Subject-specific modulation of local field potential spectral power during brain-machine interface control in primates

Journal of Neural Engineering

Volumn 11, Issue 2, 2014, Pages

  So, Kelvin ^a   Dangi, Siddharth ^a   Orsborn, Amy L ^b   Gastpar, Michael C ^a,c   Carmena, Jose M ^a,b,d  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b University of California   (United States)

^c EPFL   (Switzerland)

^d UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

brain machine interfaces (BMI); local field potential (LFP); primate

Indexed keywords

BRAIN; ELECTROPHYSIOLOGY; FREQUENCY BANDS; MAMMALS; MODULATION;

BRAIN MACHINE INTERFACE; BRAIN MACHINE INTERFACE (BMIS); DIFFERENT FREQUENCY; HIGHER FREQUENCIES; HIGHLY-CORRELATED; LOCAL FIELD POTENTIALS; LOW-FREQUENCY SPECTRA; PRIMATE;

CLOSED LOOP CONTROL SYSTEMS;

ADULT; ANIMAL EXPERIMENT; ARTICLE; BRAIN COMPUTER INTERFACE; BRAIN ELECTROPHYSIOLOGY; CONTROL STRATEGY; CONTROLLED STUDY; FREQUENCY MODULATION; LOCAL FIELD POTENTIAL; MALE; NONHUMAN; PRIORITY JOURNAL; RHESUS MONKEY; SIGNAL DETECTION; SPECTROSCOPY; TASK PERFORMANCE; ACTION POTENTIAL; ANIMAL; MICROELECTRODE; MOTOR CORTEX; PHOTOSTIMULATION; PHYSIOLOGY; PRIMATE; PROCEDURES; PSYCHOMOTOR PERFORMANCE; RANDOMIZATION;

ACTION POTENTIALS; ANIMALS; BRAIN-COMPUTER INTERFACES; MACACA MULATTA; MALE; MICROELECTRODES; MOTOR CORTEX; PHOTIC STIMULATION; PRIMATES; PSYCHOMOTOR PERFORMANCE; RANDOM ALLOCATION;

EID: 84897515344     PISSN: 17412560     EISSN: 17412552     Source Type: Journal    
DOI: 10.1088/1741-2560/11/2/026002     Document Type: Article

References (38)

1. Green A M and Kalaska J F 2011 Learning to move machines with the mind Trends Neurosci. 34 61-75
2. Fetz E E 2007 Volitional control of neural activity: implications for brain-computer interfaces J. Physiol. 579 571-9
3. Rickert J, de Oliveira S C, Vaadia E, Aertsen A, Rotter S and Mehring C 2005 Encoding of movement direction in different frequency ranges of motor cortical local field potentials J. Neurosci. 25 8815-24
4. Sanes J N and Donoghue J P 1993 Oscillations in local field potentials of the primate motor cortex during voluntary movement Proc. Natl Acad. Sci. USA 90 4470-4
5. Bansal A K, Vargas-Irwin C E, Truccolo W and Donoghue J P 2011 Relationships among low-frequency local field potentials, spiking activity, and three-dimensional reach and grasp kinematics in primary motor and ventral premotor cortices J. Neurophysiol. 105 1603-19
6. Markowitz D A, Wong Y T, Gray C M and Pesaran B 2011 Optimizing the decoding of movement goals from local field potentials in macaque cortex J. Neurosci. 31 18412-22
7. Flint R D, Ethier C, Oby E R, Miller L E and Slutzky M W 2012 Local field potentials allow accurate decoding of muscle activity J. Neurophysiol. 108 18-24
8. Flint R D, Lindberg E W, Jordan L R, Miller L E and Slutzky M W 2012 Accurate decoding of reaching movements from field potentials in the absence of spikes J. Neural Eng. 9 046006
9. Hwang E J and Andersen R A 2009 Brain control of movement execution onset using local field potentials in posterior parietal cortex J. Neurosci. 29 14363-70
10. Engelhard B, Ozeri N, Israel Z, Bergman H and Vaadia E 2013 Inducing gamma oscillations and precise spike synchrony by operant conditioning via brain-machine interface Neuron 77 361-75
11. 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
12. Schalk G, Kubánek J, Miller K J, Anderson N R, Leuthardt E C, Ojemann J G, Limbrick D, Moran D, Gerhardt L A and Wolpaw J R 2007 Decoding two-dimensional movement trajectories using electrocorticographic signals in humans J. Neural Eng. 4 264
13. Flint R, Wright Z and Slutzky M 2012 Control of a biomimetic brain-machine interface with local field potentials: performance and stability of a static decoder over 200 days EMBC: Annual Int. Conf. of the IEEE Engineering in Medicine and Biology Society pp 6719-22
14. Dangi S, Orsborn A L, Moorman H G and Carmena J M 2013 Design and analysis of closed-loop decoder adaptation algorithms for brain-machine interfaces Neural Comput. 25 1693-731
15. Haykin S S 2002 Adaptive Filter Theory 5th edn (Englewood Cliffs, NJ: Prentice Hall) ISBN 978-0132671453
16. Wu W, Black M J, Gao Y, Bienenstock E, Serruya M, Shaikhouni A and Donoghue J P 2003 Neural decoding of cursor motion using a Kalman filter Advances in Neural Information Processing Systems 15 (Cambridge, MA: MIT Press) pp 133-40
17. Gilja V et al 2012 A high-performance neural prosthesis enabled by control algorithm design Nature Neurosci. 15 1752-7
18. Wang W et al 2013 An electrocorticographic brain interface in an individual with tetraplegia PloS one 8 e55344
19. Taylor D M, Tillery S I H and Schwartz A B 2002 Direct cortical control of 3D neuroprosthetic devices Science 296 1829-32
20. Gage G J, Ludwig K A, Otto K J, Ionides E L and Kipke D R 2005 Naive coadaptive cortical control J. Neural Eng. 2 52-63
21. Shpigelman L, Lalazar H and Vaadia E 2008 Kernel-ARMA for hand tracking and brain-machine interfacing during 3D motor control Proc. Neural Information Processing System pp 1489-96
22. Heliot R, Venkatraman S and Carmena J M 2010 Decoder remapping to counteract neuron loss in brain-machine interfaces EMBC: Annual Int. Conf. of the IEEE Engineering in Medicine and Biology Society pp 1670-3
23. Mahmoudi B and Sanchez J C 2011 A symbiotic brain-machine interface through value-based decision making PloS one 6 e14760
24. Li Z, O'Doherty J E, Lebedev M A and Nicolelis M A L 2011 Adaptive decoding for brain-machine interfaces through bayesian parameter updates Neural Comput. 23 3162-204
25. Dangi S, Gowda S, Heliot R and Carmena J 2011 Adaptive kalman filtering for closed-loop brain-machine interface systems NER: IEEE/EMBS Conf. on Neural Engineering pp 609-12
26. Orsborn A L, Dangi S, Moorman H G and Carmena J M 2012 Closed-loop decoder adaptation on intermediate time-scales facilitates rapid BMI performance improvements independent of decoder initialization conditions IEEE Trans. Neural Syst. Rehabil. Eng. A 20 468-77
27. Hochberg L R et al 2012 Reach and grasp by people with tetraplegia using a neurally controlled robotic arm Nature 485 372-5
28. Donoghue J P, Simeral J D, Kim S P, Friehs G M, Hochberg L R and Black M J 2007 Toward standardized assessment of pointing devices for brain-computer interfaces Program No. 517.16 (San Diego, CA: Society for Neuroscience)
29. Rouse A G, Williams J J, Wheeler J J and Moran D W 2013 Cortical adaptation to a chronic micro-electrocorticographic brain-computer interface J. Neurosci. 33 1326-30
30. Wander J D, Blakely T, Miller K J, Weaver K E, Johnson L A, Olson J D, Fetz E E, Rao R P N and Ojemann J G 2013 Distributed cortical adaptation during learning of a brain-computer interface task Proc. Natl Acad. Sci. USA 110 10818-23
31. Kajikawa Y and Schroeder C E 2011 How local is the local field potential? Neuron 72 847-58
32. Crone N E, Miglioretti D L, Gordon B, Sieracki J M, Wilson M T, Uematsu S and Lesser R P 1998 Functional mapping of human sensorimotor cortex with electrocorticographic spectral analysis: I. Alpha and beta event-related desynchronization Brain 121 2271-99
33. Fitts P M 1954 The information capacity of the human motor system in controlling the amplitude of movement J. Exp. Psychol. 47 381-91
34. MacKenzie I S 1989 A note on the information-theoretic basis of Fitts' law J. Motor Behav. 21 323-30
35. Kim S P, Simeral J D, Hochberg L R, Donoghue J P and Black M J 2008 Neural control of computer cursor velocity by decoding motor cortical spiking activity in humans with tetraplegia J. Neural Eng. 5 455
36. Ganguly K and Carmena J M 2009 Emergence of a stable cortical map for neuroprosthetic control PLoS Biol. 7 e1000153
37. Schalk G, Miller K J, Anderson N R, Wilson J A, Smyth M D, Ojemann J G, Moran D W, Wolpaw J R and Leuthardt E C 2008 Two-dimensional movement control using electrocorticographic signals in humans J. Neural Eng. 5 75-84
38. Wolpaw J R and McFarland D J 2004 Control of a two-dimensional movement signal by a noninvasive brain-computer interface in humans Proc. Natl Acad. Sci. USA 101 17849-54