Encoding of motion targets by waves in turtle visual cortex

Xiuxia Du, Bijoy K. Ghosh, Philip Ulinski

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

Visual stimuli evoke wave activity in the visual cortex of freshwater turtles. Earlier work from our laboratory showed that information about the positions of stationary visual stimuli is encoded in the spatiotemporal dynamics of the waves and that the waves can be decoded using Bayesian detection theory. This paper extends these results in three ways. First, it shows that flashes of light separated in space and time and stimuli moving with three speeds can be discriminated statistically using the waves generated in a large-scale model of the cortex. Second, it compares the coding capabilities of spike rate and spike time codes. Spike rate codes were obtained by low-pass filtering the activities of individual neurons in the model with filters of different band widths. For the moving targets used in the study, detectability using spike rate codes is immune to the choice of a specific bandwidth, indicating that a coarse filter is able to adequately discriminate targets. Spike timing codes are binary sequences indicating the precise timing of spike activity of individual neurons across the cortex. Spike time codes generally perform better than do spike rate codes. Third, the encoding process is examined in terms of the underlying cellular mechanisms that result in the initiation, propagation and cessation of the wave. The period of peak detectability corresponds to the period in which waves are propagating across the cortex.

Original languageEnglish
Article number1658164
Pages (from-to)1688-1695
Number of pages8
JournalIEEE Transactions on Biomedical Engineering
Volume53
Issue number8
DOIs
StatePublished - Aug 2006

Keywords

  • Karhunen-Loeve (KL) decomposition
  • Motion encoding
  • Statistical hypothesis testing
  • Turtle visual cortex
  • β-space representation

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