Wei Wu, Michael J. Black, David Mumford, Yun Gao, Elie Bienenstock, John P. Donoghue  Home/Search
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Abstract: We present a switching Kalman filter model for the real-time inference of hand kinematics from a population of motor cortical neurons. Firing rates are modeled as a Gaussian mixture where the mean of each Gaussian component is a linear function of hand kinematics. A "hidden state" models the probability of each mixture component and evolves over time in a Markov chain. The model generalizes previous encoding and decoding methods, addresses the non-Gaussian nature of firing rates, and can cope... (Update)
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Inferring Attentional State and Kinematics from Motor.. - Frank Wood Prabhat (2005) (Correct)
Bayesian Population Decoding of Motor Cortical.. - Gao, Bienenstock.. (2005) (Correct)
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1.1: Neural Decoding of Cursor Motion Using a Kalman Filter - Wu, Black, Gao.. (2003) (Correct)
0.9: Automatic Spike Sorting for Neural Decoding - Wood Fellows Donoghue (2004) (Correct)
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BibTeX entry: (Update)
Wu, W., Black, M. J., Mumford, D., Gao, Y., Bienenstock, E., and Donoghue, J. P. (2004a). Modeling and decoding motor cortical activity using a switching Kalman filter. IEEE Transactions on Biomedical Engineering, 51, 933--942. http://citeseer.ist.psu.edu/article/wu04modeling.html More
@misc{ wu-modeling,
author = "W. Wu and M. Black and D. Mumford and Y. Gao and E. Bienenstock and J.
Donoghue",
title = "Modeling and decoding motor cortical activity using a switching Kalman
filter",
text = "Wu, W., Black, M. J., Mumford, D., Gao, Y., Bienenstock, E., and Donoghue,
J. P. (2004a). Modeling and decoding motor cortical activity using a switching
Kalman filter. IEEE Transactions on Biomedical Engineering, 51, 933--942.",
url = "citeseer.ist.psu.edu/article/wu04modeling.html" }
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