Distributional Learning Drives Statistical Suppression and Deafening

Overview

Journal bioRxiv

Date 2024 Sep 24

PMID 39314310

Authors

Sahil Luthra

Austin Luor

Adam T Tierney

Frederic Dick

Lori L Holt

Affiliations

Soon will be listed here.

Abstract

Significance Statement: Organisms as diverse as honeybees and humans pick up on probabilities in the world around them. People implicitly learn the likelihood of a color, price range, or even syntactic structure. How does statistical learning affect how we detect events and make decisions, especially when probabilities are completely irrelevant to the task at hand, and can change without warning? We find that people learn and track changes in perceptual probabilities irrelevant to a task and that this learning drives dynamic shifts in perception characterized by graded effects of enhancement and primarily - suppression across acoustic frequency. This can result in a remarkably long-lived 'statistical deafening' that seems maladaptive but may instead reflect use of likelihood to guide and sharpen perception.

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