A regularized point process generalized linear model for assessing the connectivity in the cat motor cortex
Name
Chen-2009-A regularized point process generalized linear model for assessing the connectivity in the cat motor cortex.pdf
Size
392.41 KB
Format
Adobe PDF
Checksum (MD5)
5c934211389c3b95aeaf037bb76d102b
Author(s)
Ghosh, Soumya
Chen, Zhe
Putrino, David F.
Ba, Demba E.
Barbieri, Riccardo
Brown, Emery N.
Alternative Title
A Regularized Point Process Generalized Linear Model for Assessing the Functional Connectivity in the Cat Motor Cortex
Date Issued
November 2009
Journal
Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2009
Publisher
Institute of Electrical and Electronics Engineers
Citation
Zhe Chen et al. “A regularized point process generalized linear model for assessing the functional connectivity in the cat motor cortex.” Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE. 2009. 5006-5009. © 2009 IEEE
Version
Final published version
Abstract
Identification of multiple simultaneously recorded neural spike train recordings is an important task in understanding neuronal dependency, functional connectivity, and temporal causality in neural systems. An assessment of the functional connectivity in a group of ensemble cells was performed using a regularized point process generalized linear model (GLM) that incorporates temporal smoothness or contiguity of the solution. An efficient convex optimization algorithm was then developed for the regularized solution. The point process model was applied to an ensemble of neurons recorded from the cat motor cortex during a skilled reaching task. The implications of this analysis to the coding of skilled movement in primary motor cortex is discussed.
MIT Department
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1109/IEMBS.2009.5334610
