2026-10-13T02:44:54Z https://api.figshare.com/v2/oai

oai:figshare.com:article/33774988 2026-09-15T08:26:46Z category_30391 category_30373 category_30376 category_30388 item_type_3 month_year_09_2026

chronic-stress-aversive-learning-predictability-controllability_dataset Daniyal Rajput (24469436) KIM FELMINGHAM (3099327) Chin-Hsuan Sophie Lin (17756290) Marta Garrido (8249886) Cognitive and computational psychology not elsewhere classified Cognition Decision making Sensory processes, perception and performance Chronic stress Controllability Predictability Aversive Learning Computational Modelling Volatile Kalman Filter Computational Psychiatry <p dir="ltr">This dataset contains behavioural, subjective, psychophysiological, and computational data from adults with chronic stress who completed a probabilistic aversive-learning task manipulating predictability and controllability. Measures include prediction accuracy, reaction time, subjective stress ratings, skin conductance responses, and trial-wise computational estimates of surprise, belief uncertainty, volatility, and learning rate. The dataset supports analyses of how chronic stress influences learning and stress responses under varying levels of environmental uncertainty and behavioural control.</p> 2026-09-15T08:26:46Z Dataset Dataset 10.6084/m9.figshare.33774988.v2 https://figshare.com/articles/dataset/chronic-stress-aversive-learning-predictability-controllability_dataset/33774988 CC BY 4.0