PLoS Computational BiologyNeurosciencePeer-reviewed journal article
Dual process impairments in reinforcement learning and working memory systems underlie learning deficits in physiological anxiety
Jennifer SentaiD, Sonia J. BishopiD, Anne Gabrielle Eva CollinsiD
Abstract
Anxiety has been robustly linked to deficits in frontal executive function including working memory (WM) and attentional control processes. However, although anxiety has also been associated with impaired performance on learning tasks, computational investigations of reinforcement learning (RL) impairment in anxiety have yielded mixed results. WM processes are known to contribute to learning behavior in parallel to RL processes and to modulate the effective learning rate as a function of load. However, WM processes have typically not been modeled in investigations of anxiety and RL. In the current study, we leveraged an experimental paradigm (RLWM) which manipulates the relative contributions of WM and RL processes in a reinforcement learning and retention task using multiple stimulus set sizes. Using a computational model of interactive RL and WM processes, we investigated whether individual differences in physiological or cognitive anxiety impacted task performance via deficits in RL or WM. Elevated physiological, but not cognitive, anxiety scores were strongly associated with worse performance during learning and retention testing across all set sizes. Computationally, higher physiological anxiety scores were significantly related to reduced learning rate and increased rate of WM decay. To highlight the importance of modeling WM contributions to learning, we considered the effect of fitting RL models without WM modules to the data. Here we found that reduced learning performance for higher physiological anxiety was at least partially misattributed to stochastic decision noise in 9 out of 10 RL-only models considered. These findings reveal a dual-process impairment in learning in anxiety that is linked to a more physiological than cognitive anxiety phenotype. More broadly, this work also points to the importance of accounting for the contribution of WM to RL when investigating psychopathology-related deficits in learning.
- Citations
- 3
- FWCI
- 1.70
- Field percentile
- top 16%
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