A Formal Approach to Modeling the Cost of Cognitive Control

TL;DR

This paper presents a formal framework for modeling the cognitive control costs involved in executing mental processes, focusing on intensity and interaction costs, and deriving optimal control policies based on process success probabilities.

Contribution

It introduces a novel formal method to quantify and analyze the costs of cognitive control, including interaction effects between competing processes.

Findings

Interaction cost depends on process strengths and competition directionality

Formal relationship established between control signals and success probabilities

Optimal control policies can be derived for desired activation levels

Abstract

This paper introduces a formal method to model the level of demand on control when executing cognitive processes. The cost of cognitive control is parsed into an intensity cost which encapsulates how much additional input information is required so as to get the specified response, and an interaction cost which encapsulates the level of interference between individual processes in a network. We develop a formal relationship between the probability of successful execution of desired processes and the control signals (additive control biases). This relationship is also used to specify optimal control policies to achieve a desired probability of activation for processes. We observe that there are boundary cases when finding such control policies which leads us to introduce the interaction cost. We show that the interaction cost is influenced by the relative strengths of individual processes, as well as the directionality of the underlying competition between processes.