Current theories suggest that action-selection in the mammalian brain depends on an interaction between multiple, neurally-separable algorithms. The existence of multiple decision-systems opens up novel questions that do not exist within a unitary decision-maker: What happens when these systems select conflicting actions? How are those conflicts resolved? A number of disorders (OCD, eating disorders, drug addiction) and a number of RDOC-related dysfunctions (compulsivity, habits, and issues of cognitive and ?self-? control) have all been proposed to depend on resolutions of conflicts between these decision-systems. Recently developed human tasks have proved capable of putting these decision-systems into conflict for study. We have translated and validated a rodent version of this new human task. We will build on our established expertise in neural ensemble recording and computational analysis to examine how conflicts between these systems is resolved. Using DREADD manipulation and neural ensemble recording technologies, we propose to identify the mechanisms and computations that underlie conflict resolution between these decision-systems.

Public Health Relevance

Current theories that suggest that action-selection in mammalian brains depends on the interaction of multiple neurally-separable algorithms imply a question that does not exist in a unitary decision-maker ? what happens when these systems select conflicting actions? Understanding how these conflicts are resolved can help recognize and alleviate disorders that arise from imbalances between decision-making systems (such as OCD, eating disorders, and drug addiction) and can also help us develop new behavioral ?nudges? that can guide behavior.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
5R01MH112688-03
Application #
9628671
Study Section
Neurobiology of Learning and Memory Study Section (LAM)
Program Officer
Rossi, Andrew
Project Start
2017-04-01
Project End
2022-01-31
Budget Start
2019-02-01
Budget End
2020-01-31
Support Year
3
Fiscal Year
2019
Total Cost
Indirect Cost
Name
University of Minnesota Twin Cities
Department
Neurosciences
Type
Schools of Medicine
DUNS #
555917996
City
Minneapolis
State
MN
Country
United States
Zip Code
55455
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Sweis, Brian M; Thomas, Mark J; Redish, A David (2018) Beyond simple tests of value: measuring addiction as a heterogeneous disease of computation-specific valuation processes. Learn Mem 25:501-512
Hasz, Brendan M; Redish, A David (2018) Deliberation and Procedural Automation on a Two-Step Task for Rats. Front Integr Neurosci 12:30
Sweis, Brian M; Thomas, Mark J; Redish, A David (2018) Mice learn to avoid regret. PLoS Biol 16:e2005853
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