Senta Jennifer D, Bishop Sonia J, Collins Anne G E
Helen Wills Neuroscience Institute, University of California, Berkeley, California, United States of America.
School of Psychology, Trinity College Dublin, Dublin, Ireland.
PLoS Comput Biol. 2025 Sep 26;21(9):e1012872. doi: 10.1371/journal.pcbi.1012872. eCollection 2025 Sep.
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.
焦虑与包括工作记忆（WM）和注意力控制过程在内的额叶执行功能缺陷密切相关。然而，尽管焦虑也与学习任务表现受损有关，但对焦虑中强化学习（RL）损伤的计算研究结果却喜忧参半。已知WM过程与RL过程并行地促进学习行为，并根据负荷调节有效学习率。然而，在焦虑和RL的研究中，WM过程通常没有被建模。在当前的研究中，我们利用了一种实验范式（RLWM），该范式在使用多种刺激集大小的强化学习和记忆任务中操纵WM和RL过程的相对贡献。使用交互式RL和WM过程的计算模型，我们研究了生理或认知焦虑的个体差异是否通过RL或WM缺陷影响任务表现。在所有刺激集大小的学习和记忆测试中，生理焦虑得分升高（而非认知焦虑得分升高）与较差的表现密切相关。在计算上，较高的生理焦虑得分与学习率降低和WM衰退率增加显著相关。为了突出对学习建模时考虑WM贡献的重要性，我们考虑了将没有WM模块的RL模型拟合到数据上的效果。在这里，我们发现，在考虑的10个仅RL模型中有9个中，较高生理焦虑导致的学习表现下降至少部分被错误地归因于随机决策噪声。这些发现揭示了焦虑中学习的双过程损伤，它与生理焦虑表型的关联大于认知焦虑表型。更广泛地说，这项工作还指出，在研究与精神病理学相关的学习缺陷时，考虑WM对RL的贡献的重要性。
