No abstract

Threat generalization to novel instances is central to learning and our under- standing of anxiety. Most previous work has investigated threat generalization based on the perceptual similarity between past and novel stimuli. Few studies have explored rule-based generalization based on higher-order, non-perceptual relations despite their importance for cognitive flexibility. This bias has resulted in neural models of threat generalization that are ill-equipped to account for abstract, conceptual forms of learning. In order to measure rule-based general- ization of threat without perceptual similarity, we developed a novel paradigm that prevents perceptual features from gaining predictive value. Our results demonstrate that participants spontaneously inferred the correct abstract rule determining reinforcement contingencies and used it to successfully generalize their behavioural threat responses (expectancy ratings, skin conductance re- sponses, and heart rate responses). Our results further show that participants were able to flexibly adapt their responses to a mid-session contingency rever- sal. We interpret our results in the context of current neural models of threat generalization and argue that association cortices play a more important role than previously assumed. These findings have implications for our understand- ing of psychiatric disorders, such as anxiety, depression, or posttraumatic stress disorder.