Extraction of Behavioral Dynamics and Learning Rules in Decision-Making Experiments

by Roy, Nicholas A.

Type Thesis
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Understanding how animals update their decision-making behavior over time is an important problem in neuroscience. Perceptual decision-making strategies evolve over the course of learning, and continue to vary even in well-trained animals. While reinforcement learning aims to understand such strategies from a normative perspective, there are comparatively fewer purely descriptive tools for capturing behavioral dynamics. Behavior is either treated as fixed or is tracked only with coarse performa…

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Summary

Understanding how animals update their decision-making behavior over time is an important problem in neuroscience. Perceptual decision-making strategies evolve over the course of learning, and continue to vary even in well-trained animals. While reinforcement learning aims to understand such strategies from a normative perspective, there are comparatively fewer purely descriptive tools for capturing behavioral dynamics. Behavior is either treated as fixed or is tracked only with coarse performance statistics, providing limited insight into the evolution of decision-making strategies.

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Edition Statements

  • Publication Date:2020

Thesis Information

  • Degree:Ph.D.
  • University:Princeton University
  • Advisor/Supervisor:Pillow, Jonathan W.
  • Pages:91

Publication Statements

  • Language:eng
  • Publication Date:2020

Edition Identifiers

  • proquest:2429005273

Subjects

Behavior decision making eng Learning Neurosciences PDF Psychophysics

Writers

Roy, Nicholas A. Pillow, Jonathan W.

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