Statistical encoding model for a primary motor cortical brain-computer interface

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Publication Type Journal Article
School or College School of Medicine
Department Ophthalmology; Bioengineering; Surgery; Physiology
Creator Normann, Richard A.
Other Author Shoham, Shy; Paninski, Liam M.; Fellows, Matthew R.; Hatsopoulos, Nicholas G.; Donoghue, John P.
Title Statistical encoding model for a primary motor cortical brain-computer interface
Date 2005
Description A number of studies of the motor system suggest that the majority of primary motor cortical neurons represent simple movement-related kinematic and dynamic quantities in their time-varying activity patterns. An example of such an encoding relationship is the cosine tuning of firing rate with respect to the direction of hand motion. We present a systematic development of statistical encoding models for movement-related motor neurons using multielectrode array recordings during a two-dimensional (2-D) continuous pursuit-tracking task. Our approach avoids massive averaging of responses by utilizing 2-D normalized occupancy plots, cascaded linear-nonlinear (LN) system models and a method for describing variability in discrete random systems. We found that the expected firing rate of most movement-related motor neurons is related to the kinematic values by a linear transformation, with a significant nonlinear distortion in about 1/3 of the neurons. The measured variability of the neural responses is markedly non-Poisson in many neurons and is well captured by a "normalized-Gaussian" statistical model that is defined and introduced here. The statistical model is seamlessly integrated into a nearly-optimal recursive method for decoding movement from neural responses based on a Sequential Monte Carlo filter.
Type Text
Publisher Institute of Electrical and Electronics Engineers (IEEE)
Volume 52
Issue 7
First Page 1312
Last Page 1322
Subject Discrete Distribution; LN Model; Neural Decoding; Neuroprosthetics; Sequential Monte-Carlo Filter
Subject MESH Brain Mapping; Electroencephalography; Models, Neurological; User-Computer Interface
Language eng
Bibliographic Citation Shoham S, Paninski LM, Fellows MR, Hatsopoulos NG, Donoghue JP, Normann RA. (July 2005). Statistical Encoding Model for a Primary Motor Cortical Brain-Computer Interface. IEEE Transactions on Biomedical Engineering, 52(7), 1312-1322
Rights Management © Institute of Electrical and Electronics Engineers (IEEE)
Format Medium application/pdf
Identifier ir-main,12731
ARK ark:/87278/s6n594zr
Setname ir_uspace
Date Created 2012-06-13
Date Modified 2021-05-06
ID 706775
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