Decoding stimuli from multi-source neural responses.

Lin Li, John S. Choi, Joseph T. Francis, Justin C. Sanchez, José C. Príncipe

Research output: Contribution to journalArticle

2 Citations (Scopus)

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
Pages (from-to)1331-1334
Number of pages4
JournalConference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference
Volume2012
StatePublished - Dec 1 2012
Externally publishedYes

Fingerprint

Tensors
Decoding
Linear Models
Electrodes
Hilbert spaces
Linear regression
Rats
Experiments

ASJC Scopus subject areas

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

Cite this

Decoding stimuli from multi-source neural responses. / Li, Lin; Choi, John S.; Francis, Joseph T.; Sanchez, Justin C.; Príncipe, José C.

In: Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference, Vol. 2012, 01.12.2012, p. 1331-1334.

Research output: Contribution to journalArticle

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