Abstract representations of events arise from mental errors in learning and memory.

ABSTRACT: Humans are adept at uncovering abstract associations in the world around them, yet the underlying mechanisms remain poorly understood. Intuitively, learning the higher-order structure of statistical relationships should involve complex mental processes. Here we propose an alternative perspective: that higher-order associations instead arise from natural errors in learning and memory. Using the free energy principle, which bridges information theory and Bayesian inference, we derive a maximum entropy model of people's internal representations of the transitions between stimuli. Importantly, our model (i) affords a concise analytic form, (ii) qualitatively explains the effects of transition network structure on human expectations, and (iii) quantitatively predicts human reaction times in pro

SUBMITTER: Lynn CW 

PROVIDER: S-EPMC7210268 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature