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Title page for ETD etd-03312008-145703


Type of Document Dissertation
Author Bernard, Melanie Rebecca
URN etd-03312008-145703
Title Coding of Natural Features by Neuronal Synchronization in Primary Visual Cortex
Degree PhD
Department Biomedical Engineering
Advisory Committee
Advisor Name Title
Professor A. B. Bonds, III Committee Chair
Professor Adam W. Anderson Committee Member
Professor R. Alan Peters, II Committee Member
Professor Richard G. Shiavi Committee Member
Professor Vivien A. Casagrande Committee Member
Keywords
  • contour detection
  • visual cortex
  • natural scenes
  • neural coding
  • synchrony
  • Visual perception
  • Image processing
  • Synchronization
Date of Defense 2008-03-27
Availability unrestricted
Abstract
Modern neuroscience seeks to understand the human brain and determine how stimulus features are directly mapped to neuronal representations that govern emergent properties like perception and behavior. One prominent proposal for population-based encoding of information is synchronization in the firing of two or more cells. Although synchrony has tremendous potential as a coding mechanism, understanding its relevance is difficult since the techniques to measure and analyze synchrony are relatively new. The work presented here combines simultaneous recordings from dozens of neurons with a novel method for identification of cellular assemblies defined by synchrony to investigate the dynamic associations among small populations during natural stimulation.

We found that synchronous activity was able to discriminate changes in structural integrity and overcome the ambiguity of firing rate to identify contour structure reliably and consistently. The time course of synchrony suggests that it is directly related to spatial stimulus properties. Using a large natural image sequence with a variety of visual features to optimize stimulation of the entire recorded population, we showed that synchronous activity was correlated with the receptive field properties of proximity, orientation, and continuity. We used these properties to create a contour index, which quantitatively described how well an assembly's configuration matched a contour structure. Synchrony was well-correlated with this measure, which indicates that cooperation may be selective for local contrast structure arranged in continuous, well-defined contours. Synchronous activity is particularly sensitive to structural content in natural images, which is preserved in the phase regularities in the image and not the power spectrum. We found that synchrony measured between assemblies representing different contours was severely reduced. Responses were sparse for each assembly across the image set and well as across all assemblies for each condition. Our results demonstrate that synchrony has the potential to encode image properties not apparent from changes in firing rate. As a fundamental mechanism of sensory cognition, synchrony may act as a sparse code to help facilitate the detection of contour information for integration and processing in higher visual areas.

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