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theses

One of the most significant questions about the nature of brain function is the extent to which brain networks are functionally constrained in terms of the task contexts in which they respond, versus whether their function is highly flexible across contexts (McIntosh, 2000). Thanks to decades of animal and human research, one of the most well defined networks in the brain is the corticostriatal circuit. The finding that dopamine neurons in this circuit respond to mismatches between expectations and outcomes in choice tasks according to a reinforcement learning (RL) algorithm (Shultz, 1997) helped orient the field of decision neuroscience towards studying RL type responses in the brain. Nearly all of these kinds of studies necessite choice tasks with concrete outcomes, in which subjects do something and get something, in order to have both expectation and outcome terms for RL modeling. However, far less attention has been paid to choice contexts that are abstract, that is, there are no expectations or outcomes. Additionally, most reward stimuli used to test decision making response are constrained by low dimensionality. This approach has left open several key questions about how the brain responds to abstract, multidimensional choices, and whether this response is modulated by factors such as choice context, subjective value, stimulus valence, and stimulus attributes in a manner that is the same or different from the well characterized response to these factors in concrete contexts. In a series of studies, this dissertation addresses the following unresolved questions: Study 1: How do brain regions associated with reward (e.g. striatum) and value (e.g. prefrontal cortex) respond when people choose amongst stimuli that are abstract and multidimensional? Study 2: How is this response affected by changes in choice context and stimulus valence? Study 3: How do value signals in the brain influence similarity coding of abstract reinforcers?

ETD_6577

Ph.D.

Includes bibliographical references

by Colleen Mills-Finnerty

doi:10.7282/T3B27X9R

ETD doctoral

The author owns the copyright to this work.