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Tracking Temporal Evolution of Nonlinear Dynamics in Hippocampus using Time-Varying Volterra Kernels

  • Rosa H.M. Chan*
  • , Dong Song
  • , Theodore W. Berger
  • *Corresponding author for this work

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

Abstract

Hippocampus and other parts of the cortex are not stationary, but change as a function of time and experience. The goal of this study is to apply adaptive modeling techniques to the tracking of multiple-input, multiple-output (MIMO) nonlinear dynamics underlying spike train transformations across brain subregions, e.g. CA3 and CA1 of the hippocampus. A stochastic state point process adaptive filter will be used to track the temporal evolutions of both feedforward and feedback kernels in the natural flow of multiple behavioral events. © 2008 IEEE.
Original languageEnglish
Title of host publicationProceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Subtitle of host publication"Personalized Healthcare through Technology”
PublisherIEEE
Pages4996-4999
ISBN (Electronic)9781424418152
ISBN (Print)9781424418145
DOIs
Publication statusPublished - Aug 2008
Externally publishedYes
Event30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS'08) - Vancouver Convention & Exhibition Centre, Vancouver, Canada
Duration: 20 Aug 200824 Aug 2008

Publication series

NameIEEE Engineering in Medicine and Biology Society. Conference Proceedings
ISSN (Print)1094-687X
ISSN (Electronic)1558-4615

Conference

Conference30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS'08)
PlaceCanada
CityVancouver
Period20/08/0824/08/08

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