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Assessing inter-individual differences with task-related functional neuroimaging

Author

Listed:
  • Maël Lebreton

    (University of Geneva
    Campus Biotech
    Universiteit van Amsterdam
    CREED, Amsterdam School of Economics (ASE), Universiteit van Amsterdam)

  • Sophie Bavard

    (Laboratoire de Neurosciences Cognitives et Computationnelles, Institut National de la Santé et de la Recherche Médicale
    Département d’Etudes Cognitives, Ecole Normale Supérieure
    Human Reinforcement Learning team, Université de Recherche Paris Sciences et Lettres)

  • Jean Daunizeau

    (Motivation, Brain & Behavior team, Institut du Cerveau et de la Moelle épinière (ICM)
    CNRS UMR 7225, INSERM U 1127, Pierre & Marie Curie University)

  • Stefano Palminteri

    (Laboratoire de Neurosciences Cognitives et Computationnelles, Institut National de la Santé et de la Recherche Médicale
    Département d’Etudes Cognitives, Ecole Normale Supérieure
    Human Reinforcement Learning team, Université de Recherche Paris Sciences et Lettres)

Abstract

Explaining and predicting individual behavioural differences induced by clinical and social factors constitutes one of the most promising applications of neuroimaging. In this Perspective, we discuss the theoretical and statistical foundations of the analyses of inter-individual differences in task-related functional neuroimaging. Leveraging a five-year literature review (July 2013–2018), we show that researchers often assess how activations elicited by a variable of interest differ between individuals. We argue that the rationale for such analyses, typically grounded in resource theory, offers an over-large analytical and interpretational flexibility that undermines their validity. We also recall how, in the established framework of the general linear model, inter-individual differences in behaviour can act as hidden moderators and spuriously induce differences in activations. We conclude with a set of recommendations and directions, which we hope will contribute to improving the statistical validity and the neurobiological interpretability of inter-individual difference analyses in task-related functional neuroimaging.

Suggested Citation

  • Maël Lebreton & Sophie Bavard & Jean Daunizeau & Stefano Palminteri, 2019. "Assessing inter-individual differences with task-related functional neuroimaging," Nature Human Behaviour, Nature, vol. 3(9), pages 897-905, September.
  • Handle: RePEc:nat:nathum:v:3:y:2019:i:9:d:10.1038_s41562-019-0681-8
    DOI: 10.1038/s41562-019-0681-8
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    Cited by:

    1. Chih-Chung Ting & Nahuel Salem-Garcia & Stefano Palminteri & Jan B. Engelmann & Maël Lebreton, 2023. "Neural and computational underpinnings of biased confidence in human reinforcement learning," Nature Communications, Nature, vol. 14(1), pages 1-18, December.
    2. Karima Chakroun & Antonius Wiehler & Ben Wagner & David Mathar & Florian Ganzer & Thilo Eimeren & Tobias Sommer & Jan Peters, 2023. "Dopamine regulates decision thresholds in human reinforcement learning in males," Nature Communications, Nature, vol. 14(1), pages 1-14, December.

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