Computational modeling of threat learning reveals links with anxiety and neuroanatomy in humans.

ABSTRACT: Influential theories implicate variations in the mechanisms supporting threat learning in the severity of anxiety symptoms. We use computational models of associative learning in conjunction with structural imaging to explicate links among the mechanisms underlying threat learning, their neuroanatomical substrates, and anxiety severity in humans. We recorded skin-conductance data during a threat-learning task from individuals with and without anxiety disorders (N=251; 8-50 years; 116 females). Reinforcement-learning model variants quantified processes hypothesized to relate to anxiety: threat conditioning, threat generalization, safety learning, and threat extinction. We identified the best-fitting models for these processes and tested associations among latent learning parameters, whole-b

SUBMITTER: Abend R 

PROVIDER: S-EPMC9197395 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature