of 50k function evaluations. Furthermore, they show that it finds function extrema quicker than stochastic differential equations (SDE, alas from 85) which uses the gradient of the function to be optimized. I'm surprised that this method slipped under my radar for so long - why hasn't anyone mentioned this? Is it because it has no proofs of convergence? has it more recently been superseded? (the paper is from 1997). Yet, I'm pleased because it means that there are also many other algorithms equally clever and novel (and simple?), out their in the literature or waiting to be discovered. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{818} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Say you have a program, called from a perl script, that may run for a long time. Get at the program's output as it appears? Simple - open a pipe to the programs STDOUT. See http://docstore.mik.ua/orelly/perl/prog3/ch16_03.htm Below is an example - I wanted to see the output of programs run, for convenience, from a perl script (didn't want to have to remember - or get wrong - all the command line arguments for each). #!/usr/bin/perl $numArgs = $#ARGV + 1; if($numArgs == 1){ if($ARGV[0] eq "table"){ open STATUS, "sudo ./video 0xc1e9 15 4600 4601 0 |"; while(<STATUS>){ print ; } close STATUS ; }elsif($ARGV[0] eq "arm"){ open STATUS, "sudo ./video 0x1ff6 60 4597 4594 4592 |"; while(<STATUS>){ print ; } close STATUS ; }else{ print "$ARGV[0] not understood - say arm or table!\n"; } } | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{817} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
My letter to a friend regarding images/817_1.pdf The free-energy principle: a unified brain theory? PMID-20068583 -- like all critics, i feel the world will benefit from my criticism ;-) Hey , I did read that paper on the plane, and wrote down some comments, but haven't had a chance to actually send them until now. err..anyway.. might as well send them since I did bother writing stuff down: I thought the paper was interesting, but rather specious, especially the way the author makes 'surprise' something to be minimized. This is blatantly false! Humans and other mammals (at least) like being surprised (in the normal meaning of the word). He says things like: "This is where free energy comes in: free energy is an upper bound on surprise, which means that if agents minimize free energy, they implicity minimize surprise -- a huge logical jump, and not one that I'm willing to accept. I feel like this author is trying to capitalize on some recent developments, like variational bayes and ensemble learning, without fully understanding them or having the mathematical chops (like Hayen) to flesh it out. So far as I understand, large theories (as this proposes to be) are useful in that they permit derivation of particular update equations; Variational Bayes for example takes the Kullbeck-Leibler divergence & a factorization of the posterior to create EM update equations. So, even if the free energy idea is valid, the author uses it at such a level to make no useful, mathy predictions. One area where I agree with him is that the nervous system create a model of the internal world, for the purpose of prediction. Yes, maybe this allows 'surprise' to be minimized. But animals minimize surprise not because of free energy, but rather for the much more quotidian reason that surprise can be dangerous. Finally, i wholly reject the idea that value and surprise can be equated or even similar. They seem orthogonal to me! Value is assigned to things that help an animal survive and multiply, surprise is things it's nervous system does not expect. All these things make sense when cast against the theories of evolurion and selection. Perhaps, perhaps selection is a consequence of decreasing free energy - this intuitively and somewhat amorphously/mystically makes sense (the aggregate consequence of life on earth is somehow order, harmony and other 'goodstuff' (but this is an anthropocentric view)) - but if so the author should be able to make more coherent / mathematical prediction of observed phenomena. Eg. why animals locally violate the second law of thermodynamics. Despite my critique, thanks for sending the article, made me think. Maybe you don't want to read it now and I saved you some time ;-) | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{813} |
ref: work-0
tags: kicadocaml zbuffer comparison picture screenshot
date: 03-03-2010 16:38 gmt
revision:4
[3] [2] [1] [0] [head]
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Simple illustration of Kicadocaml with Z buffering enabled: and disabled: I normally use it with Z buffering enabled, but turn it off if, say, I want to clearly see all the track intersections, especially co-linear tracks or zero length tracks. (Probably I should write something to merge and remove these automatically.) Note that in either case, tracks and modules are rendered back-to-front, which effects a Z-sorting of sorts; it is the GPUs Z buffer that is enabled/disabled here. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{811} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
I recently had to replace a video card on my work computer - the Nvidia 8800 died; to replace it, I bought a ATI card, since they are cheaper and higher performance. Unfortunately, ATI/AMD drivers don't play with Linux as well as Nvidia's drivers do: the ATI linux drivers v 10.2 downloaded Feb 18 2010 are incompatible with Xorg v 7.5 included in Debian squeeze (testing). To fix this problem, I had to downgrade the package xserver-xorg and associated dependencies to that in Lenny. Edit /etc/apt/sources.list & add lenny (we have an apt-cacher in the lab, use your appropriate mirror): deb http://152.16.229.8/ac/ftp.debian.org/debian/ lenny main deb-src http://152.16.229.8/ac/ftp.debian.org/debian/ lenny main deb http://152.16.229.8/ac/ftp.debian.org/debian/ squeeze main deb-src http://152.16.229.8/ac/ftp.debian.org/debian/ squeeze main deb http://security.debian.org/ squeeze/updates main deb-src http://security.debian.org/ squeeze/updates main # debian multimedia deb http://crispy/ac/www.debian-multimedia.org squeeze main sudo apt-get update sudo apt-get install xserver-xorg/stable xserver-xorg-core/stable x11-xkb-utils/stable x11-common/stable xserver-xorg-video-vesa/stable xserver-xorg-input-mouse/stable xserver-xorg-input-kbd/stable Then download the installer from AMD's site, and use it to make --buildpkg Ubuntu/intrepid packages. You will need to install one dependency, dkms (something for controlling kernel modules?). This will result in the following Debian packages: fglrx-amdcccle_8.702-0ubuntu1_amd64.deb fglrx-kernel-source_8.702-0ubuntu1_amd64.deb fglrx-modaliases_8.702-0ubuntu1_amd64.deb libamdxvba1_8.702-0ubuntu1_amd64.deb xorg-driver-fglrx_8.702-0ubuntu1_amd64.deb xorg-driver-fglrx-dev_8.702-0ubuntu1_amd64.deb which you can then install, the kernel source one first. useful for pining the xorg to come from stable: http://jaqque.sbih.org/kplug/apt-pinning.html | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{807} |
ref: -0
tags: reynolds number microorganisms engineering math fluid mechanics
date: 01-25-2010 19:17 gmt
revision:0
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http://jilawww.colorado.edu/perkinsgroup/Purcell_life_at_low_reynolds_number.pdf - great! Never thought about this before.
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{804} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
I find this particular study of how things fail fascinating - http://foreignaffairs.us/solutions.php | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{796} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
An interesting field in ML is nonlinear dimensionality reduction - data may appear to be in a high-dimensional space, but mostly lies along a nonlinear lower-dimensional subspace or manifold. (Linear subspaces are easily discovered with PCA or SVD(*)). Dimensionality reduction projects high-dimensional data into a low-dimensional space with minimum information loss -> maximal reconstruction accuracy; nonlinear dim reduction does this (surprise!) using nonlinear mappings. These techniques set out to find the manifold(s):
(*) SVD maps into 'concept space', an interesting interpretation as per Leskovec's lecture presentation. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{795} |
ref: work-0
tags: machine learning reinforcement genetic algorithms
date: 10-26-2009 04:49 gmt
revision:1
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I just had dinner with Jesse, and the we had a good/productive discussion/brainstorm about algorithms, learning, and neurobio. Two things worth repeating, one simpler than the other: 1. Gradient descent / Newton-Rhapson like techniques should be tried with genetic algorithms. As of my current understanding, genetic algorithms perform an semi-directed search, randomly exploring the space of solutions with natural selection exerting a pressure to improve. What if you took the partial derivative of each of the organism's genes, and used that to direct mutation, rather than random selection of the mutated element? What if you looked before mating and crossover? Seems like this would speed up the algorithm greatly (though it might get it stuck in local minima, too). Not sure if this has been done before - if it has, edit this to indicate where! 2. Most supervised machine learning algorithms seem to rely on one single, externally applied objective function which they then attempt to optimize. (Rather this is what convex programming is. Unsupervised learning of course exists, like PCA, ICA, and other means of learning correlative structure) There are a great many ways to do optimization, but all are exactly that - optimization, search through a space for some set of weights / set of rules / decision tree that maximizes or minimizes an objective function. What Jesse and I have arrived at is that there is no real utility function in the world, (Corollary #1: life is not an optimization problem (**)) -- we generate these utility functions, just as we generate our own behavior. What would happen if an algorithm iteratively estimated, checked, cross-validated its utility function based on the small rewards actually found in the world / its synthetic environment? Would we get generative behavior greater than the complexity of the inputs? (Jesse and I also had an in-depth talk about information generation / destruction in non-linear systems.) Put another way, perhaps part of learning is to structure internal valuation / utility functions to set up reinforcement learning problems where the reinforcement signal comes according to satisfaction of sub-goals (= local utility functions). Or, the gradient signal comes by evaluating partial derivatives of actions wrt Creating these goals is natural but not always easy, which is why one reason (of very many!) sports are so great - the utility function is clean, external, and immutable. The recursive, introspective creation of valuation / utility functions is what drives a lot of my internal monologues, mixed with a hefty dose of taking partial derivatives (see {780}) based on models of the world. (Stated this way, they seem so similar that perhaps they are the same thing?) To my limited knowledge, there has been some work as of recent in the creation of sub-goals in reinforcement learning. One paper I read used a system to look for states that had a high ratio of ultimately rewarded paths to unrewarded paths, and selected these as subgoals (e.g. rewarded the agent when this state was reached.) I'm not talking about these sorts of sub-goals. In these systems, there is an ultimate goal that the researcher wants the agent to achieve, and it is the algorithm's (or s') task to make a policy for generating/selecting behavior. Rather, I'm interested in even more unstructured tasks - make a utility function, and a behavioral policy, based on small continuous (possibly irrelevant?) rewards in the environment. Why would I want to do this? The pet project I have in mind is a 'cognitive' PCB part placement / layout / routing algorithm to add to my pet project, kicadocaml, to finally get some people to use it (the attention economy :-) In the course of thinking about how to do this, I've realized that a substantial problem is simply determining what board layouts are good, and what are not. I have a rough aesthetic idea + some heuristics that I learned from my dad + some heuristics I've learned through practice of what is good layout and what is not - but, how to code these up? And what if these aren't the best rules, anyway? If i just code up the rules I've internalized as utility functions, then the board layout will be pretty much as I do it - boring! Well, I've stated my sub-goal in the form of a problem statement and some criteria to meet. Now, to go and search for a decent solution to it. (Have to keep this blog m8ta!) (Or, realistically, to go back and see if the problem statement is sensible). (**) Corollary #2 - There is no god. nod, Dawkins. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{794} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
http://weblog.raganwald.com/2007/06/which-theory-first-evidence.html
also from that site - http://weblog.raganwald.com/2007/05/not-so-big-software-application.html
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{789} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
I've been reading Computational Explorations in Cognitive Neuroscience, and decided to try the code that comes with / is associated with the book. This used to be called "PDP+", but was re-written, and is now called Emergent. It's a rather large program - links to Qt, GSL, Coin3D, Quarter, Open Dynamics Library, and others. The GUI itself seems obtuse and too heavy; it's not clear why they need to make this so customized / panneled / tabbed. Also, it depends on relatively recent versions of each of these libraries - which made the install on my Debian Lenny system a bit of a chore (kinda like windows). A really strange thing is that programs are stored in tree lists - woah - a natural folding editor built in! I've never seen a programming language that doesn't rely on simple text files. Not a bad idea, but still foreign to me. (But I guess programs are inherently hierarchal anyway.) Below, a screenshot of the whole program - note they use a Coin3D window to graph things / interact with the model. The colored boxes in each network layer indicate local activations, and they update as the network is trained. I don't mind this interface, but again it seems a bit too 'heavy' for things that are inherently 2D (like 2D network activations and the output plot). It's good for seeing hierarchies, though, like the network model. All in all looks like something that could be more easily accomplished with some python (or ocaml), where the language itself is used for customization, and not a GUI. With this approach, you spend more time learning about how networks work, and less time programming GUIs. On the other hand, if you use this program for teaching, the gui is essential for debugging your neural networks, or other people use it a lot, maybe then it is worth it ... In any case, the book is very good. I've learned about GeneRec, which uses different activation phases to compute local errors for the purposes of error-minimization, as well as the virtues of using both Hebbian and error-based learning (like GeneRec). Specifically, the authors show that error-based learning can be rather 'lazy', purely moving down the error gradient, whereas Hebbian learning can internalize some of the correlational structure of the input space. You can look at this internalization as 'weight constraint' which limits the space that error-based learning has to search. Cool idea! Inhibition also is a constraint - one which constrains the network to be sparse. To use his/their own words: ... given the explanation above about the network's poor generalization, it should be clear why both Hebbian learning and kWTA (k winner take all) inhibitory competition can improve generalization performance. At the most general level, they constitute additional biases that place important constraints on the learning and the development of representations. Mroe specifically, Hebbian learning constrains the weights to represent the correlational structure of the inputs to a given unit, producing systematic weight patterns (e.g. cleanly separated clusters of strong correlations). Inhibitory competition helps in two ways. First, it encourages individual units to specialize in representing a subset of items, thus parcelling up the task in a much cleaner and more systematic way than would occur in an otherwise unconstrained network. Second, inhibition greatly restricts the settling dynamics of the network, greatly constraining the number of states the network can settle into, and thus eliminating a large proportion of the attractors that can hijack generalization.." | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{790} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
http://www.carolinamtnclub.com/%5CHiking%5Cgoogle%5C511.htm awesome place! but watch out for the cows! | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{783} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-19435684[0] A 128-channel 6 mW wireless neural recording IC with spike feature extraction and UWB transmitter.
____References____
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{787} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
My theory on the Flynn effect - human intelligence IS increasing, and this is NOT stopping. Look at it from a ML perspective: there is more free time to get data, the data (and world) has almost unlimited complexity, the data is much higher quality and much easier to get (the vast internet & world!(travel)), there is (hopefully) more fuel to process that data (food!). Therefore, we are getting more complex, sophisticated, and intelligent. Also, the idea that less-intelligent people having more kids will somehow 'dilute' our genetic IQ is bullshit - intelligence is mostly a product of environment and education, and is tailored to the tasks we need to do; it is not (or only very weakly, except at the extremes) tied to the wetware. Besides, things are changing far too fast for genetics to follow. Regarding this social media, like facebook and others, you could posit that social intelligence is increasing, along similar arguments to above: social data is seemingly more prevalent, more available, and people spend more time examining it. Yet this feels to be a weaker argument, as people have always been socializing, talking, etc., and I'm not sure if any of these social media have really increased it. Irregardless, people enjoy it - that's the important part. My utopia for today :-) | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{774} |
ref: work-0
tags: functional programming compilation ocaml
date: 08-24-2009 14:33 gmt
revision:0
[head]
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The implementation of functional programming languages - book! | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{765} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
shows that I'd like to watch:
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{766} |
ref: life-0
tags: enfranchised mind blog population wealth future
date: 07-06-2009 21:43 gmt
revision:0
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http://enfranchisedmind.com/blog/posts/the-fermi-paradox/
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{764} |
ref: work-0
tags: ocaml mysql programming functional
date: 07-03-2009 19:16 gmt
revision:2
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Foe my work I store a lot of analyzed data in SQL databases. In one of these, I have stored the anatomical target that the data was recorded from - namely, STN or VIM thalamus. After updating the analysis programs, I needed to copy the anatomical target data over to the new SQL tables. Where perl may have been my previous go-to language for this task, I've had enuogh of its strange quiks, hence decided to try it in Ruby (worked, but was not so elegant, as I don't actually know Ruby!) and then Ocaml. ocaml #use "topfind" #require "mysql" (* this function takes a query and a function that converts entries in a row to Ocaml tuples *) let read_table db query rowfunc = let r = Mysql.exec db query in let col = Mysql.column r in let rec loop = function | None -> [] | Some x -> rowfunc col x :: loop (Mysql.fetch r) in loop (Mysql.fetch r) ;; let _ = let db = Mysql.quick_connect ~host:"crispy" ~database:"turner" ~password:"" ~user:"" () in let nn = Mysql.not_null in (* this function builds a table of files (recording sessions) from a given target, then uses the mysql UPDATE command to propagate to the new SQL database. *) let propagate targ = let t = read_table db ("SELECT file, COUNT(file) FROM `xcor2` WHERE target='"^targ^"' GROUP BY file") (fun col row -> ( nn Mysql.str2ml (col ~key:"file" ~row), nn Mysql.int2ml (col ~key:"COUNT(file)" ~row) ) ) in List.iter (fun (fname,_) -> let query = "UPDATE `xcor3` SET `target`='"^targ^ "' WHERE STRCMP(`file`,'"^fname^"')=0" in print_endline query ; ignore( Mysql.exec db query ) ) t ; in propagate "STN" ; propagate "VIM" ; propagate "CTX" ; Mysql.disconnect db ;; Interacting with MySQL is quite easy with Ocaml - though the type system adds a certain overhead, it's not too bad. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{762} |
ref: work-0
tags: covariance matrix adaptation learning evolution continuous function normal gaussian statistics
date: 06-30-2009 15:07 gmt
revision:0
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http://www.lri.fr/~hansen/cmatutorial.pdf
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{758} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Ocaml has an interactive top level, but in order to make this useful (e.g. for inspecting the types of variables, trying out code before compiling it), you need to import libraries and modules. If you have ocamlfind on your system (I think this is the requirement..), do this with: #use "topfind";; at the ocaml prompt, then #require"package names" . e.g: tlh24@chimera:~/svn/m8ta/yushin$ ledit | ocaml Objective Caml version 3.10.2 # #use "topfind";; - : unit = () Findlib has been successfully loaded. Additional directives: #require "package";; to load a package #list;; to list the available packages #camlp4o;; to load camlp4 (standard syntax) #camlp4r;; to load camlp4 (revised syntax) #predicates "p,q,...";; to set these predicates Topfind.reset();; to force that packages will be reloaded #thread;; to enable threads - : unit = () # #require "bigarray,gsl";; /usr/lib/ocaml/3.10.2/bigarray.cma: loaded /usr/lib/ocaml/3.10.2/gsl: added to search path /usr/lib/ocaml/3.10.2/gsl/gsl.cma: loaded # #require "pcre,unix,str";; /usr/lib/ocaml/3.10.2/pcre: added to search path /usr/lib/ocaml/3.10.2/pcre/pcre.cma: loaded /usr/lib/ocaml/3.10.2/unix.cma: loaded /usr/lib/ocaml/3.10.2/str.cma: loaded # Pcre.pmatch ;; - : ?iflags:Pcre.irflag -> ?flags:Pcre.rflag list -> ?rex:Pcre.regexp -> ?pat:string -> ?pos:int -> ?callout:Pcre.callout -> string -> bool = <fun> # let m = Gsl_matrix.create 3 3;; val m : Gsl_matrix.matrix = <abstr> # m;; - : Gsl_matrix.matrix = <abstr> # m.{1,1};; - : float = 6.94305623882282e-310 # m.{0,0};; - : float = 6.94305568087725e-310 # m.{1,1} <- 1.0 ;; - : unit = () # m.{2,2} <- 2.0 ;; - : unit = () # let mstr = Marshal.to_string m [] ;; Nice! | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{757} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
My friend Joey recently showed me the trailer to "The Road", and I banefully observed that it was "yet another disaster film". This made me wonder if the number of disaster films is increasing with time - a question that was easily answered with the help of perl, matlab, and Wikipedia's list of disaster films. First, I saved the page, then converted the list of dates contained therein into a matlab-formatted string with the following quick-n-dirty script: $source = $ARGV[0]; open(FH, "< $source"); @j = <FH>; #slurp the entire file into one string. print "dates = ["; $first = 1; foreach $l (@j){ while ($l =~ /\((\d{4})\)/gs ){ if(not $first){ print ","; } print $1 ; $first = 0; } } close FH; print "]; \n"; then plotted it in matlab: hist(dates, 20) %average over 5-year periods yielding: thereby validating my expectations that the number of disaster films has increased with time! (Note i did not say the percentage of total films - that might be constant :-) | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Gleaned from the Economist (June 6-12 2009) "
Italy imports 86% of it's electricity (!) | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{754} |
ref: Gilbert-2009.03
tags: human prediction estimation social situation neighbor advice affective forecasting
date: 06-10-2009 15:13 gmt
revision:2
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PMID-19299622[0] The Surprising Power of Neighborly Advice.
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{751} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
-- from the Lenthor Engineering Design guide. Wow they are indeed everywhere! | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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PMID-17873433[0] A single-chip signal processing and telemetry engine for an implantable 96-channel neural data acquisition system.
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{456} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
"One shot of [Lee Freidlander's], from 1969, traps an entire landscape of feeling: a boundless American sky, salted with high clouds, plus Freidlander's wife, Maria, with her slightly smiling face - inside the cab of a single truck, layering what we see through the side window with what is reflected in it. I know of long novels that tell you less " (not the shot above, but just the same - ) some more - http://www.nga.gov.au/SurfaceBeauty/IMAGES/LRG/Fiedlander-1981.954.jpg | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{734} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Rethinking the American Dream by David Kamp
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PMID-17946962[0] A reconfigurable neural signal processor (NSP) for brain machine interfaces.
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PMID-17946450[0] An Autonomous, broadband, multi-channel neural recording system for freely behaving primates
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For the great enemy of truth is very often not the lie—deliberate, contrived, and dishonest—but the myth— persistent, persuasive, and unrealistic. Too often we hold fast to the clichés of our forbears. We subject all facts to a prefabricated set of interpretations. We enjoy the comfort of opinion without the discomfort of thought. —John F. Kennedy | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{727} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
quote: For a given amount of 10kHz rejection, a 1ksps ADC (a) is equivalent to a 1Msps SAR ADC (b). Filtering determines the ADC's effective throughput, not the sampling rate (c). exactly! (click to see full res version. from an excellent article, "Managing high-voltage lithium-ion batteries in HEVs" by Michael Kultgen. more notes:
other stuff in that issue:
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{715} |
ref: Legenstein-2008.1
tags: Maass STDP reinforcement learning biofeedback Fetz synapse
date: 04-09-2009 17:13 gmt
revision:5
[4] [3] [2] [1] [0] [head]
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PMID-18846203[0] A Learning Theory for Reward-Modulated Spike-Timing-Dependent Plasticity with Application to Biofeedback
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{724} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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{712} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-19245368[0] The influence of learning on sleep slow oscillations and associated spindles and ripples in humans and rats
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{685} |
ref: BrashersKrug-1996.07
tags: motor learning sleep offline consolidation Bizzi Shadmehr
date: 03-24-2009 15:39 gmt
revision:1
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PMID-8717039[0] Consolidation in human motor memory.
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PMID-16794848[9] Bilateral basal ganglia activation associated with sensorimotor adaptation.
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Alopex: A Correlation-Based Learning Algorithm for Feed-Forward and Recurrent Neural Networks (1994)
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{686} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-17855611 Motor Force Field Learning Influences Visual Processing of Target Motion
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PMID-8922425 Primary Motor and Sensory Cortex Activation during Motor Performance and Motor Imagery: A Functional Magnetic Resonance Imaging Study.
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PMID-18482830[0] Reinforcement learning of motor skills with policy gradients
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{676} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-18578851 Overconfidence in an objective anticipatory motor task.
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{674} |
ref: notes-0
tags: Barto Hierarchal Reinforcement Learning
date: 02-17-2009 05:38 gmt
revision:1
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Recent Advancements in Hierarchal Reinforcement Learning
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{673} |
ref: Vasilaki-2009.02
tags: associative learning prefrontal cortex model hebbian
date: 02-17-2009 03:37 gmt
revision:2
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PMID-19153762 Learning flexible sensori-motor mappings in a complex network.
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In the process of installing compiz - which I decided I didn't like - I removed Xfce4's window manager, xfwm4, and was stuck with metacity. Metacity probably allows focus-follows-mouse, but this cannot be configured with Xfce's control panel, hence I had to figure out how to change it back. For this, I wrote a command to look for all files, opening each, and seeing if there are any lines that match "metacity". It's a brute force approach, but one that does not require much thinking or googling. find . -print | grep -v mnt | \ perl -e 'while($k = <STDIN>){open(FH,"< $k");while($j=<FH>){if($j=~/metacity/){print "found $k";}}close FH;}'This led me to discover ~/.cache/sessions/xfce4-session-loco:0 (the name of the computer is loco). I changed all references of 'metacity' to 'xfwm4', and got the proper window manager back. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{661} |
ref: -0
tags: computational geometry triangulation ocaml kicadocaml zone fill edge
date: 01-26-2009 01:47 gmt
revision:3
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I have been working hard to add zone support to kicadocaml since the implementation in kicad's PCBnew is somewhat borken (at least for my boards). It is not a very easy task! Roughly, the task is this: given a zone of copper pour, perhaps attached to the ground net, and a series of tracks, vias, and pads also on that layer of the PCB but not on the same net, form cutouts in the zone so that there is an even spacing between the tracks/vias and zone. Currently I'm attacking the problem using triangles (not polygons like the other PCB softwares). I chose triangles since I'm using OpenGL to display the PCB, and triangles are a very native mode of drawing in OpenGL. Points are added to the triangle mesh with an incremental algorithm, where the triangles are stored as a linked-mesh : each triangle has a pointer (index#) to the triangle off edge ab,bc,ca. This allows finding the containing triangle when inserting a point a matter of jumping between triangles; since many of the points to be inserted are close to eachother, this is a relatively efficient algorithm. Once the triangle containing a point to be inserted is found, the triangle is split into three, the pointers are updated appropriately, and each triangle is tested to see if flipping with it's pair would result in a net larger smallest interior angle between the two. (This is not the same as Delaunay's criteria, but it is simpler, and it produces equally beautiful pictures.) The problem is when two triangles are allowed to overlap or a gap is allowed - this makes the search algorithm die or get into a loop, and is a major major problem of the approach. In Guibas and Stolfi's paper, "Primitives for the manipulation of general subdivisions and the computation of Voronoi diagrams", they use an edge data structure, rather than a triangle data structure, which I suppose avoids this problem. I was lazy when starting this project, and chose the more obvious triangle-centric way of storing the data. The insertion of points is actually not so hard; the big problem is making sure the edges in the original list of polygons are represented in the list of edges in the triangle mesh. Otherwise, triangles will span edges, which will result in DRC violations (e.g.g copper too close to vias). My inefficient way of doing this is to calculate, for all triangles, their intersections with the polygon segments, then adding this to the mesh until all segments are represented in the list. This process, too, is prone to numerical instability. Perhaps the solution is to move back to an edge-centric data representation, so that certain edges can be 'pinned' or frozen, and hence they are guaranteed to be in the triangle mesh's edge list. I don't know; need to think about this more. Update: I got most of it working; at least the triangulation & making sure the edges are in the triangle mesh are working. Mostly there were issues with numerical precision with narrow / small triangles; I rewrote the inside triangle function to use the cross product, which helped (this seems like the simplest way, and it avoids divisions!): ocaml let insidetri a b c d = cross (sub b a) (sub d a) > 0.0 && cross (sub c b) (sub d b) > 0.0 && cross (sub a c) (sub d c) > 0.0 ;; as well as the segment-segment intersection algorithm: ocaml let intersect a b c d = (* see if two line segments intersect *) (* return the point of intersection too *) let ab = sub b a in (* a prime is the origin *) let bp = length ab in let xx = norm ab in let yy = (-1.) *. (snd xx) , (fst xx) in let project e = (dot (sub e a) xx) , (dot (sub e a) yy) in let cp = project c in let dp = project d in let cd = sub dp cp in let m = (fst cd) /. (snd cd) in let o = (fst cp) -. m *. (snd cp) in let e = add (scl ab (o /. bp)) a in (* cp and dp must span the x-axis *) if ((snd cp) <= 0. && (snd dp) >= 0.) || ((snd cp) >= 0. && (snd dp) <= 0.) then ( if o >= 0. && o <= bp then ( true, e ) else ( false, e ) ) else ( false, e ) ;; Everything was very sensitive to ">" vs. ">=" -- all must be correct. All triangles must be CCW, too, for the inside algorithm to work - this requires that points to be inserted close to a triangle edge must be snapped to that edge to avoid any possible CW triangles. (Determining if a triangle is CW or CCW is as simple as measuring the sign of the smallest cross product between two segments). I tried, for a day or so, to include a specialized function to insert points along a triangle's edge, but that turned out not to matter; the normal flipping routine works fine. I also tried inserting auxiliary points to try to break up very small triangles, but that really didn't affect the stability of the algorithm much. It is either correct, or it is not, and my large board was a good test suite. I have, however, seeded the triangularization with a grid of (up to) 20x20 points (this depends on the aspect ratio of the region to be filled - the points are equally spaced in x and y). This adds (max) 800 triangles, but it makes the algorithm more stable - fewer very narrow triangles - and we are working with sets of 10,000 triangles anyway for the large zones of copper. Some corrections remain to be done regarding removing triangles based on DRC violation and using the linked-mesh of triangles when calculating edge-triangle edge intersection, but that should be relatively minor. Now I have to figure out how to store it in Kicad's ".brd" file format. Kicad uses "Kbool" library for intersection polygons - much faster than my triangle methods (well, it's in C not ocaml) - and generates concave polygons not triangles. Would prefer to do this so that I don't have to re-implement gerber export. (Of course, look at how much I have re-implemented! This was originally a project just to learn ocaml - Well, gotta have some fun :-) | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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PMID-12371511[0] Dopamine: generalization and bonuses
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{652} |
ref: notes-0
tags: policy gradient reinforcement learning aibo walk optimization
date: 12-09-2008 17:46 gmt
revision:0
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Policy Gradient Reinforcement Learning for Fast Quadrupedal Locomotion
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We approximated sine and cosine, needed to vector the stepper motor phase currents, in fixed-point arithmetic first in C on linux - where the results could be plotted in matlab - before converting to MSP430 code. Since the trigonometric functions are repeating, we only need a polynomial approximation of sine from 0 to pi/2. The taylor series for sine is sin(x) = x - x^3/3! + x^5/5! - x^7/7! ...; a quick check in matlab showed that the first three terms are enough to get an accurate approximation in the domain of interest. The MSP430 does not have division, however, so we approximated 1/3! = 1/6 as (1/8 + 1/32 + 1/128) and 1/5! = 1/120 as 1/128; division by powers of two is possible with right bit-shift operations. We chose base 11 (5 bits whole, 11 bits fractional) representation to avoid overflow: if 2^11 -> 1, we need to represent (pi/2)^5 -> 9.5 ; ceil(log_2(9.5)) = 4 (plus one bit for safety). The C program below shows this test. #include <stdio.h> char qsin(short i){ //i goes from 0 pi/2 base 11 or... // 0 to 3217 unsigned int cube, fifth, result; cube = (i*i) >> 11; cube = (cube*i) >> 11; //max = 7937 fifth = (cube*i) >> 11; fifth = (fifth*i) >> 11; // max = 19585 //our approximation to sine based on taylor series: //original: sin(x) = x - x^3/3! + x^5/5! //sin(x) = x - x^3*(1/8+1/32+1/128) + x^5*(1/128) result = (unsigned int)i - ((cube >> 3) + (cube >> 5) + (cube >> 7)) + (fifth >> 7); //result is base 11. need it to be base 7. result = result >> 4; if(result > 127) result = 127; return (char)result; } //this is tricky, as it involves shifts, x-inversions, and y-inversions. //but it all makes sense if you plot out the respective functions. char isin(short i){ // i is base 2^11 //but we accept 0 to 2*pi or 12867 if(i >= 0 && i < 3217) return qsin(i); else if(i >= 3217 && i < 6434) return qsin(6434 - i); else if(i >= 6434 && i < 9651) return -1*qsin(i - 6434); else if(i >= 9651 && i < 12867) return -1*qsin(12867 - i); else return 0; } char icos(short i){ // i is base 2^11 //but we accept 0 to 2*pi or 12867 if(i >= 0 && i < 3217) return qsin(3217 - i); else if(i >= 3217 && i < 6434) return -1*qsin(i - 3217); else if(i >= 6434 && i < 9651) return -1*qsin(9651 - i); else if(i >= 9651 && i < 12867) return qsin(i - 9651); else return 0; } int main(void){ short i; for(i=0; i<12867; i++){ printf("%d\t%f\t%d\t%d\n", i, ((float)i)/2048.0, (int)(isin(i)), (int)(icos(i))); } return 0; } We compiled and ran this program on the command line: gcc integer_trig.c ./a.out > test.txt Then we imported the data into matlab and plotted (Actual double floating-point sine and cosine are plotted on the same axis as thin black and magenta lines, respectively) Later, we had to change the naive standard implementation of multiply to assembly to properly implement the fixed-point arithmetic - the MSP430's standard library did not implement the 16x16 multiply followed by shift correctly (it only keeps the bottom 16 bits). Note: this assembly function is for use with Code-Composer Studio, available from the Texas Instruments website. It seems that the IAR compiler uses different assembly syntax. ;******************************************************************************* .cdecls C,LIST,"msp430x54x.h" ; Include device header file ;------------------------------------------------------------------------------- .text ; Progam Start ;------------------------------------------------------------------------------- ;;.sect "mply_11" ;;.asmfunc "mply_11" .global mply_11 ;; this MUST BE PRECEDED BY TABS !!!!! mply_11: PUSH SR ; DINT ; turn off interrupts here. NOP ; required after DINT MOV.W R12, &MPY ; load the first operand. MOV.W R13, &OP2 ; load the second operand & start multiplication. MOV.W &RESLO, R12 ; low to R12 (this is the return value) MOV.W &RESHI, R13 ; high to R13 RRA.W R12 ; 1 RRA.W R12 ; 2 RRA.W R12 ; 3 RRA.W R12 ; 4 RRA.W R12 ; 5 RRA.W R12 ; 6 RRA.W R12 ; 7 RRA.W R12 ; 8 RRA.W R12 ; 9 RRA.W R12 ; 10 RRA.W R12 ; 11 RLA.W R13 ; 1 RLA.W R13 ; 2 RLA.W R13 ; 3 RLA.W R13 ; 4 RLA.W R13 ; 5 ;; r14 can be clobbered across a function call, according to the msp430 ABI MOV.W #0x001f, R14 AND.W R14, R12 ; mask off all but the bottom 5 bits from RESLO ADD.W R13, R12 ; add (logical OR) the results. R12 is the 11-bit fixed point result. POP.W SR ; RETA ; return from subroutine. .end Note the MSP430 does not have an opcode for multiple arithmetic shifts, nor does it have code for logical shifts - hence the need for repeated shifts and bitmasks! | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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hopefully these links don't move..
I like these 'paints', too. Did you show them to me a long time ago? I remember someone showing them to me in the past and I am wondering if you were the one. -- Ana | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Artificial Cerebellum for robot control:
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My comments on this blog post, preseved here for posterity: I agree with William’s first point, spectrum is ‘owned’ by everybody; the government’s only purpose is to regulate it so that it remains an effective communication medium. Like the bandwidth that it uses, the communication system is optimally owned by users, hence it is a bad idea to auction off segments of spectrum for exclusive use by corporations. Examine at what happened to the 2.4 GHz band, an area where water absorption is high and most households have a 1kw noise generator (microwave oven): EVERYONE USES IT because it is FREE and OPEN, no licenses required. Just look at all the innovation created for this band: 802.11, bluetooth, ZigBee, cordless phones, wireless remotes, and others. If 802.11 was in the 700-1GHz band someone or a company could easily make long-distance wireless repeaters & mesh-network nodes, sell them to consumers, and everyone could SIP for FREE without paying Verizon / ATT etc. This could set it up as a pyramid scheme, where to get on the network you simply have to buy a mesh node repeater, and with it became part of the ‘corporation’ which provided your wireless services. A certain part of the purcase & access price would, of course, need to go to pay for backbone connections, service, matenance and extending connection to remote areas, but this too can be solved and managed efficiently with something like 1 phone = 1 share. With coprotations, you either have redundancy (two networks w/ twice as many cell towers) or a monopoly; neither are economically efficient. A re-allocation of prime wireless spectrum back to the correct owners - the citizens - would spur American Innovation greatly and simultaneously cut communication costs. The technology is changing, and the policy should too! Anyway, i’m sick of paying $0.10 for 100 bytes of data (txt messages) when audio data costs ~1/500th that. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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PMID-18004384[0] A synaptic memory trace for cortical receptive field plasticity.
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PMID-9448252[0] The acquisition of skilled motor performance: Fast and slow experience-driven changes in primary motor cortex
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PMID-18701678[0] Reward facilitates tactile judgments and modulates hemodynamic responses in human primary somatosensory cortex.
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PMID-16563737[0] The computational neurobiology of learning and reward
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PMID-11257908[0] Multiple Reward Signals in the Brain
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PMID-10731222[0] Reward processing in primate orbitofrontal cortex and basal ganglia
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{620} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-17035544[0] Dopaminergic control of sleep-wake states ____References____ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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PMID-18614035[0] Neuronal ensemble bursting in the basal forebrain encodes salience irrespective of valence.
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PMID-17237780[0] Switching from automatic to controlled action by monkey medial frontal cortex.
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PMID-16271465[] The basal ganglia: Learning new tricks and loving it
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{609} |
ref: -0
tags: differential dynamic programming machine learning
date: 09-24-2008 23:39 gmt
revision:2
[1] [0] [head]
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PMID-11395017[0] Neuronal correlates of motor performance and motor learning in the primary motor cortex of monkeys adapting to an external force field
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PMID-17690132 Disrupted prediction-error signal in psychosis: evidence for an associative account of delusions.
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PMID-17234689[0] Volitional control of neural activity: implications for brain-computer interfaces (part of a symposium)
humm.. this paper came out a month ago, and despite the fact that he is much older and more experienced than i, we have arrived at the same conclusions by looking at the same set of data/papers. so: that's good, i guess. ____References____ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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PMID-11081826 EMG activation patterns during force production in precision grip. III. Synchronisation of single motor units.
Dr. hepp-Raymond himself seems to be a prolific researcher, judging from his pubmed search results. e.g.:
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Robots & others designed & made at the Tokyo Institute of Technology (from the Hirose / Fukushima Robotics lab)
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http://www.dana.org/news/cerebrum/detail.aspx?id=3066 -- great article, with a well thought out, delicate treatment of the ethical/moral/ legal issues created by the interaction between the biological roots of violence (or knowlege thereof) and legal / social systems. He posits that there must be a continuum between ratinoal free will and irrational, impulsive violent behavior, with people biased to both by genetics, development, traumatic head injury, and substance abuse (among others). | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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I needed to evaluate different fixed-point filters & implement them in a way which would more-or-less easily transfer to hand-coded blackfin assembly. Hence, I wrote a small program in C to test two likely alternatives: a 5th order elliptic filter, with 82db stopband rejection, or a 4th order elliptic, with 72 db stopband rejection. see {421} also, and this useful reference. (also at {584}) UPDATE: this filter is not stable/ suitable for the 1.15 signed fraction format of the blackfin processor. As in the reference, you must use a non-canonic form which puts the numerator before the denominator. I had a great deal of difficulty trying to determine why the output of the Direct Form II filter was giving crap results with poles/zeros designed for lowpass operation. The reason appears to be that the Direct FormII filter requires dynamic range > +-1 for the w's (first feedback section). The numerator / b coefficients for these highpass filters is usually [1 -2 1] - a highpass - which returns 0 when passed saturated data. See the signal flowchart below. The program for implementing these filters as cascaded biquad/ triquads follows. The method of generating the filter coefficients is in the comments. Note that the filter coefficients for the triquad exceed and absolute magnitude of 2, hence the triquad implementation has a fixed-point format of s.2.13 (one bit sign, 2 bits whole part, 13 bits fractional part). The biquad has s.1.14 format - one bit for the whole part. Also note that I incorporated a scale factor of x2 into the first stage, and x4 into the second stage, as the output of the ADC is only 12 bits and we can afford to expand it to the full range. The filter responses, as designed (in floating point). 5th order is on the left, 4th on the right. The filter output to white noise, in the time domain. 5th order has, in this impementation, a 'softer shoulder', which i do not think is appropriate for this application. The same output in fourier space, confirming the softer shoulder effect. this was actually kinda unespected .. I thought an extra pole/zero would help! I guess the triquad & lower res coefficient quantization is less efficient.. ? #include <stdio.h> // gcc -Wall filter_test.c -o filter_test //need to test fixed-point filtering in C (where it is easy) //before converting to hand-coded assembly. short w1_1[2]= {0,0}; short w1_2[3]= {0,0,0}; short w2_1[2]= {0, 0}; short w2_2[2]= {0, 0}; /* filter 1: 5th order. biquad then a triquad. [B1, A1] = ellip(5,0.2,84, 6/31.25); %84db = 14 bits. rb = roots(B1); ra = roots(A1); pa1 = poly(ra(1:2)); pa2 = poly(ra(3:5)); pb1 = poly(rb(1:2)); pb2 = poly(rb(3:5)); b1_1 = round(pb1*sqrt(B1(1))*2^15) a1_1 = round(pa1* 2^14)* -1 b1_2 = round(pb2*sqrt(B1(1))*2^15) a1_2 = round(pa2*2^13)*-1 % triquad. */ //biquad1: short b1_1[3] = {1199, 87, 1199}; short a1_1[2] = {24544 -14085}; //triquad1: short b1_2[4] = {1199, 2313, 2313, 1199}; short a1_2[3] = {18090, -14160, 3893}; /*filter 2: can be implemented by 2 biquads. [B3, A3] = ellip(4,0.5,72, 6/31.25); rb = roots(B3); ra = roots(A3); pa1 = poly(ra(1:2)); pa2 = poly(ra(3:4)); pb1 = poly(rb(1:2)); pb2 = poly(rb(3:4)); b2_1 = round(pb1*sqrt(B3(1))*2^15) a2_1 = round(pa1* 2^14)* -1 b2_2 = round(pb2*sqrt(B3(1))*2^16) %total gain = 8. a2_2 = round(pa2*2^14)*-1 */ //biquad2: short b2_1[3] = {2082, 914, 2082}; short a2_1[2] = {24338, -13537}; //biquad2 (2): short b2_2[3] = {4163, 6639, 4163}; short a2_2[2] = {24260, -9677}; int madd_sat(int acc, short a, short b){ //emulate the blackfin //signed-integer mode of operating. page 567 in the programming reference. int c; long long l, lo, hi; lo = (long long)(-2147483647); hi = (long long)(2147483647); c = (int)a * (int)b; l = (long long)acc + (long long)c; if(l < lo) l = lo; if(l > hi) l = hi; acc = (int)l; return acc; } //need to deal with samples one at a time, as they come in, from different channels //need to quantize the coeficients //need to utilize a biquad topology / filter structure. // (this is simple - just segregate the poles. order 5 filter req. biquad & triquad. short filter_biquad(short in, short* a1, short* b1, short* w1){ int acc; short out, w; //in varies from 0 to 0x0fff - ADC is straight binary. (0 to 4095). unsigned. acc = madd_sat(0, in, 16384); acc = madd_sat(acc, w1[0], a1[0]); acc = madd_sat(acc, w1[1], a1[1]); w = (short)(acc >> 14); //hopefully this does sign-extended shift. acc = madd_sat(0, w, b1[0]); acc = madd_sat(acc, w1[0], b1[1]); acc = madd_sat(acc, w1[1], b1[0]); //symmetry. out = (short)(acc >> 14); w1[1] = w1[0]; w1[0] = w; return out; } short filter_triquad(short in, short* a2, short* b2, short* w2){ int acc; short out, w; //this one is a bit different, as the coefficients are > 2 in the denom. // hence have to normalize by a different fraction. //multiply the numerator by 4 for a net gain of 8. acc = madd_sat(0 , in, 8192); acc = madd_sat(acc, w2[0], a2[0]); acc = madd_sat(acc, w2[1], a2[1]); acc = madd_sat(acc, w2[2], a2[2]); w = acc >> 13; acc = madd_sat(0 , w, b2[0]); acc = madd_sat(acc, w2[0], b2[1]); acc = madd_sat(acc, w2[1], b2[1]); acc = madd_sat(acc, w2[2], b2[0]); //symmetry. out = (short)(acc >> 13); w2[2] = w2[1]; w2[1] = w2[0]; w2[0] = w; return out; } int main( int argv, char* argc[]){ //read the samples from stdin. int in, out; while(scanf("%d", &in)){ //compare 5th and 4th order filters directly. in -= 2048; out = filter_biquad(in, a1_1, b1_1, w1_1); out = filter_triquad(out, a1_2, b1_2, w1_2); printf("%d ", out); out = filter_biquad(in, a2_1, b2_1, w2_1); out = filter_biquad(out, a2_2, b2_2, w2_2); printf("%d ", out); } return 0; } // gcc -Wall filter_test.c -o filter_test // cat filter_test_in.dat | ./filter_test > filter_test_out.dat Below, some matlab code to test the filtering. % make some noisy data. x = randn(2000, 1); x = x .* 1000; x = x + 2048; i = find(x >= 4096) x(i) = 4095; i = find(x < 0); x(i) = 0; x = round(x); fid = fopen('filter_test_in.dat', 'w'); for k = 1:length(x) fprintf(fid, '%d ', x(k)); end fprintf(fid, 'quit'); fclose(fid); Here is a blackfin assembly implementation of the filter, Note the filter weights (i0) and delays (i1, i2) need to be on two different cache/sram banks, or the processor will stall. Also note that , as per the second diagram above, the delays for biquad 1 output are synonymous to the delays for biquad 2 input, hence they are only represented once in memory. /* directform 1 biquad now, form II saturates 1.15 format. operate on the two samples in parallel (both in 1 32bit reg). r0 x(n) -- the input from the serial bus. r1 x(n-1) (yn-1) -- ping-pong the delayed registers. r2 x(n-2) (yn-2) -- do this so save read cycles. r3 y(n-1) (xn-1) r4 y(n-2) (xn-2) r5 b0 b1 -- (low high) r6 a0 a1 i0 reads the coeficients into the registers; it loops every 32 bytes (16 coef, 4 biquads) i1 reads the delays. it loops every 640 bytes = 10 delays * 4 bytes/delay * 16 stereo channels. only increments. i2 writes the delays, loops every 640 bytes. also only increments. if i1 and i2 are dereferenced in the same cycle, the processor will stall -- each of the 1k SRAM memory banks has only one port. format of delays in memory: [x1(n-1) , x1(n-2) , x2(n-1) aka y1(n-1) , x2(n-2) aka y1(n-2) , x3(n-1) aka y2(n-1) , x3(n-2) aka y2(n-2) , x4(n-1) aka y3(n-1) , x4(n-2) aka y3(n-2) , y4(n-1) , y4(n-2) ] --that's 10 delays, 4 bytes each. */ r5 = [i0++] || r1 = [i1++]; a0 = r0.l * r5.l , a1 = r0.h * r5.l || r6 = [i0++] || [i2++] = r0; a0 += r1.l * r5.h, a1 += r1.h * r5.h || r2 = [i1++] ; a0 += r2.l * r5.l, a1 += r2.h * r5.l || r3 = [i1++] ; a0 += r3.l * r6.l, a1 += r3.h * r6.l || r4 = [i1++] ; r0.l = (a0 += r4.l * r6.h), r0.h = (a1 += r4.h * r6.h) (s2rnd) || [i2++] = r1; r5 = [i0++] || [i2++] = r0; a0 = r0.l * r5.l, a1 += r0.h * r5.l || r6 = [i0++] || [i2++] = r3; a0 += r3.l * r5.h, a1 += r3.h * r5.h || r1 = [i1++]; a0 += r4.l * r5.l, a1 += r4.h * r5.l || r2 = [i1++]; a0 += r1.l * r6.l, a1 += r1.h * r6.l; r0.l = (a0 += r2.l * r6.h), r0.h = (a1 += r2.h * r6.h) (s2rnd); r5 = [i0++] || [i2++] = r0; a0 = r0.l * r5.l, a1 = r0.h * r5.l || r6 = [i0++] || [i2++] = r1; a0 += r1.l * r5.h, a1 += r1.h * r5.h || r3 = [i1++]; a0 += r2.l * r5.l, a1 += r2.h * r5.l || r4 = [i1++]; a0 += r3.l * r6.l, a1 += r3.h * r6.l; r0.l = (a0 += r4.l * r6.h), r0.h = (a1 += r4.h * r6.h) (s2rnd); r5 = [i0++] || [i2++] = r0; a0 = r0.l * r5.l, a1 += r0.h * r5.l || r6 = [i0++] || [i2++] = r3; a0 += r3.l * r5.h, a1 += r3.h * r5.h || r1 = [i1++]; a0 += r4.l * r5.l, a1 += r4.h * r5.l || r2 = [i1++]; a0 += r1.l * r6.l, a1 += r1.h * r6.l; r0.l = (a0 += r2.l * r6.h), r0.h = (a1 += r2.h * r6.h) (s2rnd); [i2++] = r0; //save the delays. [i2++] = r1; //normally this would be pipelined. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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images/584_1.pdf -- this is a highly useful paper, but is no longer available on the author's website. For the good of all, i post it here. These may also have utility:
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{582} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Bjork has a special place in my heart - and not only because of stuff like this: http://www.youtube.com/watch?v=jX9y6AA5oOo ;) When I was in college - not so far back as Post, but before Selmasongs - we used to play a lot of pool. Not so much that we didn't get any work done, but enough that we started getting good. Near the end of that year we filmed a bunch of games & made a music video set to Underworld's remix of "Human Behavior". I don't know what happened to the actual end product, but I do clearly recall my mom complaining about the repetitive beats while I was cutting the shots so the ball collisions would align with snare/bass hits. Sometime later that year I was blown away by the real deal, the "All is full of love" music video, projected on the side of the art museum at ~ 2am when the mind is labile... Bjork & her music pervaded that period for me. I've found that music can 'tag' periods of life for me, such that when I remember the music first then the events. This winter it was Interpol, last fall was Metric, spring 2007 was Arca (you *have* to hear them!). When me and my brother went to Portugal for a few weeks we found two Pixies mix tapes in the tiny car that my friend generously let us use. Hence, Frank Black soaked our ears while the incredible Portuguese sun soaked our skin. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{579} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
oldies but goodies:
Both are in Debian of course :) | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{502} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Outline: The goal is to use a nRF24L01 to make an asymmetrical, bidirectional link. The outgoing bandwidth should be maximized, ~1.5mbps, and the incoming bandwidth can be much smaller, ~17kbps, though on both channels we want guaranteed latency, < 4ms for the outgoing data, and < 10ms for the incoming data. Furthermore, the processor that is being used to run this, a blackfin BF532, does not seem to play well when both SPI DMA is enabled and most CPU time is being spent in SPORT ISR reading samples & processing them. Fortunately, the SPI port and SPORT can be run synchronously (provided the SPI port is clocked fast enough), allowing the processor to run one 'thread' e.g. no interrupts. It seem that with high-priority interrupts, the DMA engine is not able to service the SPI perfectly, and without DMA, data comes out of the SPI in drips and drabs, and cannot keep the radio's fifo full. Hence, must program a synchronous radio controller, where states are stored in variables and not in the program counter (PC register, saved upon interrupt, etc). As in other postings on the nRF24L01, the plan is to keep the transmit fifo full for most of the 4ms allowed by the free-running pll, then transition back into either standby-I mode, or send a status packet. The status packet is always acknowledged by the primary receiver with a command packet, and this allows both synchronization and incoming bandwidth. Therefore, there are 4 classes of transfers:
screenshot of the derived code working (yea, my USB logic analyzer only runs on windows..yeck): old versions: | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{577} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
I found this on my computer tucked away into a dusty corner. Such fascinating information should not be left hidden - | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{575} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
these guys use the blackfin, too: http://www.surveyor.com/ check out the board - very clean and neat! The robot itself - with tank treads and a radio - costs $465 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
I have, minus some notable periods, been cooking for myself and at times others for about eight years now. It began after going off meal plan in college, something that my mother was rather concerned about (she violently opposed it). She needn't worry, though; huger is a powerful motivator, one that won't disappear without proper administration. At first I ate purely because of need -- an approach that is utilitarian, probably quite healthy, but ultimately depressing. I still revert back to this mode, sometimes, but feel that it is very self-defeating - we can subvert the natural hierarchies of value by placing work above food, but ultimately the (sometimes) illogical legacy of our subconscious will come back to bite. For most of evolution, a well fed animal was a happy animal, and, us humans can only ignore this for so long. If you allow me to (continue to) make broad generalizations that I'm not qualified to make, some people's problems may be traced to trying to control their reward system logically. Within my limited experience, it does not work that way; reward is from the outside world. Like food. (A learning system that is self-rewarding can be unstable). So after about a year I began to trying to cook better, with the constraints that I had neither much money nor a car. Gradually, somehow, it got better! Most of this came by watching what others did, and some via experimentation. Both were rather slow, as the others in the equation were an odd mix of busy college students with a bias to the vegan and hippy, and my experimentation was very poorly informed. I knew roughly what was out there, but not how it could all fit together. With mimicry and fiddling, occasional good results were produced (and produced and produced until I got sick of that too), but progress was slow, because you never get better at anything unless you actually care about it. I cared about grades, and nobody was grading my food. (thankfully, my gpa would have suffered!) Then I moved to Brooklyn, a translocation which hindered progress more: there was a Sicilian pizza parlor on my way home. My understanding of the culinary arts did not increase, but... my cholesterol sure did! I also developed the quick and filling habit of buying a big chunk of Jarlsburg & some bread from a bakery on the way home. The problem was that I really enjoyed what I was doing at the time, and unlike school with its segmented workflow with definite ends, the work was open-ended and like a gas. It ate up all my eating time, leaving no time for cooking. Graduate school was (is!) a similar story, more interesting work to do and not enough time to do it. There were no longer excellent pizzerias on the way home, though there were plenty of accessible restaurants, and we did make use of this fact. When eating out, though, it is better if you leave with only a warm and amorphous recollection of the food. If you leave with a sharp recollection of the food, then either it was terrible, the conversation was dull, or you are well trained (you already know the last poses no problem for me). However, if you are eating with others - and you *cooked* the food, then the dinner table is reversed: flavor matters very much! This happened, for me, upon moving into a rambling, old, drafty southern house with several others (I can't quote exactly how many -- it varied, some good, some bad, all interesting.) I think my peak moment in old 708 Parker was when cooking for a group of Brazilians - portobello mushrooms, potatoes, pork with apples. Probably I think so fondly of it because I was mostly unable to ask them what they thought of it, and they were unable to tell me. That was also shortly after having read Pat Conroy's "Recipes from my life", a book that filled me with a love of the south and cooking food. This book was just lying around somewhere in the house; finding it was no surprise, the house was positively filled with junk. Despite the good times and fruitful finds, that house liked natural gas to the tune of $500/month in the winter, so we ditched it. The kitchen was kinda crummy anyway. Having enjoyed the taste of communal life, I secured a lease on an even bigger house and moved the crew over to it. At this time my dad's interest in cooking was also reaching new heights. Whenever I would go home, we were greeted with meals of increasing complexity and variety of ingredients. I liked it a lot, but to be honest I was beginning to get a taste for my own (mediocre but tuned to the target audience) cooking! My dad is an engineer, and the transfer of approach if not skill is not surprising in retrospect. Making a good meal can be very much an engineering problem, with the ingredients mixing together in generally learnable/predictable manner, and with an unusually simple objective criteria: it should taste good. My period in the great big house (mode of occupancy:7) will end soon, but no worries: I still need to eat, and so do my friends! | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{565} |
ref: Walker-2005.12
tags: algae transfection transformation protein synthesis bioreactor
date: 03-21-2008 17:22 gmt
revision:1
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Microalgae as bioreactors PMID-16136314
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{551} |
ref: notes-0
tags: DNA transfection yasuda experiment8
date: 03-17-2008 20:11 gmt
revision:2
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{546} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
http://www.sgvsarc.com/demo.htm
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{536} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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{545} |
ref: notes-0
tags: telecommunications FCC wireless regulation government
date: 02-26-2008 04:18 gmt
revision:2
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http://news.zdnet.com/2010-1035_22-6231729.html
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{539} |
ref: -0
tags: laser power concentration GFP mCherry calibration
date: 02-01-2008 19:22 gmt
revision:0
[head]
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above, a set of curves for determining fluorescent protein concentration (GFP & mCherry) from received photon count in a two-photon microscope. Unfortunately, these depend on efficiency & power of the entire setup, so the curve is non-transferable to other microscopes. one pass of mCherry @ 5x dilution did not seem the same as the others -- perhaps the reading light was left on? % given a series of files, % calculate a quadratic to convert intensity to concentration. % assumed formula: % green intensity = background + const*[GFP]*laserpower^2 % red intensity = background + const*[RFP]*laserpower^2 + % const2[GFP]*laserpower^2 close all cd('/var/ftp/tim_hanson/T002-0130_08/solutions'); basename = 'T002-gfp-100xdil-'; int_gfp100 = IntensReadfile('T002-gfp-100xdil-', 11, 2); int_gfp10 = IntensReadfile('T002-gfp-10xdil-', 8, 2); int_mcherry10 = IntensReadfile('T002-mcherry-10xdil-', 7, 2); int_mcherry5 = IntensReadfile('T002-mcherry-5xdil-', 7, 2); int_mcherry5_2 = IntensReadfile('T002-mcherry-5xdil2-', 7, 2); int_mcherry5_4 = IntensReadfile('T002-mcherry-5xdil4-', 6, 2); bg_green = (int_gfp100(1) + int_gfp10(1))/2; bg_red = (int_mcherry10(1) + int_mcherry5(1)... + int_mcherry5_2(1) + int_mcherry5_4(1))/4; powers = (0:0.1:1).^2; int_gfp_all = [int_gfp100-bg_green, (int_gfp10-bg_green)/10]; pow_gfp_all = [powers(1:11), powers(1:8)]; green_intensity_perpower = pow_gfp_all'\int_gfp_all' green_lab = ['green intensity = ' num2str(green_intensity_perpower) ' * power^2 + ' ... num2str(bg_green) ' (photons/10us) @ 8.7 ug/ml conc. gfp']; figure plot(sqrt(powers(1:11)), int_gfp100, 'o'); hold on plot(sqrt(powers(1:8)), (int_gfp10-bg_green)/10+bg_green, 'or'); plot(sqrt(pow_gfp_all), pow_gfp_all * green_intensity_perpower + bg_green, 'gx'); legend('100x dilution','10x dilution','parabolic fit'); title('intensity of gfp vs. laser power normalized to 100x dilution') xlabel(green_lab); int_mch_all = [(int_mcherry10-bg_red)/10, (int_mcherry5-bg_red)/20, ... (int_mcherry5_2-bg_red)/20, (int_mcherry5_4-bg_red)/20]; pow_mch_all = [powers(1:7), powers(1:7), powers(1:6), powers(1:7)]; red_intensity_perpower = pow_mch_all'\int_mch_all' red_lab = ['red intensity = ' num2str(red_intensity_perpower) ' * power^2 + ' ... num2str(bg_red) ' (photons/10us) @ 8.7 ug/ml conc. mcherry']; figure plot(sqrt(powers(1:7)), (int_mcherry10-bg_red)/10+bg_red, 'o'); hold on plot(sqrt(powers(1:7)), (int_mcherry5-bg_red)/20+bg_red, 'or'); plot(sqrt(powers(1:7)), (int_mcherry5_2-bg_red)/20+bg_red, 'ok'); plot(sqrt(powers(1:6)), (int_mcherry5_4-bg_red)/20+bg_red, 'om'); plot(sqrt(pow_mch_all), pow_mch_all * red_intensity_perpower + bg_red, 'gx'); legend('10x dilution','5x dilution','5x dilution(2)','5x dilution(4)','parabolic fit'); title('intensity of mcherry vs. laser power normalized to 100x dilution') xlabel(red_lab) | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{538} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{530} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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{531} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
http://www.uspto.gov/go/pac/doc/general/
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{388} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
-- | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{526} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
I'm posting my comments about http://flock.com/ here just in case they are removed from the actual site This is all very interesting. I just downloaded it, and flock seems to work well. I'm probably not going to use it unless there is some demonstrable technical superiority (e.g. leaks less memory than firefox), as the social sites just distract me from getting work done. Anyway, I have a question: how are you going to make money? How are you paying the developers? If you are not and it is all OSS, where is the source? It seems like the VC's are just throwing money away for the (hypothetical) good of the social-network crowd. Or, rather, you are indirectly funding the popularity of sites that flock makes it easy to get at. Are these sites (e.g. facebook) paying you? Wait -- flock allows you to look at content and not the ads. They are not paying you. Perhaps you are moving along the lines of Opera, and intending to get people addicted to flock to a degree that they demand it on their mobile devices. Mobile devices are closed (for now .. check google), hence you can make money licensing software to phone manufacturers. I imagine that you'll have to rewrite the Mozilla core to do this (unless phones become significantly more powerful - not likely, they are battery devices. ) Mozilla is (L)GPL - you'll have to release the source. To the best of my knowledge, with non-physical goods money can only be made from gradients in knowledge (pun.. intended), therefore you will have to keep the source closed. If this is the case, you'll be able to make money (on this, i don't know what else you have planned) for a while, and when you can no longer, I hope you open the source like netscape. Technically, though, excellent job! your website is also very pretty! | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{525} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Tim's list of skate-like devices, sorted by flatland speed, descending order:
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{523} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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{94} |
ref: bookmark-0
tags: particle_filter unscented monte_carlo MCMC
date: 12-11-2007 16:46 gmt
revision:2
[1] [0] [head]
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{522} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
from http://www.fcc.gov/oet/info/rules/part15/part15-9-20-07.pdf :
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{520} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
http://www.dspguide.com/ch34.htm -- awesome!! | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{514} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
spectrum options for broadband wireless
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{506} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
So, you want to write inline assembly for the blackfin processor, perhaps to speed things up in a (very) time-constrained environment? Check this first:
Nobody seems to have a complete modifier list for the blackfin, which is needed to actually write something that won't be optimized out :) here is my list --
examples:
Constraints for particular machines - does not include blackfin.
; register operands ; d (r0..r7) ; a (p0..p5,fp,sp) ; e (a0, a1) ; b (i0..i3) ; f (m0..m3) ; B ; c (i0..i3,m0..m3) CIRCREGS ; C (CC) CCREGS | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{504} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
http://www.camsig.co.uk/ -- blackfin is hot like chernobyl. 1" sq 600mhz webserver etc.
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{500} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
This was written for the plik-l mailing list, Nov 16 2007 I actually had a bit of an argument yesterday with my dentist, no less, about global warming:
Mostly I'd have to agree with the dentist - the oil is going to be burned eventually, because it is just such a cheap source of energy. We are going to have to deal with the consequences. However, for coal - of which we have a far greater supply, and is considerably more dangerous / expensive to obtain - there is good reason to search for alternatives, and putting a tax on oil/natural gas now fund development of alternatives is probably very future-responsible, and will shift the energy climate so we relinquish coal (and maybe some oil) earlier, resulting in less CO2 in the atmosphere. There are infinitely many things more worthy/long-range responsible than the war, but our leaders have not touched on that. Correct me if I'm wrong, but there is little evidence that they even measured the worth of all alternatives, and decided rationally, based on integrating (over time and path probability) best-of-present knowledge of benefits and consequences. Or maybe they decided rationally, but with the worth of alternatives measured *personally*. It is this that truly angers me. Bayes for president 2008! Comments:
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{404} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
page 6 on the spec sheet. 55 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{394} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
so, you want to control the LEDs on a BF537-STAMP board? You'll need a linux box with a serial port, then will need to do a few things:
set serverip 192.168.1.149 set ipaddr 192.168.1.200 tftpboot 0x1000000 blink bootelf 0x1000000
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{495} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Electromyography of Eating Apples: Influences of Cooking, Cutting, and Peeling
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{493} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-17614134[0] Equalization filters for multiple-channel electromyogram arrays.
____References____ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{448} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Adobe acrobat reader 7.0 leaks a prodigious amount of memory on my linux system (Debian Etch, stable). However, some pdfs will only open in acroread, so i want to keep the application around for occasional use. Because of the memory leaks, it is not good to have it loaded by default by iceweasel / firefox (evince or xpdf is better). To do this:
that's it! :) | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{487} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
here is the final, concluding, email i sent to nordic semiconductor concerning my 'troubles' with their chip. I post it here in hopes that it may help somebody else out there via the magic of the internet. See {485} for the development of the mode-switch solution (2) and {484} for the dropped packet investigation. Hi xxx, Ok, i figured out both of my problems:
As a result, I'm getting 99.99 % reliability on bidirectional bandwidth of 1.39mbps PTX->PRX and 18.3kbps PRX->PTX. So, I'm a happy person :) :) Hence, I don't have to try another radio solution. Just wanted to pass the information along in case it would help your other customers. cheers, Tim Hanson | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{485} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Problem: switching modes on the nordic radios. see also {486}
solution-
present performance: txed packets = 118513 rxed packets = 118218 (note: computer has seen 118512 packets ) (and 118414 status packets, ratio: 0.999165 ) (note: 'stage ratio 0.997511 )(this includes code validation) now, if i boost the SPI clock on the bridge up to 5 mhz (headstage clock still running at 8.25mhz) to eliminate race-case (?) & add in 16 data packets before the status packets, perfection: txed packets = 44151 rxed packets = 44151 (note: computer has seen 750583 packets ) (and 44152 status packets, ratio: 1.000023 ) (note: 'stage ratio 1.000000 )after adding separate counters for TXed status and TXed data packets: txed packets = 808640 rxed packets = 50538 txed status packets = 50540 (note: computer has seen 808639 packets, ratio : 0.999999 ) (and 50540 status packets, ratio: 1.000000 ) (note: 'stage ratio 0.999960 )yay!! almost no dropped packets!! This equates to :
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{486} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
here is an email I wrote to nordic semiconductor technical support concerning switching reception/transmission modes. see also {487} & {485} Hello, I've been having problems with switching modes on the nRF24L01. I want to implement a asymmetric bidirectional link, where there is a periodic (every ~36ms) time when the primary transmitter sends a status packet, then listens for a 32-byte command packet from the primary receiver. The command packet is for conveying configuration information, etc. I am driving both radios with blackfin DSPs using the built-in SPI port @ 4mhz, and am very careful with the CSN signal. The shock-burst feature is not enabled. Unidirectional transfer works great - I get nearly 0% dropped packets when the primary transmitter & receiver never change modes, up to a rate of about 1.5mbps. Of course, I am careful not to let the radio stay in TX mode for more than 4 ms - every 3ms i give it a 'break' by de-asserting CE. But bidirectional does not work reliably. Here is my procedure, on the primary transmitter side, for sending a status packet then changing from TX to RX & back to TX, with the initial condition that CE is asserted:
The process on the primary receiver is basically the same, but inverted. Upon receiving a packet of the correct type, it switches to transmit mode, sends off a packet, waits for the TX_DS interrupt, and switches back to RX mode. Like I said, when the transmitter and receiver never switch modes, the packets always get through without any corruption. When they switch roles for one packet, only ~ 78% get through, making the status packet -> command packet reply about 62% reliable. This is when the radio is only sending status packets - hence mostly it is in what the datasheet calls 'standby-II mode'. When the radio is also transmitting data packets, the status packet -> command packet relay is about 79% reliable, suggesting that the first packet after a switch from RX to TX mode is somehow being lost. Indeed, when I look at the IRQ signals on an oscilloscope, it is apparent that a certain percentage of the time the TX_DS interrupt is not followed by a RX_DR interrupt. so - what am I doing wrong??!! I'm desperate to make this work, and have tried almost every permutation! thanks, Tim Hanson | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{484} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
experimential results with the Nordic nRF24l01 (recall, as per {477}, that all SPI signals have an in-line 100 ohm resistor on both the headstage and bridge)
finally, it is solved!how:
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{477} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
I've been having problems transmitting packets in a pipelined fashion using the nordic nRF24L01 tranciever IC. Namely, I cannot send multiple packets at once by keeping the on-chip 3-packet fifo full (note packets are 32 bytes data, max; with header/CRC, they are close to 40 bytes). If this fifo is full, the radio should remain in transmit mode - see {470}, and also {484} Above, what happens when I let the fifo go dry / empty, and force the PLL to resync for each transmitted packet, as per the following sequence:
Note just about all packets are received properly and that the RX irq closely follows the TX irq. Above, what happens when i try to pipeline transmission, e.g.
One initial theory was that noise on the SPI bus was corrupting the packets. However:
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{483} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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{479} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
http://pespmc1.vub.ac.be/books/IntroCyb.pdf -- dated, but still interesting, useful, a book in and of itself!
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{378} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
http://www.palowireless.com/infotooth/tutorial/baseband.asp
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{476} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{475} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
http://www.neuroconnex.com/ -- looks like they have some excellent products, but not sure how to purchase them.
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{472} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
buglabs, makers of plug n' play configurable handheld platform based on open-source technologies
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{464} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
The problem: I have an interrupt status routine (ISR) which can interrupt the main, radio-servicing routine at any time. To keep the ISR from corrupting the register values of the main routine while it works, these registers must be pushed, and later popped, to the stack. Now, doing this takes time, so I'd prefer to pop / push as few registers as possible. Namely, I don't want to push/pop the hardware loop registers - LC0 (loop counter 0), LB0 (loop bottom 0, where the hardware loop starts) & LT0 (loop top 0, where the hardware loop ends). Gcc seems to only touch bank 1, never bank 0, so I don't have to save the 3 regs above. However, to make sure, I've written a perl file to examine the assembled code: my $file = "decompile.asm"; open(FH, $file); @j = <FH>; my $i=0; my @badregs = ("LC0", "LB0", "LT0"); foreach $reg (@badregs){ foreach $k (@j){ if($k =~ /$reg/){ $i++; print "touch register $reg : $k"; } } } #tell make if we found problems or not. if($i>0){ exit 1; }else{ exit 0; } 'make' looks at the return value perl outputs, as instructed via the makefile (relevant portion below): headstage.ldr:headstage.dxe rm -f *.ldr $(LDR) -T BF532 -c headstage.ldr $< bfin-elf-objdump -d headstage.dxe > decompile.asm perl register_check.pl if it finds assembly which accesses the 'bad' registers, make fails. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{471} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Little Stupid Details - what they are, and how to avoid them
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{465} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
good explanation of 32-bit CRC (from the blackfin BF537 hardware ref): | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{444} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
nordic semi links: here is the connection list for the nRF24L01 module made by sparkfunelectronics
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{447} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
things required to enable interrupts on a blackfin processor, not necessarily in order though all are required (also see the list, in the programming ref, on page 4-31):
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{445} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
pretty impressive project, especially considering how much time and money they spent ($15 m, 6 man-months to do the verilog (only!)) http://www.hotchips.org/archives/hc16/3_Tue/1_HC16_Sess6_Pres1_bw.pdf | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{439} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
abandoned because I realized that I could work on 2 channels at once (as there are 2 MACs onboard) & could use the s2rnd multiply-accumulate flay & could load registers 32bits at a time! ah well, might as well archive my efforts :) r6.h = 2048; r0.l = r0.l - r6.h (s) || r1.l = w[i0++] || r2.l = w[i1++]; //subtract offset, load a1[0] into r1.l, w1[0] into r2.l a0 = r0.l * r1.l (is) || r1.h = w[i0++]; //mac in*a1[0], load a[1] to r1.h a0 += r2.l * r1.h (is) || r1.l = w[i0++]|| r2.h = w[i1--]; //mac w[0]*a1[1], load a1[2] into r1.l, w1[1] to r2.h r4 = (a0 += r2.h * r1.l) (is) || r3.l = w[i0++]; //mac w1[1]*a1[2] store to r4, b1[0] to r3.l r4 = r4 >>> 14 || r3.h = w[i0++]; //arithmetic right shift, 32 bit inst, b1[1] to r3.h, r4 is new w1. a0 = r4.l * r3.l (is) || w[i1++] = r4.l; //mac w1*b1[0], save w1 into w1[0] a0 += r2.l * r3.h (is) || w[i1++] = r2.l; //mac w1[0]*b[1], save w1[0] into w1[1] r4 = (a0 += r2.h * r3.l) (is) || r1.l = w[i0++] || r2.l = w[i1++];//mac w1[1]*b1[0] store r4, a2[0] to r1.l, w2[0] to r2.l r4 = r4 >>> 14 || r1.h = w[i0++] || r2.h = w[i1--]; //arith. right shift, a2[1] to r1.h, w2[1] to r2.h a0 = r4.l * r1.l (is); //mac in*a2[0], a2[2] into r1.l a0 += r2.l * r1.h (is) || rl.l = w[i0++]; //mac w2[0]*a2[1], b2[0] into r3.l r4 = (a0 += r2.h * r1.l) (is) || r3.l = w[i0++]; //mac w2[1]*a2[2] store r4, b2[1] into r3.h r4 = r4 >>> 14 || r3.h = w[i0++]; //arithmetic shift to get w2, b2[2] to r3.h a0 = r4.l * r3.l (is) || w[i1++] = r4.l; //mac w2 * b2[0], store w2 to w2[0] a0 += r2.l * r3.h (is) || w[i1++] = r2.l; //mac w2[0]*b2[1], store w2[0] to w2[1]. i1 now pointing to secondary channel. r4 = (a0 += r2.h * r3.l) (is) || i0 -= 10; //mac w2[1]*b2[0]. reset coeff ptr. done with pri chan, save in r5. r5 = r4 >>> 14; //time for the secondary channel! r0.h = r0.h - r6.h (s) || r1.l = w[i0++] || r2.l = w[i1++]; //subtract offset, load a1[0] to r1.1, w1[0] to r2.l a0 = r0.h * r1.l (is) || r1.h = w[i0++] ; //mac in*a1[0], a1[1] to r1.h, save out samp pri. a0 += r2.l * r1.h (is) || r1.l = w[r0++] || r2.h = w[i1--]; //mac w1[0]*a1[1], a1[2] to r1.l, w1[1] to r2.h r4 = (a0 += r2.h * r1.l) (is) || r3.l = w[i0++]; //mac, b1[0] to r3.l r4 = r4 >>> 14 || r3.h = w[i0++]; //arithmetic shift, b1[1] to r3.h a0 = r4.l * r3.l (is) || w[i1++] = r4.l; //mac w1*b1[0], save w1 to w1[0] a0 += r2.l * r3.h (is) || w[i++] = r2.l; //mac w1[0], save w1[0] to w1[1] r4 = (a0 += r2.h * r3.l) (is) || r1.l = w[i0++] || r2.l = w[i1++]; //mac w1[1]*b1[0] store r4, a2[0] to r1.l, w2[0] to r2.l r4 = r4 >>> 14 || r2.h = w[i1--]; // r4 output of 1st biquad, w2[1] to r2.h a0 = r4.l * r1.l (is) || r1.h = w[i0++] ; //mac in* a2[0], a2[1] to r1.h a0 += r2.l * r1.h (is) || r1.h = w[i0++] ; //mac w2[0]*a2[1], a2[2] to r1.l r4 = (a0 += r2.h * r1.l) (is) || r3.l = w[i0++]; //mac w2[1]*a2[2], b2[0] to r3.l r4 = r4 >>> 14 || r3.h = w[i0++]; //r4 is w2, b2[2] to r3.h a0 = r4.l * r3.l (is) || w[i++] = r4.l ; //mac w2 * b2[0], store w2 to w2[0] a0 += r2.l * r3.h (is) || w[i++] = r2.l; //mac w2[0] * b2[1], store w2[0] to w2[1]. i1 now pointing to next channel. r4 = (a0 += r2.h * r3.l) (is) || i0 -= 10; //mac w2[1] * b2[0], reset coeff. ptr, save in r4. r4 = r4 >>> 14; here is a second (but still not final) attempt, once i realized that it is possible to issue 2 MACS per cycle // I'm really happy with this - every cycle is doing two MMACs. :) /* // i0 i1 (in 16 bit words) r1 = [i0++] || r4 = [i1++]; // 2 2 r1= a0 a1 r4= w0's a0 = r0.l * r1.l, a1 = r0.h * r1.l || r2 = [i0++] || r5 = [i1]; // 4 2 r2= a2 a2 r5= w1's a0 += r4.l * r1.h, a1 = r4.h * r1.h || r3 = [i0++] || [i1--] = r4; // 6 0 r3= b0 b1 w1's=r4 r0.l = (a0 += r5.l * r2.l), r0.h = (a1 += r5.h * r2.l)(s2rnd); a0 = r0.l * r3.l, a1 = r0.h * r3.l || [i1++] = r0; // 6 2 w0's = r0 a0 += r4.l * r3.h, a1 += r4.h * r3.h || r1 = [i0++] || i1 += 4; // 8 4 r1 = a0 a1 //load next a[0] a[1] to r1; move to next 2nd biquad w's; don't reset the coef pointer - move on to the next biquad. r0.l = (a0 += r5.l * r3.l), r0.h = (a1 += r5.h * r3.l)(s2rnd) || r4 = [i1++]; // 8 6 r4 = w0's, next biquad //note: the s2rnd flag post-multiplies accumulator contents by 2. see pg 581 or 15-69 //second biquad. a0 = r0.l * r1.l, a1 = r0.h * r1.l || r2 = [i0++] || r5 = [i1]; // 10 6 r2= a2 a2 r5 = w1's a0 += r4.l * r1.h, a1 += r4.h * r1.h || r3 = [i0++] || [i1--] = r4; // 12 4 r3= b0 b1 w1's = r4 r0.l = (a0 += r5.l * r2.l), r0.h = (a1 += r5.h * r2.l)(s2rnd); // a0 = r0.l * r3.l, a1 = r0.h * r3.l || [i1++] = r0; // 12 6 w0's = r0 a0 += r4.l * r3.h, a1 += r4.h * r3.h || r1 = [i0++] || i1 += 4; // 14 8 r1 = a0 a1 r0.l = (a0 += r5.l * r3.l), r0.h = (a1 += r5.h * r3.l)(s2rnd) || r4 = [i1++]; // 14 10 r4 = w0's //third biquad. a0 = r0.l * r1.l, a1 = r0.h * r1.l || r2 = [i0++] || r5 = [i1]; // 16 10 r2= a2 a2 r5 = w1's a0 += r4.l * r1.h, a1 += r4.h * r1.h || r3 = [i0++] || [i1--] = r4; // 18 8 r3= b0 b1 w1's = r4 r0.l = (a0 += r5.l * r2.l), r0.h = (a1 += r5.h * r2.l)(s2rnd); // a0 = r0.l * r3.l, a1 = r0.h * r3.l || [i1++] = r0; // 18 10 w0's = r0 a0 += r4.l * r3.h, a1 += r4.h * r3.h || r1 = [i0++] || i1 += 4; // 20 12 r1 = a0 a1 r0.l = (a0 += r5.l * r3.l), r0.h = (a1 += r5.h * r3.l)(s2rnd) || r4 = [i1++]; // 20 14 r4 = w0's //fourth biquad. a0 = r0.l * r1.l, a1 = r0.h * r1.l || r2 = [i0++] || r5 = [i1]; // 22 14 a0 += r4.l * r1.h, a1 += r4.h * r1.h || r3 = [i0++] || [i1--] = r4; // 24 12 r0.l = (a0 += r5.l * r2.l), r0.h = (a1 += r5.h * r2.l)(s2rnd); a0 = r0.l * r3.l, a1 = r0.h * r3.l || [i1++] = r0; // 24 14 a0 += r4.l * r3.h, a1 += r4.h * r3.h || i1 += 4; // 24 16 r0.l = (a0 += r5.l * r3.l), r0.h = (a1 += r5.h * r3.l)(s2rnd); // 48: loop back; 32 bytes: move to next channel. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{442} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
http://mirror.mricon.com/french/french.html -- "how i learned french in a year"
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{441} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
So, in order to measure how quantizing filter coeficients affects filter response, I quantized the coefficients of a 8th order bandpass filter designed with: [B1, A1] = ellip(4,0.8,70, [600/31.25e3 6/31.25]);here is a function that quantizes & un-quantizes the filter coeff, then compares the frequency responses: function [Bq, Aq, Bcoef, Acoef] = filter_quantize(B, A) % quantize filter coeficients & un-quantize so as to get some idea to % the *actual* fixed-point filter performance. % assume that everything in broken into biquads. base = 10; Aroots = roots(A); Broots = roots(B); order = length(Aroots)/2; % the number of biquads. scale = B(1).^(1/order); % distribute the gain across the biquads. for o = 0:order-1 Acoef_biquad(o+1, :) = poly(Aroots(o*2+1 : o*2+2)); Bcoef_biquad(o+1, :) = poly(Broots(o*2+1 : o*2+2))*scale; end Bcoef = round(Bcoef_biquad .* 2^base); Acoef = round(Acoef_biquad .* 2^base); % now, reverse the process. Bq2 = Bcoef ./ 2^base; Aq2 = Acoef ./ 2^base; for o = 0:order-1 Arootsq(o*2+1: o*2+2) = roots(Aq2(o+1, :)); Brootsq(o*2+1: o*2+2) = roots(Bq2(o+1, :)); end Aq = poly(Arootsq); Bq = poly(Brootsq).*B(1); [H, W] = freqz(B, A); [Hq, Wq] = freqz(Bq, Aq); figure plot(W, db(abs(H)), 'b') hold on plot(W, db(abs(Hq)), 'r') axis([0 pi -100 0])The result: high frequency is not much affected but low frequency is strongly affected. But this is at a quatization to 10 bits - quantization to 15 bits lead to reasonably good performance. I'm not sure if this conclusively indicates / counterindicates downsampling prior to highpassing for my application, but i would say that it does, as if you downsample by 2 the highpass cutoff frequency will be 2x larger hence the filter will be less senitive to quantization errors which affect low frequencies. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
so, you want to look at internal registers on your embedded blackfin processor? register access is probably enough to help A LOT with debugging!
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{213} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
openwince:
IR length: 22 Chain length: 3 Device Id: 00000001010000110100000010010011 Manufacturer: Xilinx Unknown part! Device Id: 00000101000001000110000010010011 Manufacturer: Xilinx Unknown part! Device Id: 00000101000001000101000010010011 Manufacturer: Xilinx Unknown part! chain.c(110) Part 0 without active instruction chain.c(133) Part 0 without active instruction chain.c(110) Part 0 without active instruction Pictures from the ragged stone user manual explain the pin numbering and orientation of the 2mm 14 pin dual row jatag header (compatable with Xilinx parallel port JTAG programmer & hence linux's jtag tools) | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{432} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{410} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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{409} |
ref: bookmark-0
tags: optimization function search matlab linear nonlinear programming
date: 08-09-2007 02:21 gmt
revision:0
[head]
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http://www.mat.univie.ac.at/~neum/ very nice collection of links!! | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{405} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{403} |
ref: bookmark-0
tags: blackfin ELF freestanding applications boot
date: 08-01-2007 14:40 gmt
revision:0
[head]
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http://www.johanforrer.net/BLACKFIN/index.html very good, very instructive. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{402} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
some cool fonts -- > sudo apt-get install ttf-bitstream-vera ttf-dejavu ttf-bpg-georgian-fonts ttf-dustin ttf-f500 ttf-freefont ttf-gentium ttf-isabella ttf-junicode ttf-kacst ttf-khmeros ttf-mgopen ttf-sjfonts ttf-staypuft ttf-summersby t1-xfree86-nonfree ttf-xfree86-nonfree ttf-larabie-deco ttf-larabie-straight ttf-larabie-uncommon | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{401} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
http://hardm.ath.cx:88/pdf/RFpenetrationInTissue.pdf
even more interesting: wireless brain machine interface | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{397} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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{392} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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{386} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
http://video.google.com/videoplay?docid=-3254488777215293198 need to learn more about this infamous federal reserve! | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{382} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
a while ago I made a custom keyboard for myself - something like the frogPad chording keyboard, but more suitable for programming. Here is the image i made for myself to learn the layout. Upon testing, however, it seems that those scribbly marks on the paper had some import - this is the present layout, as re-drawn in inkscape. Presumably this second iteration is better? | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{379} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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{373} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
http://xtronics.com/reference/viscosity.htm the source site - http://xtronics.com/ - has a lot of interesting information. The author seems as enamored with Debian as I am. (hence, there is plenty of Debian information there :) for example, they have a quick reference on kicad: http://xtronics.com/reference/kicad.html | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{372} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
oh yea!!! nice work mate!! http://www.rohrbacher.net/kicad/quicklib.php btw, kicad is the shit - and it is now in Debian!! I love debian! I love kicad! | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{367} |
ref: notes-0
tags: RF telemetry differential phase shift key prosthesis power transmission TETS PSK
date: 05-12-2007 23:13 gmt
revision:0
[head]
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transcutaneous data telemetry system tolerant to power telemetry interference
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{362} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
An experiment with bluetooth, jabra, and hypothetical wireless lowfi neural recording:
# HCId options options { # Automatically initialize new devices autoinit yes; # Security Manager mode # none - Security manager disabled # auto - Use local PIN for incoming connections # user - Always ask user for a PIN # security auto; # Pairing mode # none - Pairing disabled # multi - Allow pairing with already paired devices # once - Pair once and deny successive attempts pairing multi; # Default PIN code for incoming connections passkey "0000"; } # Default settings for HCI devices device { # Local device name # %d - device id # %h - host name name "%h-%d"; # Local device class # class 0x3e0100; #--host class 0x500204; # Default packet type #pkt_type DH1,DM1,HV1; # Inquiry and Page scan iscan enable; pscan enable; # Default link mode # none - no specific policy # accept - always accept incoming connections # master - become master on incoming connections, # deny role switch on outgoing connections lm accept; # Default link policy # none - no specific policy # rswitch - allow role switch # hold - allow hold mode # sniff - allow sniff mode # park - allow park mode lp rswitch,hold,sniff,park; } And here is /etc/bluetooth/rfcomm.conf: (I added the device MAC and turned on automatic binding.. not sure if that was a good thing to do) rfcomm0 { # Automatically bind the device at startup bind yes; # Bluetooth address of the device device 00:16:8F:BF:7B:E0; # RFCOMM channel for the connection channel 1; # Description of the connection comment "Example Bluetooth device"; }
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{354} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
____References____ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{71} |
ref: Francis-2005.11
tags: Joe_Francis motor_learning reaching humans delay intertrial interval
date: 04-09-2007 22:48 gmt
revision:1
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PMID-16132970[0] The Influence of the Inter-Reach-Interval on Motor Learning. Previous studies have demonstrated changes in motor memories with the passage of time on the order of hours. We sought to further this work by determining the influence that time on the order of seconds has on motor learning by changing the duration between successive reaches (inter-reach-interval IRI). Human subjects made reaching movements to visual targets while holding onto a robotic manipulandum that presented a viscous curl field. We tested four experimental groups that differed with respect to the IRI (0.5, 5, 10 or 20 sec). The 0.5 sec IRI group performed significantly worse with respect to a learning index than the other groups over the first set of 192 reaches. Each group demonstrated significant learning during the first set. There was no significant difference with respect to the learning index between the 5, 10 or 20 sec IRI groups. During the second and third set of 192 reaches the 0.5 sec IRI group's performance became indistinguishable from the other groups indicating that fatigue did not cause the initial poor performance and that with continued training the initial deficit in performance could be overcome. ____References____ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{106} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-15208695[0] PDF HTML summary Optimal feedback control and the neural basis of volitional motor control by Stephen S. Scott ____References____ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{104} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
this seems to be the same as {339}, with a different pubmed id & different author list. bug in the system! PMID-16193273[0] On the relations between single cell activity in the motor cortex and the direction and magnitude of three-dimensional dynamic isometric force* the majority of cells responded to direction
____References____ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{32} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
http://www.ixo.de/info/usb_jtag/ open source USB Jtag adapter, works with dragon (I think!) | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{278} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-17143147[0] Decoding movement intent from human premotor cortex neurons for neural prosthetic applications
____References____ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{286} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-8463818[0] Contribution of the monkey corticomotoneuronal system to the control of force in precision grip
____References____ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{345} |
ref: HeppReymond-1999.09
tags: force motor control grip electrophysiology
date: 04-09-2007 20:20 gmt
revision:0
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PMID-10473750[0] Context-dependent force coding in motor and premotor cortical areas.
____References____ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{344} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-2027042[0] Making arm movements within different parts of space: the premotor and motor cortical representation of a coordinate system for reaching to visual targets.
____References____ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{294} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-2376768[0] Making arm movements within different parts of space: dynamic aspects in the primate motor cortex
____References____ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{337} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-2723767[0] A comparison of movement direction-related versus load direction-related activity in primate motor cortex, using a two-dimensional reaching task.
____References____ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{335} |
ref: Georgopoulos-1992.06
tags: motor control force Georgopoulos
date: 04-09-2007 19:56 gmt
revision:1
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PMID-1609282[0] The motor cortex and the coding of force.
____References____ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{340} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-12522173[0] Systematic changes in motor cortex cell activity with arm posture during directional isometric force generation.
____References____ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{339} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-8817266[0] On the relations between single cell activity in the motor cortex and the direction and magnitude of three-dimensional static isometric force.
____References____ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{326} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-9331494[0] Force and the motor cortex.
____References____ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{259} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-17271543[] http://hardm.ath.cx:88/pdf/sanchez2004.pdf ____References____ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{290} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-14610628[0] A critical evaluation of the force control hypothesis in motor control.
____References____ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{273} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-12879039[0] Military-funded research is not unethical heh! ____References____ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{266} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-15852014[] Decoding the visual and subjective contents of the human brain
____References____ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{263} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-15811234[] Mirror Neurons Responding to Observation of Actions Made with Tools in Monkey Ventral Premotor Cortex
____References____ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{226} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{243} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-17035544 Dopaminergic control of sleep-wake states.
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{25} |
ref: Dum-2003.01
tags: cerebellum dentate_nucleus projections cerebrum prefrontal posterior_pareital M1 PM thalamus somatotopic
date: 03-11-2007 04:42 gmt
revision:2
[1] [0] [head]
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PMID-12522208 An unfolded map of the cerebellar dentate nucleus and its projections to the cerebral cortex
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{229} |
ref: notes-0
tags: SNR MSE error multidimensional mutual information
date: 03-08-2007 22:33 gmt
revision:2
[1] [0] [head]
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http://ieeexplore.ieee.org/iel5/516/3389/00116771.pdf or http://hardm.ath.cx:88/pdf/MultidimensionalSNR.pdf
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{228} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
http://www.borbelyaudio.com/adobe/ae599bor.pdf
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{225} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
First Experiments to test plasma confinement by magnetic dipole
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{27} |
ref: notes-0
tags: VOR OKR climbing_fibers cerebellum purkinje cells
date: 02-05-2007 23:45 gmt
revision:1
[0] [head]
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{190} |
ref: Lavin-2005.05
tags: dopamine PFC VTA prefrontal_cortex ventral_tegmentum 2005
date: 02-05-2007 20:37 gmt
revision:1
[0] [head]
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PMID-15901782[0]Mesocortical Dopamine Neurons Operate in Distinct Temporal Domains Using Multimodal Signaling
____References____ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{198} |
ref: Teich-1997.03
tags: fractal LGN RGC electrophysiology SUA fano_factor
date: 02-05-2007 19:00 gmt
revision:0
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PMID-9058948[0] Fractal character of the neural spike train in the visual system of the cat
http://hardcarve.com/wikipic/Teich1997_fanofactor.gif ____References____ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{176} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-15010499[0] Recursive Bayesian Decoding of Motor Cortical Signals by Particle Filtering
____References____ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{197} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-15151178[0] Sequential Rearrangements of the Ensemble Activity of Putamen Neurons in the Monkey Brain as a Correlate of Continuous Behavior
____References____ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{23} |
ref: Vyssotski-2006.02
tags: neurologger neural_recording recording_technology EEG SUA LFP electrical engineering
date: 02-05-2007 06:21 gmt
revision:6
[5] [4] [3] [2] [1] [0] [head]
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PMID-16236777[0] Miniature neurologgers for flying pigeons: multichannel EEG and action and field potentials in combination with GPS recording. Recording neuronal activity of animals moving through their natural habitat is difficult to achieve by means of conventional radiotelemetry. This illustration shows a new approach, exemplified by a homing pigeon carrying both a small GPS path recorder and a miniaturized action and field potential logger (“neurologgerâ€), the entire assembly weighing maximally 35 g, a load carried easily by a pigeon over a distance of up to 50 km. Before release at a distant location, the devices are activated and store both positional and neuronal activity data during the entire flight. On return to the loft, all data are downloaded and can be analyzed using software for path analysis and electrical brain activity. Thus single unit activity or EEG patterns can be matched to the flight path superimposed on topographical maps. Such neurologgers may also be useful for a variety of studies using unrestrained laboratory animals in different environments or test apparatuses. The prototype on the hand-held pigeon records and stores EEG simultaneously from eight channels up to 47 h, or single unit activity from two channels during 9 h, but the number of channels can be increased without much gain in weight by sandwiching several of these devices. Further miniaturization can be expected. For details, see Vyssotski AL, Serkov AN, Itskov PM, Dell Omo G, Latanov AV, Wolfer DP, and Lipp H-P. Miniature neurologgers for flying pigeons: multichannel EEG and action and field potentials in combination with GPS recording. [1] ____References____ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{7} |
ref: bookmark-0
tags: book information_theory machine_learning bayes probability neural_networks mackay
date: 0-0-2007 0:0
revision:0
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http://www.inference.phy.cam.ac.uk/mackay/itila/book.html -- free! (but i liked the book, so I bought it :) | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{10} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
items 2-4 are not in accord with the stated purpose of leptin (1). | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{15} |
ref: bookmark-0
tags: monte_carlo MCMC particle_filter probability bayes filtering biblography
date: 0-0-2007 0:0
revision:0
[head]
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http://www-sigproc.eng.cam.ac.uk/smc/papers.html -- sequential monte carlo methods. (bibliography)
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{22} |
ref: Brown-2001.11
tags: Huntingtons motor_learning intentional implicit cognitive deficits
date: 0-0-2007 0:0
revision:0
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PMID-11673321 http://brain.oxfordjournals.org/cgi/content/full/124/11/2188 :
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{37} |
ref: bookmark-0
tags: Unscented sigma_pint kalman filter speech processing machine_learning SDRE control UKF
date: 0-0-2007 0:0
revision:0
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{77} |
ref: Kilgard-1998.03
tags: dopamine basal_forebrain nucleus_basalis cortical_plasticity
date: 0-0-2007 0:0
revision:0
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PMID-9497289[0] Cortical map reorganization enabled by nucleus basalis activity
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{98} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
http://hardm.ath.cx/pdf/unscentedKalmanFilter.pdf -- the square root transform. contains a nice tabulation of the original algorithm, which i what I use. http://hardm.ath.cx/pdf/unscentedKalmanFilter2000.pdf -- the original, with examples of state, parameter, and dual estimation http://en.wikipedia.org/wiki/Kalman_filter -- wikipedia page, also has the unscented kalman filter http://www.cs.unc.edu/~welch/kalman/media/pdf/Julier1997_SPIE_KF.pdf - Julier and Ulhmann's original paper. a bit breif. http://www.cs.ubc.ca/~murphyk/Papers/Julier_Uhlmann_mar04.pdf -- Julier and Ulhmann's invited paper, quite excellent. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{103} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
The Computational Neurobiology of Reaching and Pointing - online notes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{110} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Iso learning approximates a solution to the inverse controller problem in an usupervised behavioral paradigm http://hardm.ath.cx/pdf/isolearning2002.pdf
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{141} |
ref: learning-0
tags: motor control primitives nonlinear feedback systems optimization
date: 0-0-2007 0:0
revision:0
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http://hardm.ath.cx:88/pdf/Schaal2003_LearningMotor.pdf not in pubmed. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{140} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-15649663 Composite adaptive control with locally weighted statistical learning.
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{146} |
ref: van-2004.11
tags: anterior cingulate cortex error performance monitoring 2004
date: 0-0-2007 0:0
revision:0
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PMID-15518940 Errors without conflict: implications for performance monitoring theories of anterior cingulate cortex.
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{147} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-12899253 Boosting bit rates and error detection for the classification of fast-paced motor commands based on single-trial EEG analysis
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{148} |
ref: Vidal-2000.01
tags: EEG ERN error negativity conflict resolution 2000
date: 0-0-2007 0:0
revision:0
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PMID-10686362 Is the 'error negativity' specific to errors?
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{151} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-11741014 Computational approaches to motor control. Tamar Flash and Terry Sejnowski.
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{192} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PMID-11073866 Ventral Tegmental Area Afferents to the Prefrontal Cortex Maintain Membrane Potential ‘Up’ States in Pyramidal Neurons via D1 Dopamine Receptors
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{4} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{6} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
okay, so i spent some time on this and eventually realized that linux doesn't (can't) have all the symbols of the windows fonts used in MathML (for example the pitchfork symbol). The general solution, as per http://mcelrath.org/Notes/MathML, is not so difficult:
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{13} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
http://www.beautifulcrime.com/public/exhibitions/ Need flash to view the site. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{14} |
ref: bookmark-0
tags: urban art san_francisco california vector_art mod_art store
date: 0-0-2006 0:0
revision:0
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{18} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SELECT * FROM `base` WHERE MATCH(`From`, `To`) AGAINST('hanson') ORDER BY `Date` DESC Limit 0, 100
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{31} |
ref: bookmark-0
tags: job_search professional employment wisdom
date: 0-0-2006 0:0
revision:0
[head]
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{40} |
ref: bookmark-0
tags: Bayes Baysian_networks probability probabalistic_networks Kalman ICA PCA HMM Dynamic_programming inference learning
date: 0-0-2006 0:0
revision:0
[head]
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http://www.cs.ubc.ca/~murphyk/Bayes/bnintro.html very, very good! many references, well explained too. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{45} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
http://www.newscientist.com/article/dn8859-methanolpowered-artificial-muscles-start-to-flex.html | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{47} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{50} |
ref: bookmark-0
tags: teflon PTFE bonding metal polytetrafluoroethylene tetraflouroethylene
date: 0-0-2006 0:0
revision:0
[head]
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http://pslc.ws/mactest/ptfeidea.htm block copolymer: http://en.wikipedia.org/wiki/Copolymer | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{51} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
http://www.ddj.com/dept/architect/184414658 very logical, well organized. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{52} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
http://www.evl.uic.edu/eolmst1/GLSL/ easy to compile on my debian system - all the development libraries had debian packages! also of interest :
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{57} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
http://www.cs.rug.nl/~rudy/matlab/
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{66} |
ref: bookmark-0
tags: machine_learning classification entropy information
date: 0-0-2006 0:0
revision:0
[head]
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http://iridia.ulb.ac.be/~lazy/ -- Lazy Learning. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{72} |
ref: abstract-0
tags: tlh24 error signals in the cortex and basal ganglia reinforcement_learning gradient_descent motor_learning
date: 0-0-2006 0:0
revision:0
[head]
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Title: Error signals in the cortex and basal ganglia. Abstract: Numerous studies have found correlations between measures of neural activity, from single unit recordings to aggregate measures such as EEG, to motor behavior. Two general themes have emerged from this research: neurons are generally broadly tuned and are often arrayed in spatial maps. It is hypothesized that these are two features of a larger hierarchal structure of spatial and temporal transforms that allow mappings to procure complex behaviors from abstract goals, or similarly, complex sensory information to produce simple percepts. Much theoretical work has proved the suitability of this organization to both generate behavior and extract relevant information from the world. It is generally agreed that most transforms enacted by the cortex and basal ganglia are learned rather than genetically encoded. Therefore, it is the characterization of the learning process that describes the computational nature of the brain; the descriptions of the basis functions themselves are more descriptive of the brain’s environment. Here we hypothesize that learning in the mammalian brain is a stochastic maximization of reward and transform predictability, and a minimization of transform complexity and latency. It is probable that the optimizations employed in learning include both components of gradient descent and competitive elimination, which are two large classes of algorithms explored extensively in the field of machine learning. The former method requires the existence of a vectoral error signal, while the latter is less restrictive, and requires at least a scalar evaluator. We will look for the existence of candidate error or evaluator signals in the cortex and basal ganglia during force-field learning where the motor error is task-relevant and explicitly provided to the subject. By simultaneously recording large populations of neurons from multiple brain areas we can probe the existence of error or evaluator signals by measuring the stochastic relationship and predictive ability of neural activity to the provided error signal. From this data we will also be able to track dependence of neural tuning trajectory on trial-by-trial success; if the cortex operates under minimization principles, then tuning change will have a temporal relationship to reward. The overarching goal of this research is to look for one aspect of motor learning – the error signal – with the hope of using this data to better understand the normal function of the cortex and basal ganglia, and how this normal function is related to the symptoms caused by disease and lesions of the brain. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{85} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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{86} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
pretty simple, to add a .mp3 to all files in a directory (e.g. if they originally were on an old mac): rename 's/(.*)/$1.mp3/' *the expression in quotes is just a perl regular expression | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{90} |
ref: bookmark-0
tags: mirror reflective projection lens design NEC optics
date: 0-0-2006 0:0
revision:0
[head]
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http://www.nec.co.jp/techrep/en/journal/g06/n03/060319.html very neat - and I'm surprised that they put all of this on the web! you can almost make one of these yourself with the information within. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
{92} | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
with the extended kalman filter, from '92: http://ftp.ccs.neu.edu/pub/people/rjw/kalman-ijcnn-92.ps with the unscented kalman filter : http://hardm.ath.cx/pdf/NNTrainingwithUnscentedKalmanFilter.pdf |