Modeling and decoding motor cortical activity using a switching Kalman filter

  title={Modeling and decoding motor cortical activity using a switching Kalman filter},
  author={Wei Wu and Michael J. Black and David Mumford and Yun Gao and Elie Bienenstock and John P. Donoghue},
  journal={IEEE Transactions on Biomedical Engineering},
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… CONTINUE READING
Highly Influential
This paper has highly influenced 10 other papers. REVIEW HIGHLY INFLUENTIAL CITATIONS


Publications citing this paper.
Showing 1-10 of 124 extracted citations

An Application Specific Instruction Set Processor (ASIP) for Adaptive Filters in Neural Prosthetics

IEEE/ACM Transactions on Computational Biology and Bioinformatics • 2015
View 16 Excerpts
Highly Influenced

Neural decoding based on probabilistic neural network

Journal of Zhejiang University SCIENCE B • 2009
View 4 Excerpts
Highly Influenced

Decoding Hand Kinematics and Neural States Using Gaussian Process Model

2008 2nd International Conference on Bioinformatics and Biomedical Engineering • 2008
View 4 Excerpts
Highly Influenced


Publications referenced by this paper.
Showing 1-10 of 33 references

Switching Kalman Filters

View 17 Excerpts
Highly Influenced

Motor cortical representation of speed and direction during reaching.

Journal of neurophysiology • 1999
View 5 Excerpts
Highly Influenced

Similar Papers

Loading similar papers…