A neurocomputational theory of action regulation predicts motor behavior in neurotypical individuals and patients with Parkinsons disease

Abstract

Surviving in an uncertain environment requires not only the ability to select the best action, but also the flexibility to withhold inappropriate actions when the environmental conditions change. Although selecting and withholding actions have been extensively studied in both human and animals, there is still lack of consensus on the mechanism underlying these action regulation functions, and more importantly, how they inter-relate. A critical gap impeding progress is the lack of a computational theory that will integrate the mechanisms of action regulation into a unified framework. The current study aims to advance our understanding by developing a neurodynamical computational theory that models the mechanism of action regulation that involves suppressing responses, and predicts how disruption of this mechanism can lead to motor deficits in Parkinsons disease (PD) patients. We tested the model predictions in neurotypical individuals and PD patients in three behavioral tasks that involve free action selection between two opposed directions, action selection in the presence of conflicting information and abandoning an ongoing action when a stop signal is presented. Our results and theory suggest an integrated mechanism of action regulation that affects both action initiation and inhibition. When this mechanism is disrupted, motor behavior is affected, leading to longer reaction times and higher error rates in action inhibition. Author SummaryHumans can rapidly regulate actions according to updated demands of the environment. A key component of action regulation is action inhibition, the failure of which contributes to various neuropsychiatric disorders. When faced with multiple choices, dealing with conflicting information, or current actions become inappropriate or unwanted, we should be able to pause or completely abandon actions. Despite extensive efforts to understand how the brain selects, pauses, and abandons actions based on environmental demands, the mechanisms underlying these action regulation functions and, perhaps more importantly, how they inter-relate remain elusive. Part of this challenge lies in the fact that these mechanisms were rarely explored together, making it difficult to develop a unified theory that explains the computational aspects of action regulation functions. The current study introduces a large-scale model that better characterizes the computations of action regulation functions, how they are implemented within brain networks that involve frontal, motor and basal ganglia (BG) circuits, and how disruption of these circuits can lead to deficits in motor behavior seen in Parkinsons disease (PD).The model was developed by studying the motor behavior of healthy individuals and PD patients in three motor tasks that involve action inhibition. Overall, the model explains many key aspects on how the brain regulates actions that involve inhibitory processes, opening new avenues for improving and developing therapeutic interventions for diseases that may involve these circuits.