Coupling time decoding and trajectory decoding using a target-included model in the motor cortex

Neurocomputing

Volumn 82, Issue , 2012, Pages 117-126

  Lawhern, Vernon ^a   Hatsopoulos, Nicholas G ^b   Wu, Wei ^a  

^a FLORIDA STATE UNIVERSITY   (United States)

^b UNIVERSITY OF CHICAGO   (United States)

Author keywords

Motor cortex; Neural decoding; State space model; Target included model; Time decoding; Trajectory decoding

Indexed keywords

DECODING METHODS; INITIAL STAGES; MAIN STRUCTURE; MOTOR CORTEX; MOVEMENT BEHAVIOR; NEURAL DECODING; NEURONAL ACTIVITIES; STATE-SPACE FRAMEWORK; STATE-SPACE MODELS;

TRAJECTORIES;

DECODING;

ACCURACY; ALGORITHM; ANIMAL EXPERIMENT; ARTICLE; CONTROLLED STUDY; HAND MOVEMENT; INFORMATION TECHNOLOGY; KALMAN FILTER ALGORITHM; KINEMATICS; MODEL; MOTOR CORTEX; NONHUMAN; PRIORITY JOURNAL; STEREOTYPY; TIME DECODING; TRAJECTORY DECODING;

EID: 84862825739     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2011.10.030     Document Type: Article

References (37)

1. Achtman N., Afshar A., Santhanam G., Yu B.M., Ryu S.I., Shenoy K.V. Free-paced high-performance brain-computer interfaces. J. Neural Eng. 2007, 4:336-347.
2. Bokil H.S., Pesaran B., Andersen R.A., Mitra P.P. A method for detection and classification of events in neural activity. IEEE Trans. Biomed. Eng. 2006, 53:1678-1687.
3. Boyd S., Vandenberghe L. Convex Optimization 2004, Cambridge University Press.
4. Brockwell A.E., Kass R.E., Schwartz A.B. Statistical signal processing and the motor cortex. Proc. IEEE 2007, 95:1-18.
5. Brockwell A.E., Rojas A.L., Kass R.E. Recursive Bayesian decoding of motor cortical signals by particle filtering. J. Neurophysiol. 2004, 91:1899-1907.
6. Chi Z., Wu W., Haga Z., Hatsopoulos N., Margoliash D. Template-based spike pattern identification with linear convolution and dynamic time warping. J. Neurophysiol. 2007, 97:1221-1235.
7. Cunningham J.P., Yu B.M., Gilja V., Ryu S.I., Shenoy K.V. Toward optimal target placement for neural prosthetic devices. J. Neurophysiol. 2008, 100:3445-3457.
8. Eden U., Frank L., Barbieri R., Solo V., Brown E. Dynamic analysis of neural encoding by point process adaptive filtering. Neural Comput. 2004, 16:971-988.
9. Haykin S. Kalman Filtering and Neural Networks 2001, John Wiley & Sons, Inc.
10. Kemere C., Shenoy K.P., Meng T.H. Model-based neural decoding of reaching movements: a maximum likelihood approach. IEEE Trans. Biomed. Eng. 2005, 5:353-356.
11. Kemere C., Meng T.H. Optimal estimation of feed-forward-controlled linear systems. Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing 2005, vol. 5:353-356.
12. Kim S., Simeral J.D., Hochberg L.R., Donoghue J.P., Black M.J. Neural control of computer cursor velocity by decoding motor cortical spiking activity in humans with tetraplegia. J. Neural Eng. 2008, 5:455.
13. Kim S.P., Sanchez J.C., Principe J.C. Real time input subset selection for linear time-variant MIMO systems. Optim. Methods Software 2007, 22(1):83-98.
14. Koyama S., Chase S.M., Whitford A.S., Velliste M., Schwartz A.B., Kass R.E. Comparison of brain-computer interface decoding algorithms in open-loop and closed-loop control. J. Comput. Neurosci. 2010, 29:73-87.
15. Koyama S., Pérez-Bolde L.C., Shalizi C.R., Kass R. Approximate methods for state-space models. J. Am. Stat. Assoc. 2010, 105(489):170-180.
16. Kulkarni J.E., Paninski L. Common-input models for multiple neural spike-train data. Network: Comput. Neural Syst. 2007, 18:375-407.
17. Kulkarni J.E., Paninski L. State-space decoding of goal directed movement. IEEE Signal Process. Mag. 2008, 25(1):78-86.
18. Lawhern V., Wu W., Hatsopoulos N.G., Paninski L. Population decoding of motor cortical activity using a generalized linear model with hidden states. J. Neurosci. Methods 2010, 2:267-280.
19. Moran D., Schwartz A. Motor cortical representation of speed and direction during reaching. J. Neurophysiol. 1999, 82(5):2676-2692.
20. Mulliken G.H., Musallam S., Andersen R.A. Decoding trajectories from posterior parietal cortex ensembles. J. Neurosci. 2008, 28(48):12913-12926.
21. Nykamp D. A mathematical framework for inferring connectivity in probabilistic neuronal networks. Math. Biosci. 2007, 205:204-251.
22. Paninski L. Maximum likelihood estimation of cascade point-process neural encoding models. Network: Comput. Neural Syst. 2004, 15:243-262.
23. Paninski L., Ahmadian Y., Ferreira D., Koyama S., Rahnama Rad K., Vidne M., Vogelstein J., Wu W. A new look at state-space models for neural data. J. Comput. Neurosci. 2010, 29:107-126.
24. Paninski L., Fellows M., Hatsopoulos N., Donoghue J.P. Spatiotemporal tuning of motor cortical neurons for hand position and velocity. J. Neurophysiol. 2004, 91:515-532.
25. Sanchez J.C., Erdogmus D., Principe J.C., Wessberg J., Nicolelis M.A.L. Interpreting spatial and temporal neural activity through a recurrent neural network brain machine interface. IEEE Trans. Neural Syst. Rehabil. Eng. 2005, 13:213-219.
26. Scott S.H. Apparatus for measuring and perturbing shoulder and elbow joint positions and torques during reaching. J. Neurosci. Methods 1999, 89:119-127.
27. Shenoy K.V., Meeker D., Cao S., Kureshi S.A., Pesaran B., Buneo C.A., Batista A.P., Mitra P.P., Burdick J.W., Andersen R.A. Neural prosthetic control signals from plan activity. NeuroReport 2003, 14(4):591-597.
28. Srinivasan L., Brown E.N. A state-space analysis for reconstruction of goal-directed movements using neural signals. IEEE Trans. Biomed. Eng. 2007, 54(3):526-535.
29. Srinivasan L., Eden U.T., Mitter S.K., Brown E.N. General-purpose filter design for neural prosthetic devices. J. Neurophysiol. 2007, 98:2456-2475.
30. Srinivasan L., Eden U.T., Willsky A.S., Brown E.N. A state-space analysis for reconstruction of goal-directed movements using neural signals. Neural Comput. 2006, 18:2465-2494.
31. Stevenson I.H., Rebesco J.M., Hatsopoulos N.G., Haga Z., Miller L.E., Kording K.P. Bayesian inference of functional connectivity and network structure from spikes. IEEE Trans. Neural Syst. Rehabil. 2009, 17:203-213.
32. Truccolo W., Donoghue J.P. Nonparametric modeling of neural point processes via stochastic gradient boosting regression. Neural Comput. 2007, 19:672-705.
33. Truccolo W., Eden U.T., Fellows M.R., Donoghue J.P., Brown E.N. A point process framework for relating neural spiking activity to spiking history, neural ensemble and extrinsic covariate effects. J. Neurophysiol. 2005, 93:1074-1089.
34. Wu W., Gao Y., Bienenstock E., Donoghue J.P., Black M.J. Bayesian population decoding of motor cortical activity using a Kalman filter. Neural Comput. 2006, 18(1):80-118.
35. Wu W., Hatsopoulos N. Real-time decoding of non-stationary neural activity in motor cortex. IEEE Trans. Neural Syst. Rehabil. Eng. 2008, 16(3):213-222.
36. Wu W., Kulkarni J.E., Hatsopoulos N.G., Paninski L. Neural decoding of hand motion using a linear state-space model with hidden states. IEEE Trans. Neural Syst. Rehabil. Eng. 2009, 17(4):370-378.
37. Yu B.M., Kemere C., Santhanam G., Afshar A., Ryu S.I., Meng T.H., Sahani M., Shenoy K.V. Mixture of trajectory models for neural decoding of goal-directed movements. J. Neurophysiol. 2007, 97:3763-3780.