Neural integration underlying naturalistic prediction flexibly adapts to varying sensory input rate.

ABSTRACT: Prediction of future sensory input based on past sensory information is essential for organisms to effectively adapt their behavior in dynamic environments. Humans successfully predict future stimuli in various natural settings. Yet, it remains elusive how the brain achieves effective prediction despite enormous variations in sensory input rate, which directly affect how fast sensory information can accumulate. We presented participants with acoustic sequences capturing temporal statistical regularities prevalent in nature and investigated neural mechanisms underlying predictive computation using MEG. By parametrically manipulating sequence presentation speed, we tested two hypotheses: neural prediction relies on integrating past sensory information over fixed time periods or fixed amounts

SUBMITTER: Baumgarten TJ 

PROVIDER: S-EPMC8113607 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature