You are not authenticated, login.
text: sort by
tags: modified
type: chronology
[0] Rektor I, Kaiiovský P, Bares M, Brázdil M, Streitová H, Klajblová H, Kuba R, Daniel P, A SEEG study of ERP in motor and premotor cortices and in the basal ganglia.Clin Neurophysiol 114:3, 463-71 (2003 Mar)

[0] Is this the bionic man?Nature 442:7099, 109 (2006 Jul 13)[1] Hochberg LR, Serruya MD, Friehs GM, Mukand JA, Saleh M, Caplan AH, Branner A, Chen D, Penn RD, Donoghue JP, Neuronal ensemble control of prosthetic devices by a human with tetraplegia.Nature 442:7099, 164-71 (2006 Jul 13)[2] Santhanam G, Ryu SI, Yu BM, Afshar A, Shenoy KV, A high-performance brain-computer interface.Nature 442:7099, 195-8 (2006 Jul 13)[3] Shenoy KV, Meeker D, Cao S, Kureshi SA, Pesaran B, Buneo CA, Batista AP, Mitra PP, Burdick JW, Andersen RA, Neural prosthetic control signals from plan activity.Neuroreport 14:4, 591-6 (2003 Mar 24)

[0] Vyssotski AL, Serkov AN, Itskov PM, Dell'Omo G, Latanov AV, Wolfer DP, Lipp HP, Miniature neurologgers for flying pigeons: multichannel EEG and action and field potentials in combination with GPS recording.J Neurophysiol 95:2, 1263-73 (2006 Feb)[1] Otto KJ, Johnson MD, Kipke DR, Voltage pulses change neural interface properties and improve unit recordings with chronically implanted microelectrodes.IEEE Trans Biomed Eng 53:2, 333-40 (2006 Feb)

hide / / print
ref: Schalk-2000.12 tags: error potential EEG wadsworth BCI 2000 BMI date: 01-23-2013 07:15 gmt revision:3 [2] [1] [0] [head]

PMID-11090763[0] EEG-based communication: presence of an error potential.

  • Idea: they trained a set of subjects to use mu/beta rhythm over central sulcus (sensorimotor) amplitude to move a cursor around the screen, and simultaneously monitored for error-related potentials to correct errors in decoding.
  • patients get 80-97% accuracy in a binary choice task.
  • look at the end of a trial to see if they 'approve' of the choice.
  • had to remove eyeblink artifacts! however, people tend to defer eyeblinks until the end of performance.
  • error = average EEG during error trials - EEG during correct trial. (a potential)
    • the error was over primary motor/ somatosensory cortex.
    • used adaptive noise cancellation to remove some of the eyeblink EMG.


[0] Schalk G, Wolpaw JR, McFarland DJ, Pfurtscheller G, EEG-based communication: presence of an error potential.Clin Neurophysiol 111:12, 2138-44 (2000 Dec)

hide / / print
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 [0] [head]

PMID-19564605[0] Cognitive fitness of cost-efficient brain functional networks.

  • Idea: smaller, tighter networks are correlated with better task performance
    • working memory task in normal subjects and schizophrenics.
  • Larger networks operate with higher beta frequencies (more effort?) and show less efficient task performance.
  • Not sure about the noisy data, but v. interesting theory!


[0] Bassett DS, Bullmore ET, Meyer-Lindenberg A, Apud JA, Weinberger DR, Coppola R, Cognitive fitness of cost-efficient brain functional networks.Proc Natl Acad Sci U S A 106:28, 11747-52 (2009 Jul 14)

hide / / print
ref: Rektor-2003.03 tags: ERP basal ganglia P300 EEG date: 09-25-2008 02:35 gmt revision:2 [1] [0] [head]

PMID-12705427[0] A SEEG study of ERP in motor and premotor cortices and in the basal ganglia.

  • SEEG = stereo (algorithmically (not electrically) differential) EEG.
  • Used depth electrodes in epilepsy patients.
  • targeted M1, SMA & premotor cortices as well as the basal ganglia.
  • ERP larger and more frequent in the basal ganglia, with no difference in the latency between the ERP in the cortex and in the basal ganglia.
  • ERP were in response to visual and auditory 'oddball' tasks
    • Patients had to detect the less usual tone or visual object & count it; sometimes detection involved pressing a button.


hide / / print
ref: bookmark-2006.07 tags: BMI BCI EEG bibliography Stephan Scott date: 09-07-2008 19:54 gmt revision:2 [1] [0] [head]



hide / / print
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]

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 (“neurologger”), 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]


hide / / print
ref: bookmark-0 tags: eeg oss openeeg recording linux date: 0-0-2007 0:0 revision:0 [head]


hide / / print
ref: Blankertz-2006.06 tags: BMI EEG ECoG competiton 2006 date: 0-0-2007 0:0 revision:0 [head]

PMID-16792282 http://hardm.ath.cx:88/pdf/BCIcompetition2006.pdf

hide / / print
ref: Parra-2003.06 tags: BMI BCI EEG error correction ERN date: 0-0-2007 0:0 revision:0 [head]

PMID-12899266 Response error correction-a demonstration of improved human-machine performance using real-time EEG monitoring

  • the goal of an adaptive interface is to estimate variables correlated to human performance and adapt the HCI (human computer interface) = BCI accordingly.
    • use specific observable states to judge the subject's cognitive state, and use this information to adapt the BCI & maximize performance.
  • percieved errors are associated with a negative fronto-central deflection in the EEG signal = ERN, error-related negativity.
  • they can detect the ERN using a linear classifier within 100ms on a single-trial basis.
  • also have to remove eyeblink.

hide / / print
ref: Blankertz-2003.06 tags: BMI BCI EEG error classification motor commands Blankertz date: 0-0-2007 0:0 revision:0 [head]

PMID-12899253 Boosting bit rates and error detection for the classification of fast-paced motor commands based on single-trial EEG analysis

  • want to minimize subject training and maximize the major learning load on the computer.
  • task: predict the laterality of imminent left-right hand finger movements in a natural keyboard typing condition. they got ~15bits/minute (in one subject, ~50bits per minute!)
    • used non-oscilatory signals.
  • did a to detect 85% percent of error trials, and limited false-positives to ~2%

hide / / print
ref: Vidal-2000.01 tags: EEG ERN error negativity conflict resolution 2000 date: 0-0-2007 0:0 revision:0 [head]

PMID-10686362 Is the 'error negativity' specific to errors?

  • they see a small ERN on correct trials, focused @ FCz.
  • rather than an error-process per se, we propose that the ERN reflects either a comparison process leading secondarily to error detection, or an emotional reaction.