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To uncover the neural correlates to go-directed behavior, single unit action potentials are considered fundamental computing units and have been examined by different analytical methodologies under a broad set of hypotheses. Using a behaving rat performing a directional choice learning

To uncover the neural correlates to go-directed behavior, single unit action potentials are considered fundamental computing units and have been examined by different analytical methodologies under a broad set of hypotheses. Using a behaving rat performing a directional choice learning task, we aim to study changes in rat's cortical neural patterns while he improved his task performance accuracy from chance to 80% or higher. Specifically, simultaneous multi-channel single unit neural recordings from the rat's agranular medial (AGm) and Agranular lateral (AGl) cortices were analyzed using joint peristimulus time histogram (JPSTHs), which effectively unveils firing coincidences in neural action potentials. My results based on data from six rats revealed that coincidences of pair-wise neural action potentials are higher when rats were performing the task than they were not at the learning stage, and this trend abated after the rats learned the task. Another finding is that the coincidences at the learning stage are stronger than that when the rats learned the task especially when they were performing the task. Therefore, this coincidence measure is the highest when the rats were performing the task at the learning stage. This may suggest that neural coincidences play a role in the coordination and communication among populations of neurons engaged in a purposeful act. Additionally, attention and working memory may have contributed to the modulation of neural coincidences during the designed task.
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    Title
    • Emerging neural coincidences in rats agranular medial and agranular lateral cortices during learning of a directional choice task
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    Date Created
    2014
    Resource Type
  • Text
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    • thesis
      Partial requirement for: M.S., Arizona State University, 2014
    • bibliography
      Includes bibliographical references (p. 33-37)
    • Field of study: Electrical engineering

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    by Bing Cheng

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