Schettino Martino, Ghezzi Valerio, Ang Yuen-Siang, Duda Jessica M, Fagioli Sabrina, Mennin Douglas S, Pizzagalli Diego A, Ottaviani Cristina
Department of Psychology, Sapienza University of Rome, 00185 Rome, Italy.
Department of Social and Cognitive Computing, Institute of High Performance Computing, Agency for Science, Technology and Research, Singapore 138632, Singapore.
Brain Sci. 2021 Apr 30;11(5):585. doi: 10.3390/brainsci11050585.
Perseverative cognition (PC) is a transdiagnostic risk factor that characterizes both hypo-motivational (e.g., depression) and hyper-motivational (e.g., addiction) disorders; however, it has been almost exclusively studied within the context of the negative valence systems. The present study aimed to fill this gap by combining laboratory-based, computational and ecological assessments. Healthy individuals performed the Probabilistic Reward Task (PRT) before and after the induction of PC or a waiting period. Computational modeling was applied to dissociate the effects of PC on reward sensitivity and learning rate. Afterwards, participants underwent a one-week ecological momentary assessment of daily PC occurrence, as well as anticipatory and consummatory reward-related behavior. Induction of PC led to increased response bias on the PRT compared to waiting, likely due to an increase in learning rate but not in reward sensitivity, as suggested by computational modeling. In daily-life, PC increased the discrepancy between expected and obtained rewards (i.e., prediction error). Current converging experimental and ecological evidence suggests that PC is associated with abnormalities in the functionality of positive valence systems. Given the role of PC in the prediction, maintenance, and recurrence of psychopathology, it would be clinically valuable to extend research on this topic beyond the negative valence systems.
固执性认知(PC)是一种跨诊断风险因素,它同时表征了低动机(如抑郁症)和高动机(如成瘾)障碍;然而,几乎所有相关研究都局限于负性效价系统的背景下。本研究旨在通过结合基于实验室的、计算性的和生态学评估来填补这一空白。健康个体在诱发PC或经过等待期前后完成概率奖励任务(PRT)。应用计算建模来区分PC对奖励敏感性和学习率的影响。之后,参与者进行了为期一周的生态学瞬时评估,以评估日常PC的发生情况以及与预期和完成奖励相关的行为。与等待期相比,诱发PC导致在PRT上的反应偏差增加,计算建模表明这可能是由于学习率增加而非奖励敏感性增加所致。在日常生活中,PC增加了预期奖励与获得奖励之间的差异(即预测误差)。当前相互印证的实验和生态学证据表明,PC与正性效价系统功能异常有关。鉴于PC在精神病理学的预测、维持和复发中的作用,将该主题的研究扩展到负性效价系统之外在临床上具有重要价值。