Revealing the information contents of memory within the stimulus information representation framework

Schyns, P. G. , Zhan, J., Jack, R. E. and Ince, R. A.A. (2020) Revealing the information contents of memory within the stimulus information representation framework. Proceedings of the Royal Society of London Series B: Biological Sciences, 375, 20190705. (doi: 10.1098/rstb.2019.0705) (PMID:32248774)

[img]
Preview
Text
211486.pdf - Published Version
Available under License Creative Commons Attribution.

1MB

Abstract

The information contents of memory are the cornerstone of the most influential models in cognition. To illustrate, consider that in predictive coding, a prediction implies that specific information is propagated down from memory through the visual hierarchy. Likewise, recognizing the input implies that sequentially accrued sensory evidence is successfully matched with memorized information (categorical knowledge). Although the existing models of prediction, memory, sensory representation and categorical decision are all implicitly cast within an information processing framework, it remains a challenge to precisely specify what this information is, and therefore where, when and how the architecture of the brain dynamically processes it to produce behaviour. Here, we review a framework that addresses these challenges for the studies of perception and categorization–stimulus information representation (SIR). We illustrate how SIR can reverse engineer the information contents of memory from behavioural and brain measures in the context of specific cognitive tasks that involve memory. We discuss two specific lessons from this approach that generally apply to memory studies: the importance of task, to constrain what the brain does, and of stimulus variations, to identify the specific information contents that are memorized, predicted, recalled and replayed.

Item Type:Articles
Additional Information:Funding: This study was funded by EPSRC (grant no. MURI 1720461).
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Jack, Professor Rachael and Zhan, Dr Jiayu and Ince, Dr Robin and Schyns, Professor Philippe
Authors: Schyns, P. G., Zhan, J., Jack, R. E., and Ince, R. A.A.
College/School:College of Medical Veterinary and Life Sciences > School of Psychology & Neuroscience
College of Science and Engineering > School of Psychology
Journal Name:Proceedings of the Royal Society of London Series B: Biological Sciences
Publisher:The Royal Society
ISSN:0962-8452
ISSN (Online):1471-2954
Published Online:06 April 2020
Copyright Holders:Copyright © 2020 The Authors
First Published:First published in Proceedings of the Royal Society of London Series B: Biological Sciences 375:20190705
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
304240Beyond Pairwise Connectivity: developing an information theoretic hypergraph methodology for multi-modal resting state neuroimaging analysisRobin InceWellcome Trust (WELLCOTR)214120/Z/18/ZNP - Centre for Cognitive Neuroimaging (CCNi)
307582tbcPhilippe SchynsThe Royal Society (ROYSOC)RSWF\R3\183002NP - Centre for Cognitive Neuroimaging (CCNi)
172413Brain Algorithmics: Reverse Engineering Dynamic Information Processing Networks from MEG time seriesPhilippe SchynsWellcome Trust (WELLCOTR)107802/Z/15/ZNP - Centre for Cognitive Neuroimaging (CCNi)