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Cognitive Control as a Multivariate Optimization Problem.

Harrison Ritz1, Xiamin Leng1, Amitai Shenhav1

  • 1Brown University.

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This summary is machine-generated.

Understanding cognitive control is key to adaptation. New models frame control allocation as a decision-making problem, potentially explaining mental effort by drawing parallels with motor control strategies.

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Area of Science:

  • Cognitive Neuroscience
  • Decision Science
  • Neuroscience

Background:

  • Cognitive control allows adaptation by managing thoughts and actions across diverse situations.
  • Research has identified various forms of cognitive control (enhancement, suppression, inhibition) and their neural underpinnings.
  • While situations triggering control adjustments are known, the precise rules governing these shifts remain unclear.

Purpose of the Study:

  • To address the challenge of selecting among multiple cognitive control configurations.
  • To explore the complexities of the inverse problem in cognitive control allocation.
  • To propose a normative perspective on mental effort by drawing parallels with motor control.

Main Methods:

  • Framing cognitive control allocation as a decision-making problem.
  • Developing unifying and normative models for control adjustments based on incentives and task demands.
  • Examining inverse problems in motor control and optimal control theory.

Main Results:

  • Progress has been made in modeling control allocation as a decision process.
  • Optimal control theory, particularly the role of effort costs, offers potential solutions to motor control inverse problems.
  • These principles may illuminate how the brain optimizes complex control configurations.

Conclusions:

  • The allocation of cognitive control presents an inverse problem analogous to motor control.
  • Effort costs, as suggested by optimal control theory, may regularize actions and inform cognitive control strategies.
  • This approach offers a new normative framework for understanding mental effort and cognitive control optimization.