Self-recalibrating classifiers for intracortical brain-computer interfaces

Journal of Neural Engineering

Volumn 11, Issue 2, 2014, Pages

  Bishop, William ^a,b   Chestek, Cynthia C ^c,d,e   Gilja, Vikash ^c,d   Nuyujukian, Paul ^c,f   Foster, Justin D ^c   Ryu, Stephen I ^c,g   Shenoy, Krishna V ^c,d   Yu, Byron M ^b,h  

^a Department of Machine Learning Carnegie Mellon University ^*  (United States)

^b CARNEGIE MELLON UNIVERSITY   (United States)

^c Stanford University   (United States)

^d STANFORD UNIVERSITY   (United States)

^e UNIVERSITY OF MICHIGAN   (United States)

^f STANFORD UNIVERSITY SCHOOL OF MEDICINE   (United States)

^g PALO ALTO MEDICAL FOUNDATION   (United States)

^h CARNEGIE MELLON UNIVERSITY   (United States)

Author keywords

brain computer interface; classification; stable decoding

Indexed keywords

CLASSIFICATION (OF INFORMATION); DECODING; INTERFACES (COMPUTER);

CLASSIFICATION ACCURACY; CLINICAL TRANSLATION; CONTINUOUS CONTROL; MOTOR CORTEX; OFF-LINE ANALYSIS; STABLE PERFORMANCE; THRESHOLD-CROSSING; TUNING PARAMETER;

BRAIN COMPUTER INTERFACE;

ACCURACY; ACTION POTENTIAL; ADULT; ANIMAL EXPERIMENT; ARTICLE; BEHAVIOR CHANGE; BRAIN COMPUTER INTERFACE; CALIBRATION; CLASSIFIER; CONTROLLED STUDY; CORTICAL ELECTRODE; LEARNING; MALE; MOTOR CORTEX; MOVEMENT (PHYSIOLOGY); NONHUMAN; PRIORITY JOURNAL; RHESUS MONKEY; SELF RECALIBRATING CLASSIFIER; TASK PERFORMANCE; ANIMAL; CLASSIFICATION; ELECTRODE IMPLANT; MICROELECTRODE; PHOTOSTIMULATION; PHYSIOLOGY; PROCEDURES; PSYCHOMOTOR PERFORMANCE;

ACTION POTENTIALS; ANIMALS; BRAIN-COMPUTER INTERFACES; CALIBRATION; ELECTRODES, IMPLANTED; MACACA MULATTA; MALE; MICROELECTRODES; MOTOR CORTEX; PHOTIC STIMULATION; PSYCHOMOTOR PERFORMANCE;

EID: 84897558015     PISSN: 17412560     EISSN: 17412552     Source Type: Journal    
DOI: 10.1088/1741-2560/11/2/026001     Document Type: Article

References (54)

1. Achtman N, Afshar A, Santhanam G, Byron M Y, Ryu S I and Shenoy K V 2007 Free-paced high-performance brain-computer interfaces J. Neural Eng. 4 336-47
2. Aggarwal V, Acharya S, Tenore F, Shin H-C, Etienne-Cummings R, Schieber M H and Thakor N V 2008 Asynchronous decoding of dexterous finger movements using M1 neurons IEEE Trans. Neural Syst. Rehabil. Eng. 16 3-14
3. Blom H and Bar-Shalom Y 1988 The interacting multiple model algorithm for systems with Markovian switching coefficients IEEE Trans. Autom. Control 33 780-3
4. Blumberg J, Rickert J, Waldert S, Schulze-Bonhage A, Aertsen A and Mehring C 2007 Adaptive classification for brain computer interfaces Proc. 29th Annual Int. Conf. IEEE EMBS (Lyon, France,) pp 2536-9
5. Brunner P, Ritaccio A, Emrich J, Bischof H and Schalk G 2011 Rapid communication with a 'p300' matrix speller using electrocorticographic signals (ecog) Front. Neurosci. 5 5
6. Chase S M, Kass R E and Schwartz A B 2012 Behavioral and neural correlates of visuomotor adaptation observed through a brain-computer interface in primary motor cortex J. Neurophysiol. 108 624-44
7. Chase S M, Schwartz A B and Kass R E 2009 Bias, optimal linear estimation, and the differences between open-loop simulation and closed-loop performance of spiking-based brain-computer interface algorithms Neural Netw. 22 1203-13
8. Chestek C, Batista A, Santhanam G, Yu B, Afshar A, Cunningham J, Gilja V, Ryu S, Churchland M and Shenoy K 2007 Single-neuron stability during repeated reaching in macaque premotor cortex J. Neurosci. 27 10742-50
9. Chestek C et al 2011 Long-term stability of neural prosthetic control signals from silicon cortical arrays in rhesus macaque motor cortex J. Neural Eng. 8 045005
10. Chestek C A, Cunningham J P, Gilja V, Nuyujukian P, Ryu S I and Shenoy K V 2009 Neural prosthetic systems: current problems and future directions Proc. 31st Annual Int. Conf. IEEE EMBS (Minneapolis, MN,) pp 3369-75
11. Chestek C A, Gilja V, Blabe C H, Foster B L, Shenoy K V, Parvizi J and Henderson J M 2013 Hand posture classification using electrocorticography signals in the gamma band over human sensorimotor brain areas J. Neural Eng. 10 026002
12. Collinger J L, Wodlinger B, Downey J E, Wang W, Tyler-Kabara E C, Weber D J, McMorland A J, Velliste M, Boninger M L and Schwartz A B 2012 High-performance neuroprosthetic control by an individual with tetraplegia Lancet 381 557-64
13. Dempster A P, Laird N M and Rubin D B 1977 Maximum likelihood from incomplete data via the em algorithm J. R. Stat. Soc. B 39 1-38
14. Eden U, Truccolo W, Fellows M, Donoghue J and Brown E 2004a Reconstruction of hand movement trajectories from a dynamic ensemble of spiking motor cortical neurons Proc. 26th Annual Int. Conf. IEEE EMBS (San Francisco, CA,) pp 4017-20
15. Eden U T, Frank L M, Barbieri R, Solo V and Brown E N 2004b Dynamic analysis of neural encoding by point process adaptive filtering Neural Comput. 16 971-98
16. Flint R D, Wright Z A, Scheid M R and Slutzky M W 2013 Long term, stable brain machine interface performance using local field potentials and multiunit spikes J. Neural Eng. 10 056005
17. Fraser G, Chase S, Whitford A and Schwartz A 2009 Control of a brain-computer interface without spike sorting J. Neural Eng. 6 055004
18. Galán F, Nuttin M, Lew E, Ferrez P W, Vanacker G, Philips J and Millán J d R 2008 A brain-actuated wheelchair: asynchronous and non-invasive brain-computer interfaces for continuous control of robots Clin. Neurophysiol. 119 2159-69
19. Ganguly K and Carmena J M 2009 Emergence of a stable cortical map for neuroprosthetic control PLoS Biol. 7 e1000153
20. Georgopoulos A P, Kettner R E and Schwartz A B 1988 Primate motor cortex and free arm movements to visual targets in three-dimensional space: ii. Coding of the direction of movement by a neuronal population J. Neurosci. 8 2928-37
21. Georgopoulos A P et al 1986 Neuronal population coding of movement direction Science 233 1416-9
22. Gilja V et al 2012 A high-performance neural prosthesis enabled by control algorithm design Nature Neurosci. 15 1752-7
23. Hochberg L et al 2012 Reach and grasp by people with tetraplegia using a neurally controlled robotic arm Nature 485 372-5
24. Jarosiewicz B, Chase S M, Fraser G W, Velliste M, Kass R E and Schwartz A B 2008 Functional network reorganization during learning in a brain-computer interface paradigm Proc. Natl Acad. Sci. 105 19486-91
25. Kemere C, Santhanam G, Yu B M, Afshar A, Ryu S, Meng T and Shenoy K 2008 Detecting neural-state transitions using hidden Markov models for motor cortical prostheses J. Neurophysiol. 100 2441-52
26. Leeb R, Friedman D, Müller-Putz G, Scherer R, Slater M and Pfurtscheller G 2007 Self-paced (asynchronous) bci control of a wheelchair in virtual environments: a case study with a tetraplegic Comput. Intell. Neurosci. 2007 79642
27. Li Z, O'Doherty J E, Hanson T L, Lebedev M A, Henriquez C S and Nicolelis M A 2009 Unscented Kalman filter for brain-machine interfaces PLoS One 4 e6243
28. Li Z, O'Doherty J, Lebedev M and Nicolelis M 2011 Adaptive decoding for brain-machine interfaces through Bayesian parameter updates Neural Comput. 23 3162-204
29. Maynard E, Hatsopoulos N, Ojakangas C, Acuna B, Sanes J, Normann R and Donoghue J 1999 Neuronal interactions improve cortical population coding of movement direction J. Neurosci. 19 8083-93
30. Musallam S, Corneil B, Greger B, Scherberger H and Andersen R 2004 Cognitive control signals for neural prosthetics Science 305 258-62
31. Ohnishi K, Weir R and Kuiken T 2007 Neural machine interfaces for controlling multifunctional powered upper-limb prostheses Expert Rev. Med. Devices 4 43-53
32. Pascual J, Vidaurre C and Kawanabe M 2011 Investigating eeg non-stationarities with robust pca and its application to improve BCI performance Int. J. Bioelectromagnetism 13 50-51
33. Perge J A, Homer M L, Malik W Q, Cash S, Eskandar E, Friehs G, Donoghue J P and Hochberg L R 2013 Intra-day signal instabilities affect decoding performance in an intracortical neural interface system J. Neural Eng. 10 036004
34. Pistohl T, Schulze-Bonhage A, Aertsen A, Mehring C and Ball T 2012 Decoding natural grasp types from human ecog Neuroimage 59 248-60
35. Polikov V, Tresco P and Reichert W 2005 Response of brain tissue to chronically implanted neural electrodes J. Neurosci. Methods 148 1-18
36. Santhanam G, Linderman M, Gilja V, Afshar A, Ryu S, Meng T and Shenoy K 2007 HermesB: a continuous neural recording system for freely behaving primates IEEE Trans. Biomed. Eng. 54 2037-50
37. Santhanam G, Ryu S I, Yu B M, Afshar A and Shenoy K V 2006 A high-performance brain-computer interface Nature 442 195-8
38. Santhanam G, Yu B, Gilja V, Ryu S, Afshar A, Sahani M and Shenoy K 2009 Factor-analysis methods for higher-performance neural prostheses J. Neurophysiol. 102 1315-30
39. Scherer R, Muller G, Neuper C, Graimann B and Pfurtscheller G 2004 An asynchronously controlled eeg-based virtual keyboard: improvement of the spelling rate IEEE Trans. Biomed. Eng. 51 979-84
40. Shanechi M M, Hu R C, Powers M, Wornell G W, Brown E N and Williams Z M 2012 Neural population partitioning and a concurrent brain-machine interface for sequential motor function Nature Neurosci. 15 1715-22
41. Shenoy K V, Meeker D, Cao S, Kureshi S A, Pesaran B, Buneo C A, Batista A P, Mitra P P, Burdick J W and Andersen R A 2003 Neural prosthetic control signals from plan activity Neuroreport 14 591-6
42. Shenoy P, Krauledat M, Blankertz B, Rao R and Müller K 2006 Towards adaptive classification for BCI J. Neural Eng. 3 R13-23
43. Srinivasan L, Eden U, Mitter S and Brown E 2007 General-purpose filter design for neural prosthetic devices J. Neurophysiol. 98 2456-75
44. Sykacek P and Roberts S 2003 Adaptive classification by variational Kalman filtering Advances in Neural Information Processing Systems (NIPS) vol 15 ed S Thrun, S Becker and K Obermayer (Cambridge, MA: MIT Press) pp 737-44
45. Sykacek P, Roberts S and Stokes M 2004 Adaptive BCI based on variational Bayesian Kalman filtering: an empirical evaluation IEEE Trans. Biomed. Eng. 51 719-27
46. Taylor D M, Tillery S I H and Schwartz A B 2002 Direct cortical control of 3d neuroprosthetic devices Science 296 1829-32
47. Vaughan T M, McFarland D J, Schalk G, Sarnacki W A, Krusienski D J, Sellers E W and Wolpaw J R 2006 The wadsworth BCI research and development program: at home with BCI IEEE Trans. Neural Syst. Rehabil. Eng. 14 229-33
48. Velliste M, Perel S, Spalding M C, Whitford A S and Schwartz A B 2008 Cortical control of a prosthetic arm for self-feeding Nature 453 1098-101
49. Vidaurre C and Blankertz B 2010 Towards a cure for BCI illiteracy Brain Topography 23 194-8
50. Vidaurre C, Schlögl A, Blankertz B, Kawanabe M and Müller K 2008 Unsupervised adaptation of the lda classifier for brain-computer interfaces Proc. 4th Int. Brain-Computer Interface Workshop and Training Course (Graz, Austria,) vol 2008 pp 122-7
51. Wang W et al 2009 Human motor cortical activity recorded with micro-ecog electrodes, during individual finger movements Proc. 31st Annual Int. Conf. IEEE EMBS (Minneapolis, MN,) pp 586-9
52. Wang Z, Gunduz A, Brunner P, Ritaccio A, Ji Q and Schalk G 2012 Decoding onset and direction of movements using electrocorticographic (ecog) signals in humans Front. Neuroeng. 5 15
53. Wu W, Gao Y, Bienenstock E, Donoghue J P and Black M J 2006 Bayesian population decoding of motor cortical activity using a Kalman filter Neural Comput. 18 80-118
54. Wu W and Hatsopoulos N 2008 Real-time decoding of nonstationary neural activity in motor cortex IEEE Trans. Neural Syst. Rehabil. Eng. 16 213-22