Hippocampal and prefrontal regulation of flexible decision updating during memory-guided learning and decision-making
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Miles, Jesse Thomas
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Abstract
Decision-making requires us to integrate information that is spread out across timescales ranging from milliseconds to years. The information we use to guide decisions depends on current goals and the context in which the decisions are made, all of which can change within moments. As such, we can expect variations in decision-making behavior to depend on requirements of the tasks we engage in, what we’ve learned about our current situation, and how flexibly we behave. Studies of decision-making behavior in rodents have documented a process in which subjects visibly vacillate between options before committing to a final decision. The behavior, widely known as vicarious trial and error (VTE), has garnered attention as an outward manifestation of deliberation/indecision, and has been shown to vary with task proficiency and changes in task demands. Interestingly, similar phenomena have been reported in both non-human primates and humans, suggesting VTE and related behaviors are widespread. Despite almost a century of investigation, what exactly defines a VTE can be unclear, and the field has not yet converged on a method for their identification. Plus, we’re still learning how the litany of brain structures underpinning decision-making interact to enable the decision-making process – especially as it varies from trial-to-trial during learning, and as behaviors like VTE occur. Further, we tend to take for granted that decision-making, learning, memory, and behavioral flexibility are associated with one another, but we often can’t say whether that association is fundamental or because we’ve defined them such that they depend on one another. This thesis addresses these issues by proposing and comparing ways to identify VTE, providing new insights into how neural circuitry that supports learning and memory also enables flexible decision-making and VTE, and re-operationalizing how we assess and compare behavioral flexibility and learning to help define behavioral contexts.
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Thesis (Ph.D.)--University of Washington, 2023
