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[0] Gage GJ, Ludwig KA, Otto KJ, Ionides EL, Kipke DR, Naive coadaptive cortical control.J Neural Eng 2:2, 52-63 (2005 Jun)

[0] Jackson A, Mavoori J, Fetz EE, Correlations between the same motor cortex cells and arm muscles during a trained task, free behavior, and natural sleep in the macaque monkey.J Neurophysiol 97:1, 360-74 (2007 Jan)

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ref: -0 tags: multimode fiber imaging date: 11-15-2019 03:10 gmt revision:2 [1] [0] [head]

PMID-30588295 Subcellular spatial resolution achieved for deep-brain imaging in vivo using a minimally invasive multimode fiber

  • Oh wow wowww
  • Imaged through a 50um multimode optical fiber!
  • Multimode scattering matrix was inverted through a LC-SLM

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ref: -0 tags: adaptive optics sensorless retina fluorescence imaging optimization zernicke polynomials date: 11-15-2019 02:51 gmt revision:0 [head]

PMID-26819812 Wavefront sensorless adaptive optics fluorescence biomicroscope for in vivo retinal imaging in mice

  • Idea: use backscattered and fluorescence light to optimize the confocal image through imperfect optics ... and the lens of the mouse eye.
    • Optimization was based on hill-climbing / line search of each Zernicke polynomial term for the deformable mirror. (The mirror had to be characterized beforehand, naturally).
    • No guidestar was needed!
  • Were able to resolve the dendritic processes of EGFP labeled Thy1 ganglion cells and Cx3 glia.

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ref: -2019 tags: non degenerate two photon excitation fluorophores fluorescence OPO optical parametric oscillator date: 10-31-2019 20:53 gmt revision:0 [head]

Efficient non-degenerate two-photon excitation for fluorescence microscopy

  • Used an OPO + delay line to show that non-degenerate (e.g. photons of two different energies) can induce greater fluorescence, normalized to input energy, than normal same-energy excitation.

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ref: -2015 tags: PaRAC1 photoactivatable Rac1 synapse memory optogenetics 2p imaging mouse motor skill learning date: 10-30-2019 20:35 gmt revision:1 [0] [head]

PMID-26352471 Labelling and optical erasure of synaptic memory traces in the motor cortex

  • Idea: use Rac1, which has been shown to induce spine shrinkage, coupled to a light-activated domain to allow for optogenetic manipulation of active synapses.
  • PaRac1 was coupled to a deletion mutant of PSD95, PSD delta 1.2, which concentrates at the postsynaptic site, but cannot bind to postsynaptic proteins, thus minimizing the undesirable effects of PSD-95 overexpression.
    • PSD-95 is rapidly degraded by proteosomes
    • This gives spatial selectivity.
  • They then exploited the dendritic targeting element (DTE) of Arc mRNA which is selectively targeted and translated in activiated dendritic segments in response to synaptic activation in an an NMDA receptor dependent manner.
    • Thereby giving temporal selectivity.
  • Construct is then PSD-PaRac1-DTE; this was tested on hippocampal slice cultures.
  • Improved sparsity and labelling further by driving it with the Arc promoter.
  • Motor learning is impaired in Arc KO mice; hence inferred that the induction of AS-PaRac1 by the Arc promoter would enhance labeling during learning-induced potentiation.
  • Delivered construct via in-utero electroporation.
  • Observed rotarod-induced learning; the PaRac signal decayed after two days, but the spine volume persisted in spines that showed Arc / DTE hence PA labeled activity.
  • Now, since they had a good label, performed rotarod training followed by (at variable delay) light pulses to activate Rac, thereby suppressing recently-active synapses.
    • Observed both a depression of behavioral performance.
    • Controlled with a second task; could selectively impair performance on one of the tasks based on ordering/timing of light activation.
  • The localized probe also allowed them to image the synapse populations active for each task, which were largely non-overlapping.

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ref: -0 tags: carbon capture links date: 10-18-2019 14:20 gmt revision:0 [head]

Carbon capture links:

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ref: -0 tags: Lucy Flavin mononucelotide FAD FMN fluorescent protein reporter date: 10-17-2019 19:54 gmt revision:1 [0] [head]

PMID-25906065 LucY: A Versatile New Fluorescent Reporter Protein

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ref: -2019 tags: meta learning feature reuse deepmind date: 10-06-2019 04:14 gmt revision:1 [0] [head]

Rapid learning or feature reuse? Towards understanding the effectiveness of MAML

  • It's feature re-use!
  • Show this by freezing the weights of a 5-layer convolutional network when training on Mini-imagenet, either 5shot 1 way, or 5shot 5 way.
  • From this derive ANIL, where only the last network layer is updated in task-specific training.
  • Show that ANIL works for basic RL learning tasks.
  • This means that roughly the network does not benefit much from join encoding -- encoding both the task at hand and the feature set. Features can be learned independently from the task (at least these tasks), with little loss.

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ref: -0 tags: ETPA entangled two photon absorption Goodson date: 09-24-2019 02:25 gmt revision:6 [5] [4] [3] [2] [1] [0] [head]

Can we image biological tissue with entangled photons?

How much fluorescence can we expect, based on reasonable concentrations & published ETPA cross sections?

Start with beer's law: A=σLN A = \sigma L N AA = absorbance; LL = sample length, 10 μm, 1e-3 cm; NN = concentration, 10 μmol; σ\sigma = cross-section, for ETPA assume 2.4e18cm 2/molec2.4e-18 cm^2 / molec (this is based on a FMN based fluorophore; actual cross-section may be higher). Including Avogadro's number and 1l=1000cm 31 l = 1000 cm^3 , A=1.45e5A = 1.45e-5

Now, add in quantum efficiency ϕ=0.8\phi = 0.8 (Rhodamine); collection efficiency η=0.2\eta = 0.2 ; and an incoming photon pair flux of I=1e12photons/sec/modeI = 1e12 photons / sec / mode (which roughly about the limit for quantum behavior; n = 0.1 photons / mode; will add this calculation).

F=ϕησLNI=2.3e6photons/secF = \phi \eta \sigma L N I = 2.3e6 photons/sec This is very low, but within practical imaging limits. As a comparison, incoherent 2p imaging creates ~ 100 photons per pulse, of which 10 make it to the detector; for 512 x 512 pixels at 15fps, the dwell time on each pixel is 20 pulses of a 80 MHz Ti:Sapphire laser, or ~ 200 photons.

Note the pair flux is per optical mode; for a typical application, we'll use a Nikon 16x objective with a 600 μm Ø FOV and 0.8 NA. At 800 nm imaging wavelength, the diffraction limit is 0.5 μm. This equates to about 7e57e5 addressable modes in the FOV. Then an illumination of 1e121e12 photons / sec / mode equates to 7e177e17 photons over the whole field; if each photon pair has an energy of 2.75eV,λ=450nm2.75 eV, \lambda = 450 nm , this is equivalent to 300 mW. 100mW is a reasonable limit, hence scale incoming flux to 2.3e172.3e17 pairs /sec.

Hence, the imaging mode is power limited, and not quantum limited (if you could get such a bright entangled source). And right now that's the limit -- for a BBO crystal, circa 1998 experimenters were getting 1e4 photons / sec / mW. So, 2.3e172.3e17 pairs / sec would require 23 GW. Yikes.

More efficient entangled sources have been developed, using periodically-poled potassium titanyl phosphate (PPPTP), which (again assuming linearity) puts the power requirement at 23 MW. This is within the reason of q-switched lasers, but still incredibly inefficient. The down-conversion process is not linear in intensity, which is why Goodson pumps with SHG from a Ti:sapphire to yield ~1e7 photons; but this of induces temporal correlations which increase the frequency of incoherent TPA.

Still, combining PPPTP with a Ti:sapphire laser could result in 1e13 photons / sec, which is sufficient for scanned microscopy. Since the laser is pulsed, it will still be subject to incoherent TPA; but that's OK, the point is to reduce the power going into the animal via larger ETPA cross-section. The answer to above is a tentative yes. Upon the development of brighter entangled sources (e.g. arrays of quantum structures), this can move to fully widefield imaging.

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ref: -0 tags: co2 capture entropy carbon dioxide date: 09-22-2019 00:46 gmt revision:1 [0] [head]

How much energy is thermodynamically required to concentrate CO 2CO_2 from one liter of air?

CO 2CO_2 concentration is 400ppm, or 0.4%. 1l of air is 1/22.4 or 44mMol. From wikipedia, the entropy of mixing is:

Δ mixS=nR(x 1ln(x 1)+x 2ln(x 2)) \Delta_{mix} S = n R (x_1 ln(x_1) + x_2 ln(x_2)) where x 1x_1 and x 2x_2 are the fraction of air and CO 2CO_2 (0.996 and 0.004)

This works out to 9.5e3J/K9.5e-3 J/K . At STP, 300K, this means you need only about 2.9J2.9 J to extract the carbon dioxide.

A car driving 1 km emits about 150g carbon dioxide. This is 3.4 moles, which will diffuse into 852 moles of air, or 19e3 liters of air (19 cubic meters). To pull this back out of the air then you'd need at minimum 55.3 kJ.

This is not much at all -- a car produces 100kW mechanical power, or 100kJ every second, and presumably it takes a minute to drive that 1km. But such perfectly efficient purification is not possible.

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ref: -0 tags: ETPA entangled two photon absorption Goodson date: 09-19-2019 15:49 gmt revision:13 [12] [11] [10] [9] [8] [7] [head]

Various papers put out by the Goodson group:

And from a separate group at Northwestern:

  • Entangled Photon Resonance Energy Transfer in Arbitrary Media
    • Suggests three orders of magnitude improvement in cross-section relative to incoherent TPA.
    • In SPDC, photon pairs are generated randomly and usually accompanied by undesirable multipair emissions.
      • For solid-state artificial atomic systems with radiative cascades (singled quantum emitters like quantum dots), the quantum efficiency is near unity.
    • Paper is highly mathematical, and deals with resonance energy transfer (which is still interesting)

Regarding high fluence sources, quantum dots / quantum structures seem promising.

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ref: -0 tags: betzig lattice light sheet date: 09-18-2019 18:32 gmt revision:0 [head]

PMID-25342811 Lattice Light Sheet Microscopy: Imaging Molecules to Embryos at High Spatiotemporal Resolution

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ref: -2013 tags: 2p two photon STED super resolution microscope date: 09-18-2019 02:22 gmt revision:0 [head]

PMID-23442956 Two-Photon Excitation STED Microscopy in Two Colors in Acute Brain Slices

  • Plenty of details on how they set up the microscope.

PMID-29932052 Chronic 2P-STED imaging reveals high turnover of spines in the hippocampus in vivo

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ref: -2012 tags: cortex striatum learning carmena costa basal ganglia date: 09-13-2019 18:30 gmt revision:6 [5] [4] [3] [2] [1] [0] [head]

PMID-22388818 Corticostriatal plasticity is necessary for learning intentional neuroprosthetic skills.

  • Trained a mouse to control an auditory cursor, as in Kipke's task {99}. Did not cite that paper, claimed it was 'novel'. oops.
  • Summed neuronal firing rate of groups of 2 or 4 M1 neurons.
  • Auditory feedback was essential for the operant learning.
    • One group increased the frequency with increased firing rate; the other decreased tone with increasing FR.
  • Specific deletion of striatal NMDA receptors impairs the ability to learn neuroprosthetic skills.
    • Hence, they argue, cortico-striatal plastciity is required to learn abstract skills, such as this tone to firing rate target acquisition task.
  • Controlled by recording EMG of the vibrissae + injection of lidocane into the whisker pad.
  • One reward was sucrose solution; the other was a food pellet. When the rat was satiated on one modality, they showed increased preference for the opposite reward during BMI control -- thereby demonstrating intentionality. Clever!.
  • Noticed pronounced oscillatory spike coupling, the coherence of which was increased in low-frequency bands in late learning relative to early learning (figure 3).
  • Genetic manipulations: knockin line that expresses Cre recombinase in both striatonigral and striatopallidal medium spiny neurons, crossed with mice carrying a floxed allele of the NMDAR1 gene.
    • These animals are relatively normal, and can learn to perform rapid sequential movements, but are unable to learn precise motor sequences.
    • Acute pharmacological blockade of NMDAR did not affect performance of the neuroprosthetic skill.
    • Hence the deficits in the transgenic mice are due to an inability to perform the skill.

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ref: Gage-2005.06 tags: naive coadaptive control Kalman filter Kipke audio BMI date: 09-13-2019 02:33 gmt revision:2 [1] [0] [head]

PMID-15928412[0] Naive coadaptive Control May 2005. see notes

____References____

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ref: Jackson-2007.01 tags: Fetz neurochip sleep motor control BMI free behavior EMG date: 09-13-2019 02:21 gmt revision:4 [3] [2] [1] [0] [head]

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

  • used their implanted "neurochip" recorder that recorded both EMG and neural activity. The neurochip buffers data and transmits via IR offline. It doesn't have all that much flash onboard - 16Mb.
    • used teflon-insulated 50um tungsten wires.
  • confirmed that there is a strong causal relationship, constant over the course of weeks, between motor cortex units and EMG activity.
    • some causal relationships between neural firing and EMG varied dependent on the task. Additive / multiplicative encoding?
  • this relationship was different at night, during REM sleep, though (?)
  • point out, as Todorov did, that Stereotyped motion imposes correlation between movement parameters, which could lead to spurrious relationships being mistaken for neural coding.
    • Experiments with naturalistic movement are essential for understanding innate, untrained neural control.
  • references {597} Suner et al 2005 as a previous study of long term cortical recordings. (utah probe)
  • during sleep, M1 cells exhibited a cyclical patter on quiescence followed by periods of elevated activity;
    • the cycle lasted 40-60 minutes;
    • EMG activity was seen at entrance and exit to the elevated activity period.
    • during periods of highest cortical activity, muscle activity was completely suppressed.
    • peak firing rates were above 100hz! (mean: 12-16hz).

____References____

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ref: -2019 tags: Kleinfeld Harris record every neuron date: 09-13-2019 01:51 gmt revision:0 [head]

PMID-31495645 Can One Concurrently Record Electrical Spikes from Every Neuron in a Mammalian Brain?

  • Argues for a concrete arrangement of 6um diamond (1.2TPa modulus) shanks, 2mm long, on 40um hexagonal grid. Each would be patterned with 5 layers of metal, 30nm x 30nm Au traces (what about surface roughness?), high dielectric insulation, 9um x 14um TiN contacts.
  • This will be mated to state of the art adaptive amplifiers, which would be biased to only burn necessary power needed to sort spikes.
  • The sharpened spikes should penetrate the brain; 4um diameter diamond shanks should also work...
  • Overall volume displacement ~ 2% (which still seems high).
  • Suggest that the shanks can push capillaries out of the way, or puncture them while making a seal. Clearly, that's possible ...
  • ... but realistically, unless these are inserted glacially slowly, it will cause possibly catastrophic / cascading inflammation. (Which can spread on the order of 100-150um).
  • Does not cite Marblestone 2013.

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ref: -0 tags: swept field confocal date: 09-12-2019 20:01 gmt revision:1 [0] [head]

PMID-22831554 Swept field laser confocal microscopy for enhanced spatial and temporal resolution in live-cell imaging.

  • Invented by Marvin Minsky back in 1955 memoir!
  • Idea is not unlike light-sheet imaging -- sweep a confocal slit and laser line across a sample, rather than a pinhole and point, respectively.
  • This results in lower phototoxicity, but still reasonable rejection of out-of-focus light compared to widefield imaging.

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ref: -2017 tags: two photon holographic imaging Arch optogenetics GCaMP6 date: 09-12-2019 19:24 gmt revision:1 [0] [head]

PMID-28053310 Simultaneous high-speed imaging and optogenetic inhibition in the intact mouse brain.

  • Bovetti S1, Moretti C1, Zucca S1, Dal Maschio M1, Bonifazi P2,3, Fellin T1.
  • Image GCamp6 in either scanned mode (high resolution, slow) or holographically (SLM, redshirt 80x80 NeuroCCD, activate opsin Arch, simultaneously record juxtasomal action potentials.

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ref: -2007 tags: photobleaching GFP date: 09-10-2019 01:42 gmt revision:1 [0] [head]

PMID-17179937 Major signal increase in fluorescence microscopy through dark-state relaxation (2007)

  • 5-25x increase in fluorescence yields.
  • Idea: allow the (dark) triplet states to decay naturally by keeping inter-pulse intervals of illumination greater than 1us.
  • Works for both 1p and 2p.
  • For volume imaging via 2p, I don’t think that 1um decay time is much of an issue; revisit given fluorophores after >1ms!
  • Suggests again that transition from triplet dark state to excited higher state is a prominent or significant cause of photobleaching; also suggests that triple quenching will have limited utility in scanned or pulsed 2p systems (will have more utility in 1p systems, perhaps..)
  • Atto532 dye has low intersystem crossing to the triplet state (1%) [3,5,14] .. humm.
  • 2p total photon emission seems to flatten above 100GW/cm^2 intensity.
  • 2p absorption is easily saturated independent of pulse width: for short pulses, high intensity leads to absorption to T1 state, which has high cross-section to the Tn>1 state; longer pulses give more time for single-photon absorption.
  • τp by m = 200 and hence the pulse energy by 14-fold does not have a considerable effect on G2p. This obviously indicates that the saturation of the S0 → S1 or of the T1 → Tn > 1 excitation eliminates any dependence on pulse peak intensity or energy.

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ref: -0 tags: computational neuroscience opinion tony zador konrad kording lillicrap date: 07-30-2019 21:04 gmt revision:0 [head]

Two papers out recently in Arxive and Biorxiv:

  • A critique of pure learning: what artificial neural networks can learn from animal brains
    • Animals learn rapidly and robustly, without the need for labeled sensory data, largely through innate mechanisms as arrived at and encoded genetically through evolution.
    • Still, this cannot account for the connectivity of the human brain, which is much to large for the genome; with us, there are cannonical circuits and patterns of intra-area connectivity which act as the 'innate' learning biases.
    • Mice and men are not so far apart evolutionary. (I've heard this also from people FIB-SEM imaging cortex) Hence, understanding one should appreciably lead us to understand the other. (I agree with this sentiment, but for the fact that lab mice are dumb, and have pretty stereotyped behaviors).
    • References Long short term memory and learning to learn in networks of spiking neurons -- which claims that a hybrid algorithm (BPTT with neuronal rewiring) with realistic neuronal dynamics markedly increases the computational power of spiking neural networks.
  • What does it mean to understand a neural network?
    • As has been the intuition with a lot of neuroscientists probably for a long time, posits that we have to investigate the developmental rules (wiring and connectivity, same as above) plus the local-ish learning rules (synaptic, dendritic, other .. astrocytic).
      • The weights themselves, in either biological neural networks, or in ANN's, are not at all informative! (Duh).
    • Emphasizes the concept of compressability: how much information can be discarded without impacting performance? With some modern ANN's, 30-50x compression is possible. Authors here argue that little compression is possible in the human brain -- the wealth of all those details about the world are needed! In other words, no compact description is possible.
    • Hence, you need to learn how the network learns those details, and how it's structured so that important things are learned rapidly and robustly, as seen in animals (very similar to above).