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Title page for ETD etd-04032006-130216


Type of Document Master's Thesis
Author Bernard, Melanie Rebecca
Author's Email Address melanie.r.bernard@vanderbilt.edu
URN etd-04032006-130216
Title Analysis methodology of synchrony in simultaneously recorded single unit activity in the visual cortex
Degree Master of Science
Department Biomedical Engineering
Advisory Committee
Advisor Name Title
A. B. Bonds, III Committee Chair
Richard Shiavi Committee Member
Keywords
  • Image processing
  • Visual cortex
  • neural coding
  • temporal coordination
  • natural images
  • neural assembly
  • Visual perception
  • Synchronization
Date of Defense 2006-04-03
Availability unrestricted
Abstract
      Our brains process and interpret sensory information in order to generate perceptions of the environment or motivate behavior. However, the underlying mechanisms by which salient stimulus qualities are represented by neuronal response patterns remain a mystery. Precise coordination of spike events, or synchrony, is an attractive candidate to play a role in (visual) coding since it exists among (visual) cortical neurons, but its functional significance is largely unknown. Proving synchrony's importance in signaling is difficult since adequate methods to measure synchrony have not been developed. Current approaches quantify synchrony as a relationship between two neurons. However, synchrony allows for the formation of transient functional groups which could include tens, hundreds, thousands, or even larger numbers of neurons. Furthermore, very few studies have investigated how to measure the quality of synchrony in an assembly as well as develop some means to display these quantities.


      The work presented here derives a measure for synchrony within assemblies of arbitrary size by modeling the biological process of postsynaptic potential integration. We derive measures for the magnitude and quality of synchrony as well as show how our results are consistent with the Joint Peri-Stimulus Time Histogram approach for assemblies of two neurons. We also evaluate synchrony's role as a possible neural substrate for contour integration by investigating dynamic grouping and characteristics of group membership. Finally, we propose future investigation of synchrony as a biological sparse code employed by the visual cortex to represent high-order stimulus features in natural scenes.

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