Modelling human behaviour in cognitive tasks with latent dynamical systems

Paul I. Jaffe (), Russell A. Poldrack, Robert J. Schafer and Patrick G. Bissett
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Paul I. Jaffe: Stanford University
Russell A. Poldrack: Stanford University
Robert J. Schafer: Lumos Labs
Patrick G. Bissett: Stanford University

Nature Human Behaviour, 2023, vol. 7, issue 6, 986-1000

Abstract: Abstract Response time data collected from cognitive tasks are a cornerstone of psychology and neuroscience research, yet existing models of these data either make strong assumptions about the data-generating process or are limited to modelling single trials. We introduce task-DyVA, a deep learning framework in which expressive dynamical systems are trained to reproduce sequences of response times observed in data from individual human subjects. Models fitted to a large task-switching dataset captured subject-specific behavioural differences with high temporal precision, including task-switching costs. Through perturbation experiments and analyses of the models’ latent dynamics, we find support for a rational account of switch costs in terms of a stability–flexibility trade-off. Thus, our framework can be used to discover interpretable cognitive theories that explain how the brain dynamically gives rise to behaviour.

Date: 2023
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DOI: 10.1038/s41562-022-01510-8

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