| Nonstationary modeling of neural population dynamics. | |
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MedLine Citation:
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PMID: 19963837 Owner: NLM Status: In-Data-Review |
Abstract/OtherAbstract:
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A stochastic state point-process adaptive filter was used to track the temporal evolution of several simulated nonlinear dynamical systems. The estimated Laguerre coefficients and Laguerre poles were used to reconstruct the feedforward and feedback kernels in the system. Simulations showed that the proposed method could track the actual underlying changes of nonlinear kernels using spike input and spike output information alone. The estimated models also converge quickly to the actual models after abrupt step changes in kernels. The proposed method can be used to track the functional input-output properties of neural systems as a result of learning, changes in context, aging or other factors in the natural flow of behavioral events. |
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Authors:
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Rosa H M Chan; Dong Song; Theodore W Berger |
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Publication Detail:
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Type: Journal Article |
Journal Detail:
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Title: Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference Volume: 1 ISSN: 1557-170X ISO Abbreviation: Conf Proc IEEE Eng Med Biol Soc Publication Date: 2009 |
Date Detail:
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Created Date: 2009-12-07 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 101243413 Medline TA: Conf Proc IEEE Eng Med Biol Soc Country: United States |
Other Details:
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Languages: eng Pagination: 4559-62 Citation Subset: IM |
Affiliation:
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Department of Biomedical Engineering, University of Southern California, Los Angeles, CA 90089 USA. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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