Neural circuits underlying flexible control of evidence evaluation timescales in decision making

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Project Summary Impaired decision making is observed in almost all mental disorders. Neural circuits mechanisms responsible for the flexible control of decision making therefore hold particular promise as targets for treatments to improve decision making impairments. Much progress has been made in elucidating the neural mechanisms supporting many aspects of cognitive flexibility that influence decision processes, but relevantly little is known about the mechanisms that control the form and timescale of evidence evaluation for decision making. In contrast to the dominant paradigms used for the study of perceptual decisions that focus on situations involving linear integration of repeated samples of evidence, many decisions instead benefit from weighting evidence differentially as a function of time. The proposed experiments will use a rat model system to probe the neural circuits underlying flexible control of evidence evaluation in these circumstances. The first aim will develop a new auditory change detection paradigm to study neural contributions to decisions involving non-integrative forms of evidence evaluation. Specifically, we will examine how a network of brain regions known to encode decision variables in tasks involving linear integration of evidence here encodes decision variables based on dynamic weighting with time in evidence evaluation. The second aim will test how altered decision bounds affect this encoding in the change detection paradigm. Decision bounds determine the amount of evidence needed for choice commitment, so they play a key role in control over the timescale of evidence evaluation. We will simultaneously record from three brain regions previously implicated separately in the control of decision bounds to examine how associated neural changes are coordinated between regions. The third aim will test how altered decision kernels induce changes in the same network of brain regions. Decision kernels determine how evidence is weighted as a function of time, so they play a key role in control over the form of evidence evaluation. We will first examine the degree to which each of the studied brain regions alters it response dynamics to external evidence based on altered decision kernels. Next, we will probe the direct involvement of those regions in circuits responsible for the altered response dynamics versus the inheriting of altered response dynamics from upstream neural processing. The objective of this work is to expose targets for principled treatments at the level of specific neural circuit mechanisms to improve decision making impairments associated with mental disorders, including ongoing work in our lab. In the long term, we expect this research to harness a combination of human, non-human primate, and rodent model systems to produce a detailed understanding of the neural circuit mechanisms that underlie flexible control over evidence evaluation for decision making, paving the way for treatment development.