Time as a bridge from brain to behavior
Date of Award
Doctor of Philosophy (PhD)
Time has mystified philosophers, artists, and scientists for centuries, but only recently has it become possible to study the neurobiology of time. Time is critical for cognition, and the mechanisms through which it impacts neural processes, such as those for decision-making, are starting to be better understood. Standard mathematical models for decision-making are not suited to studying stimuli or strategies which change over time, so we construct a generalization of a standard model as well as an efficient computational framework, providing insight at both the behavioral and the neural level. We use this framework to understand behavior and single-neuron recordings in the frontal eye field (FEF) for a perceptual decision-making task with stimuli which change over time. First, we perform a high-throughput screen across potential models of decision-making strategies to understand how uncertainty in stimulus onset influences decision-making. Next, we examine the neural response immediately after the change in evidence, and show how this can be used to further clarify decision-making strategy. We also show that a signal representing elapsed time predicted by several behavioral strategies is abundant in FEF neurons. Finally, we determine how high-dimensional data analysis might be impacted by the presence of signals which vary smoothly over time. Overall, this demonstrates the critical role of time in cognition, providing concrete details of its strategic role and neural implementation. This sets the stage for the study of time in neurological and neuropsychiatric disorders.
Shinn, Maxwell, "Time as a bridge from brain to behavior" (2021). Yale Graduate School of Arts and Sciences Dissertations. 177.