Decoding stimuli from multi-source neural responses

Lin Li, John S. Choi, Joseph T. Francis, Justin C. Sanchez, Jose C. Principe

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Spike trains and local field potentials (LFPs) are two different manifestations of neural activity recorded simultaneously from the same electrode array and contain complementary information of stimuli or behaviors. This paper proposes a tensor product kernel based decoder, which allows modeling the sample from different sources individually and mapping them onto the same reproducing kernel Hilbert space (RKHS) defined by the tensor product of the individual kernels for each source, where linear regression is conducted to identify the nonlinear mapping from the multi-type neural responses to the stimuli. The decoding results of the rat sensory stimulation experiment show that the tensor-product-kernel-based decoder outperforms the decoders with either single-type neural activities.

Original languageEnglish
Title of host publicationProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Pages1331-1334
Number of pages4
DOIs
StatePublished - Dec 14 2012
Event34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012 - San Diego, CA, United States
Duration: Aug 28 2012Sep 1 2012

Other

Other34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012
Country/TerritoryUnited States
CitySan Diego, CA
Period8/28/129/1/12

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Biomedical Engineering
  • Health Informatics

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