Mixture of trajectory models for neural decoding of goal-directed movements.

Abstract

Probabilistic decoding techniques have been used successfully to infer time-evolving physical state, such as arm trajectory or the path of a foraging rat, from neural data. A vital element of such decoders is the trajectory model, expressing knowledge about the statistical regularities of the movements. Unfortunately, trajectory models that both 1… (More)

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Cite this paper

@article{Yu2007MixtureOT, title={Mixture of trajectory models for neural decoding of goal-directed movements.}, author={Byron M. Yu and Caleb Kemere and Gopal Santhanam and Afsheen Afshar and Stephen I. Ryu and Teresa H. Y. Meng and Maneesh Sahani and Krishna V. Shenoy}, journal={Journal of neurophysiology}, year={2007}, volume={97 5}, pages={3763-80} }