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

N. Menghi, F. Silvestrin, L. Pascolini, W. Penny

Research output: Contribution to journalArticlepeer-review

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.
Original languageEnglish
Article number107860
JournalNeurobiology of Learning and Memory
Volume206
Early online date10 Nov 2023
DOIs
Publication statusE-pub ahead of print - 10 Nov 2023

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