Header

UZH-Logo

Maintenance Infos

Learning what to see in a changing world


Schmack, Katharina; Weilnhammer, Veith; Heinzle, Jakob; Stephan, Klaas E; Sterzer, Philipp (2016). Learning what to see in a changing world. Frontiers in Human Neuroscience:10:263.

Abstract

Visual perception is strongly shaped by expectations, but it is poorly understood how such perceptual expectations are learned in our dynamic sensory environment. Here, we applied a Bayesian framework to investigate whether perceptual expectations are continuously updated from different aspects of ongoing experience. In two experiments, human observers performed an associative learning task in which rapidly changing expectations about the appearance of ambiguous stimuli were induced. We found that perception of ambiguous stimuli was biased by both learned associations and previous perceptual outcomes. Computational modeling revealed that perception was best explained by a model that continuously updated priors from associative learning and perceptual history and combined these priors with the current sensory information in a probabilistic manner. Our findings suggest that the construction of visual perception is a highly dynamic process that incorporates rapidly changing expectations from different sources in a manner consistent with Bayesian learning and inference.

Abstract

Visual perception is strongly shaped by expectations, but it is poorly understood how such perceptual expectations are learned in our dynamic sensory environment. Here, we applied a Bayesian framework to investigate whether perceptual expectations are continuously updated from different aspects of ongoing experience. In two experiments, human observers performed an associative learning task in which rapidly changing expectations about the appearance of ambiguous stimuli were induced. We found that perception of ambiguous stimuli was biased by both learned associations and previous perceptual outcomes. Computational modeling revealed that perception was best explained by a model that continuously updated priors from associative learning and perceptual history and combined these priors with the current sensory information in a probabilistic manner. Our findings suggest that the construction of visual perception is a highly dynamic process that incorporates rapidly changing expectations from different sources in a manner consistent with Bayesian learning and inference.

Statistics

Citations

Dimensions.ai Metrics
11 citations in Web of Science®
8 citations in Scopus®
7 citations in Microsoft Academic
Google Scholar™

Altmetrics

Downloads

71 downloads since deposited on 10 Oct 2016
42 downloads since 12 months
Detailed statistics

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Economics
Dewey Decimal Classification:330 Economics
Scopus Subject Areas:Social Sciences & Humanities > Neuropsychology and Physiological Psychology
Life Sciences > Neurology
Health Sciences > Psychiatry and Mental Health
Life Sciences > Biological Psychiatry
Life Sciences > Behavioral Neuroscience
Language:English
Date:31 May 2016
Deposited On:10 Oct 2016 07:04
Last Modified:29 Apr 2020 22:06
Publisher:Frontiers Research Foundation
ISSN:1662-5161
OA Status:Gold
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.3389/fnhum.2016.00263

Download

Gold Open Access

Download PDF  'Learning what to see in a changing world'.
Preview
Content: Published Version
Filetype: PDF
Size: 2MB
View at publisher
Licence: Creative Commons: Attribution 4.0 International (CC BY 4.0)