Abstract
Cognitive stability and flexibility are core functions in the successful pursuit of behavioral goals. While there is evidence for a common frontoparietal network underlying both functions and for a key role of dopamine in the modulation of flexible versus stable behavior, the exact neurocomputational mechanisms underlying those executive functions and their adaptation to environmental demands are still unclear. In this work we study the neurocomputational mechanisms underlying cue based task switching (flexibility) and distractor inhibition (stability) in a paradigm specifically designed to probe both functions. We develop a physiologically plausible, explicit model of neural networks that maintain the currently active task rule in working memory and implement the decision process. We simplify the four-choice decision network to a nonlinear drift-diffusion process that we canonically derive from a generic winner-take-all network model. By fitting our model to the behavioral data of individual subjects, we can reproduce their full behavior in terms of decisions and reaction time distributions in baseline as well as distractor inhibition and switch conditions. Furthermore, we predict the individual hemodynamic response timecourse of the rule-representing network and localize it to a frontoparietal network including the inferior frontal junction area and the intraparietal sulcus, using functional magnetic resonance imaging. This refines the understanding of task-switch-related frontoparietal brain activity as reflecting attractor-like working memory representations of task rules. Finally, we estimate the subject-specific stability of the rule-representing attractor states in terms of the minimal action associated with a transition between different rule states in the phase-space of the fitted models. This stability measure correlates with switching-specific thalamocorticostriatal activation, i.e., with a system associated with flexible working memory updating and dopaminergic modulation of cognitive flexibility. These results show that stochastic dynamical systems can implement the basic computations underlying cognitive stability and flexibility and explain neurobiological bases of individual differences.
Highlights
The successful pursuit of behavioral goals often requires the stable maintenance of behavioral plans even in the face of distracting influences from the environment
We find that subjects with more stable rule representation networks require during task switching the increased activation of a thalamocorticostriatal network, which is associated with the updating of information in working memory [17,30,31,32] and dopaminergic modulation of cognitive flexibility [17,33]
Participants had to respond fast and accurately by button presses to digits between 1 and 9 that were presented in different shades of gray against a black background
Summary
The successful pursuit of behavioral goals often requires the stable maintenance of behavioral plans even in the face of distracting influences from the environment. Important is the ability to flexibly adapt behavior to changing environmental demands. These two abilities are often described as cognitive flexibility and stability and are conceptualized as component processes of the executive control of behavior [1,2]. Cognitive stability is often operationalized in delayed response tasks [3,4], in which a stimulus has to be remembered for a short time span (maintenance period) after its presentation, before a decision based on the stimulus has to be made. To test the resistance of the working memory representation, this task is often combined with the presentation of distracting stimuli during the maintenance period [5,6,7]. Cognitive flexibility can be tested in terms of reversal learning, such as in the Wisconsin Card Sorting Test [8,9], in terms of cue based switching of attention to a different stimulus or stimulus dimension within a single task [10,11], or in terms of cue based task switching [12,13,14,15] in which different tasks have to be executed on the same stimulus material
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