A regularized point process generalized linear model for assessing the connectivity in the cat motor cortex
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...
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| Format: | Article |
| Language: | en_US |
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Institute of Electrical and Electronics Engineers
2010
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| Online Access: | http://hdl.handle.net/1721.1/58950 https://orcid.org/0000-0003-2668-7819 https://orcid.org/0000-0002-6166-448X |
| _version_ | 1826188071958216704 |
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| author | Ghosh, Soumya Chen, Zhe Putrino, David F. Ba, Demba E. Barbieri, Riccardo Brown, Emery N. |
| author2 | Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences |
| author_facet | Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences Ghosh, Soumya Chen, Zhe Putrino, David F. Ba, Demba E. Barbieri, Riccardo Brown, Emery N. |
| author_sort | Ghosh, Soumya |
| collection | MIT |
| description | 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. |
| first_indexed | 2024-09-23T07:54:09Z |
| format | Article |
| id | mit-1721.1/58950 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T07:54:09Z |
| publishDate | 2010 |
| publisher | Institute of Electrical and Electronics Engineers |
| record_format | dspace |
| spelling | mit-1721.1/589502022-09-23T09:31:35Z A regularized point process generalized linear model for assessing the connectivity in the cat motor cortex A Regularized Point Process Generalized Linear Model for Assessing the Functional Connectivity in the Cat Motor Cortex Ghosh, Soumya Chen, Zhe Putrino, David F. Ba, Demba E. Barbieri, Riccardo Brown, Emery N. Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Chen, Zhe Chen, Zhe Putrino, David F. Ba, Demba E. Barbieri, Riccardo Brown, Emery N. 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. National Institutes of Health (U.S.) (Grant DP1-OD003646) National Institutes of Health (U.S.) (Grant R01-DA015644) National Institutes of Health (U.S.) (Grant R01-HL084502) 2010-10-07T19:47:47Z 2010-10-07T19:47:47Z 2009-11 Article http://purl.org/eprint/type/JournalArticle 978-1-4244-3296-7 1557-170X http://hdl.handle.net/1721.1/58950 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 https://orcid.org/0000-0003-2668-7819 https://orcid.org/0000-0002-6166-448X en_US http://dx.doi.org/10.1109/IEMBS.2009.5334610 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2009 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. application/pdf Institute of Electrical and Electronics Engineers IEEE |
| spellingShingle | Ghosh, Soumya Chen, Zhe Putrino, David F. Ba, Demba E. Barbieri, Riccardo Brown, Emery N. A regularized point process generalized linear model for assessing the connectivity in the cat motor cortex |
| title | A regularized point process generalized linear model for assessing the connectivity in the cat motor cortex |
| title_full | A regularized point process generalized linear model for assessing the connectivity in the cat motor cortex |
| title_fullStr | A regularized point process generalized linear model for assessing the connectivity in the cat motor cortex |
| title_full_unstemmed | A regularized point process generalized linear model for assessing the connectivity in the cat motor cortex |
| title_short | A regularized point process generalized linear model for assessing the connectivity in the cat motor cortex |
| title_sort | regularized point process generalized linear model for assessing the connectivity in the cat motor cortex |
| url | http://hdl.handle.net/1721.1/58950 https://orcid.org/0000-0003-2668-7819 https://orcid.org/0000-0002-6166-448X |
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