Document Detail


Ascertaining neuron importance by information theoretical analysis in motor Brain-Machine Interfaces.
MedLine Citation:
PMID:  19615852     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Point process modeling of neural spike recordings has the potential to capture with high specificity the information contained in spike time occurrence. In Brain-Machine Interfaces (BMIs) the neural tuning characteristic assessed from neural spike recordings can distinguish neuron importance in terms of its modulation with the movement task. Consequently, it improves generalization and reduces significantly computation in previous decoding algorithms, where models reconstruct the kinematics from recorded activities of hundreds of neurons. We propose to apply information theoretical analysis based on an instantaneous tuning model to extract the important neuron subsets for point process decoding on BMI. The cortical distribution of extracted neuron subsets is analyzed and the statistical decoding performance using subset selection is studied with respect to different number of neurons and compared to the one by the full neuron ensemble. With much less computation, the extracted importance neurons provide comparable kinematic reconstructions compared to the full neuron ensemble. The performance of the extracted subset is compared to the random selected subset with same number of neurons to further validate the effectiveness of the subset-extraction approach.
Authors:
Yiwen Wang; Jose C Principe; Justin C Sanchez
Publication Detail:
Type:  Journal Article; Research Support, U.S. Gov't, Non-P.H.S.     Date:  2009-06-30
Journal Detail:
Title:  Neural networks : the official journal of the International Neural Network Society     Volume:  22     ISSN:  1879-2782     ISO Abbreviation:  Neural Netw     Publication Date:    2009 Jul-Aug
Date Detail:
Created Date:  2009-08-11     Completed Date:  2009-11-02     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  8805018     Medline TA:  Neural Netw     Country:  United States    
Other Details:
Languages:  eng     Pagination:  781-90     Citation Subset:  IM    
Affiliation:
Department of Electrical & Computer Engineering, University of Florida, Gainesville, FL, USA. wangyw@cnel.ufl.edu
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MeSH Terms
Descriptor/Qualifier:
Action Potentials
Algorithms
Animals
Arm
Biomechanics
Computer Simulation
Electrodes, Implanted
Haplorhini
Information Theory
Models, Neurological*
Monte Carlo Method
Motor Activity / physiology*
Motor Cortex / physiology*
Neurons / physiology*
Poisson Distribution
Psychomotor Performance / physiology
Somatosensory Cortex / physiology*
User-Computer Interface*

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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