Abstract

Cognitive control is typically understood as a set of mechanisms that enable humans to reach goals that require integrating the consequences of actions over longer time scales. Importantly, using routine behaviour or making choices beneficial only at short time scales would prevent one from attaining these goals. During the past two decades, researchers have proposed various computational cognitive models that successfully account for behaviour related to cognitive control in a wide range of laboratory tasks. As humans operate in a dynamic and uncertain environment, making elaborate plans and integrating experience over multiple time scales is computationally expensive. Importantly, it remains poorly understood how uncertain consequences at different time scales are integrated into adaptive decisions. Here, we pursue the idea that cognitive control can be cast as active inference over a hierarchy of time scales, where inference, i.e., planning, at higher levels of the hierarchy controls inference at lower levels. We introduce the novel concept of meta-control states, which link higher-level beliefs with lower-level policy inference. Specifically, we conceptualize cognitive control as inference over these meta-control states, where solutions to cognitive control dilemmas emerge through surprisal minimisation at different hierarchy levels. We illustrate this concept using the exploration-exploitation dilemma based on a variant of a restless multi-armed bandit task. We demonstrate that beliefs about contexts and meta-control states at a higher level dynamically modulate the balance of exploration and exploitation at the lower level of a single action. Finally, we discuss the generalisation of this meta-control concept to other control dilemmas.

Highlights

  • The concept of cognitive control is generally used as a summary term for a set of processes that enable humans to flexibly configure perceptual, emotional, and response selection processes in accordance with superordinate goals

  • To set the scene for the proposed model, we briefly introduce the active inference framework, which is an application of the free-energy principle (Friston, 2010) to a sequential decision making under uncertainty, that is, a partially observable Markov decision process (POMDP) (Kaelbling, Littman and Cassandra, 1998; Littman, 2009)

  • As our goal is to describe how the cognitive control and the resolution of control dilemmas naturally emerge within deep active inference, we denote as the meta-control state a state, at an upper level of the hierarchy, which imposes constraints on prior beliefs at the adjacent lower level

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Summary

Introduction

The concept of cognitive control is generally used as a summary term for a set of processes that enable humans to flexibly configure perceptual, emotional, and response selection processes in accordance with superordinate goals. Much of the experimental research on cognitive control has focused on relatively simple laboratory tasks, as, for instance, interference paradigms, such as Stroop or flanker task (Kalanthroff, Davelaar, Henik, Goldfarb and Usher, 2018; Scherbaum, Fischer, Dshemuchadse and Goschke, 2011), or paradigms assessing cognitive flexibility, such as task switching (Koch, Poljac, Muller and Kiesel, 2018). Many of these tasks are designed to induce conflicting internal representations, which trigger responses that are in contradiction to the instructed task goal and may lead to an incorrect response. Such tasks have been remarkably useful as psychological “probes” into component mechanisms of cognitive control, such as response inhibition or goal shielding, as they enable researchers to study how the brain copes with crosstalk between conflicting representations and competing responses

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