Temporal stability of Bayesian belief updating in perceptual decision-making.

ABSTRACT: Bayesian inference suggests that perception is inferred from a weighted integration of prior contextual beliefs with current sensory evidence (likelihood) about the world around us. The perceived precision or uncertainty associated with prior and likelihood information is used to guide perceptual decision-making, such that more weight is placed on the source of information with greater precision. This provides a framework for understanding a spectrum of clinical transdiagnostic symptoms associated with aberrant perception, as well as individual differences in the general population. While behavioral paradigms are commonly used to characterize individual differences in perception as a stable characteristic, measurement reliability in these behavioral tasks is rarely assessed. To remedy this

SUBMITTER: Goodwin I 

PROVIDER: S-EPMC11335944 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature