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Computational Evidence for Underweighting of Current Error and Overestimation of Future Error in Anxious Individuals
Published Web Location
https://doi.org/10.1016/j.bpsc.2019.12.011Abstract
Background
Real-time control of goal-directed actions requires continuous adjustments in response to both current error (i.e., distance from goal state) and predicted future error. Proportion-integral-derivative control models, which are extensively used in the automated control of industrial processes, formalize this intuition. Previous computational approaches to anxiety have separately addressed behavioral inhibition and exaggerated error processing, but a proportion-integral-derivative control approach that decomposes error processing into current and anticipated error could integrate these accounts and extend them to a real-time sensorimotor control domain.Methods
We applied a simplified proportion-derivative control model to a virtual driving task in a transdiagnostic psychiatric sample of 317 individuals and computed a drive parameter (weighting of current error) and a damping parameter (weighting of the rate of change of error, enabling adjustment based on future error).Results
Self-reported fear, but not negative affect, was selectively associated with lower drive and lower damping. Those individuals that were characterized by lower drive and damping also exhibited lower caudal anterior cingulate cortex, but not insula, volume in a structural magnetic resonance imaging analysis.Conclusions
The proportion-derivative control approach reveals that fear is specifically associated with reduced weighting of current error and overestimation of future error, resulting in both approach inhibition and overcorrecting overshoots around a goal state.Many UC-authored scholarly publications are freely available on this site because of the UC's open access policies. Let us know how this access is important for you.
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