Resolving conflicts between decision-making algorithms

NIH RePORTER · NIH · R01 · $420,135 · view on reporter.nih.gov ↗

Abstract

Project summary 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.

Key facts

NIH application ID
10106479
Project number
5R01MH112688-05
Recipient
UNIVERSITY OF MINNESOTA
Principal Investigator
A DAVID REDISH
Activity code
R01
Funding institute
NIH
Fiscal year
2021
Award amount
$420,135
Award type
5
Project period
2017-04-01 → 2022-01-31