Dynamic construction of reduced representations in the brain for perceptual decision behavior

Zhan, J., Ince, R. A.A. , Van Rijsbergen, N. and Schyns, P. G. (2019) Dynamic construction of reduced representations in the brain for perceptual decision behavior. Current Biology, 29(2), 319-326.e4. (doi:10.1016/j.cub.2018.11.049) (PMID:30639108) (PMCID:PMC6345582)

[img]
Preview
Text
173793.pdf - Published Version
Available under License Creative Commons Attribution.

2MB

Abstract

Summary: Over the past decade, extensive studies of the brain regions that support face, object, and scene recognition suggest that these regions have a hierarchically organized architecture that spans the occipital and temporal lobes [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14], where visual categorizations unfold over the first 250 ms of processing [15, 16, 17, 18, 19]. This same architecture is flexibly involved in multiple tasks that require task-specific representations—e.g. categorizing the same object as “a car” or “a Porsche.” While we partly understand where and when these categorizations happen in the occipito-ventral pathway, the next challenge is to unravel how these categorizations happen. That is, how does high-dimensional input collapse in the occipito-ventral pathway to become low dimensional representations that guide behavior? To address this, we investigated what information the brain processes in a visual perception task and visualized the dynamic representation of this information in brain activity. To do so, we developed stimulus information representation (SIR), an information theoretic framework, to tease apart stimulus information that supports behavior from that which does not. We then tracked the dynamic representations of both in magneto-encephalographic (MEG) activity. Using SIR, we demonstrate that a rapid (∼170 ms) reduction of behaviorally irrelevant information occurs in the occipital cortex and that representations of the information that supports distinct behaviors are constructed in the right fusiform gyrus (rFG). Our results thus highlight how SIR can be used to investigate the component processes of the brain by considering interactions between three variables (stimulus information, brain activity, behavior), rather than just two, as is the current norm.

Item Type:Articles
Additional Information:P.G.S. received support from the Wellcome Trust (Senior Investigator Award, UK; 107802) and the Multidisciplinary University Research Initiative/Engineering and Physical Sciences Research Council (USA, UK; 172046-01).
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Schyns, Professor Philippe and Zhan, Miss Jiayu and Van Rijsbergen, Dr Nicola and Ince, Dr Robin
Authors: Zhan, J., Ince, R. A.A., Van Rijsbergen, N., and Schyns, P. G.
College/School:College of Medical Veterinary and Life Sciences > Institute of Neuroscience and Psychology
Journal Name:Current Biology
Publisher:Elsevier
ISSN:0960-9822
ISSN (Online):1879-0445
Published Online:10 January 2019
Copyright Holders:Copyright © 2018 The Authors
First Published:First published in Current Biology 29(1):319-326.e4
Publisher Policy:Reproduced under a Creative Commons License

University Staff: Request a correction | Enlighten Editors: Update this record

Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
698281Brain Algorithmics: Reverse Engineering Dynamic Information Processing Networks from MEG time seriesPhilippe SchynsWellcome Trust (WELLCOTR)107802/Z/15/ZINP - CENTRE FOR COGNITIVE NEUROIMAGING
700661Visual Commonsense for Scene UnderstandingPhilippe SchynsEngineering and Physical Sciences Research Council (EPSRC)EP/N019261/1INP - CENTRE FOR COGNITIVE NEUROIMAGING