The emergence of task-relevant representations in a nonlinear decision-making task

Menghi, N., Silvestrin, F., Pascolini, L. and Penny, W. ORCID: https://orcid.org/0000-0001-9064-1191 (2023) The emergence of task-relevant representations in a nonlinear decision-making task. Neurobiology of Learning and Memory, 206. ISSN 1074-7427

Preview

PDF (Menghi_etal_2023_NLM) - Published Version Available under License Creative Commons Attribution Non-commercial No Derivatives. Download (6MB) | Preview

Abstract

This paper describes the relationship between performance in a decision-making task and the emergence of task-relevant representations. Participants learnt two tasks in which the appropriate response depended on multiple relevant stimuli and the underlying stimulus-outcome associations were governed by a latent feature that participants could discover. We divided participants into good and bad performers based on their overall classification rate and computed behavioural accuracy for each feature value. We found that participants with better performance had a better representation of the latent feature space. We then used representation similarity analysis on Electroencephalographic (EEG) data to identify when these representations emerge. We were able to decode task-relevant representations in a time window emerging 700ms after stimulus presentation, but only for participants with good task performance. Our findings suggest that, in order to make good decisions, it is necessary to create and extract a low-dimensional representation of the task at hand.

Item Type:	Article
Uncontrolled Keywords:	3*,uoa4 ,/dk/atira/pure/researchoutput/REFrank/3_
Faculty \ School:	Faculty of Social Sciences > School of Psychology
UEA Research Groups:	Faculty of Social Sciences > Research Centres > Centre for Behavioural and Experimental Social Sciences
Depositing User:	LivePure Connector
Date Deposited:	15 Nov 2023 11:55
Last Modified:	29 Oct 2024 13:30
URI:	https://ueaeprints.uea.ac.uk/id/eprint/93641
DOI:	10.1016/j.nlm.2023.107860

Downloads

Actions (login required)

View Item