Explicit knowledge of task structure is a primary determinant of human model-based action

Pedro Castro-Rodrigues, Thomas Akam, Ivar Snorasson, Marta Camacho, Vitor Paixão, Ana Maia, J. Bernardo Barahona-Corrêa, Peter Dayan, H. Blair Simpson, Rui M. Costa and Albino J. Oliveira-Maia ()
Additional contact information
Pedro Castro-Rodrigues: Champalimaud Foundation
Thomas Akam: Champalimaud Foundation
Ivar Snorasson: New York State Psychiatric Institute
Marta Camacho: Champalimaud Foundation
Vitor Paixão: Champalimaud Foundation
Ana Maia: Champalimaud Foundation
J. Bernardo Barahona-Corrêa: Champalimaud Foundation
Peter Dayan: Max Planck Institute for Biological Cybernetics
H. Blair Simpson: New York State Psychiatric Institute
Rui M. Costa: Champalimaud Foundation
Albino J. Oliveira-Maia: Champalimaud Foundation

Nature Human Behaviour, 2022, vol. 6, issue 8, 1126-1141

Abstract: Abstract Explicit information obtained through instruction profoundly shapes human choice behaviour. However, this has been studied in computationally simple tasks, and it is unknown how model-based and model-free systems, respectively generating goal-directed and habitual actions, are affected by the absence or presence of instructions. We assessed behaviour in a variant of a computationally more complex decision-making task, before and after providing information about task structure, both in healthy volunteers and in individuals suffering from obsessive-compulsive or other disorders. Initial behaviour was model-free, with rewards directly reinforcing preceding actions. Model-based control, employing predictions of states resulting from each action, emerged with experience in a minority of participants, and less in those with obsessive-compulsive disorder. Providing task structure information strongly increased model-based control, similarly across all groups. Thus, in humans, explicit task structural knowledge is a primary determinant of model-based reinforcement learning and is most readily acquired from instruction rather than experience.

Date: 2022
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DOI: 10.1038/s41562-022-01346-2

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