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The challenges and prospects of brain-based prediction of behaviour

Author

Listed:
  • Jianxiao Wu

    (Research Center Jülich
    Heinrich-Heine University Düsseldorf)

  • Jingwei Li

    (Research Center Jülich
    Heinrich-Heine University Düsseldorf)

  • Simon B. Eickhoff

    (Research Center Jülich
    Heinrich-Heine University Düsseldorf)

  • Dustin Scheinost

    (Yale School of Medicine
    Yale University
    Yale School of Medicine
    Yale School of Medicine)

  • Sarah Genon

    (Research Center Jülich
    Heinrich-Heine University Düsseldorf)

Abstract

Relating individual brain patterns to behaviour is fundamental in system neuroscience. Recently, the predictive modelling approach has become increasingly popular, largely due to the recent availability of large open datasets and access to computational resources. This means that we can use machine learning models and interindividual differences at the brain level represented by neuroimaging features to predict interindividual differences in behavioural measures. By doing so, we could identify biomarkers and neural correlates in a data-driven fashion. Nevertheless, this budding field of neuroimaging-based predictive modelling is facing issues that may limit its potential applications. Here we review these existing challenges, as well as those that we anticipate as the field develops. We focus on the impacts of these challenges on brain-based predictions. We suggest potential solutions to address the resolvable challenges, while keeping in mind that some general and conceptual limitations may also underlie the predictive modelling approach.

Suggested Citation

  • Jianxiao Wu & Jingwei Li & Simon B. Eickhoff & Dustin Scheinost & Sarah Genon, 2023. "The challenges and prospects of brain-based prediction of behaviour," Nature Human Behaviour, Nature, vol. 7(8), pages 1255-1264, August.
    • Handle: RePEc:nat:nathum:v:7:y:2023:i:8:d:10.1038_s41562-023-01670-1
    DOI: 10.1038/s41562-023-01670-1
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    Cited by:

    1. M. Lumaca & P. E. Keller & G. Baggio & V. Pando-Naude & C. J. Bajada & M. A. Martinez & J. H. Hansen & A. Ravignani & N. Joe & P. Vuust & K. Vulić & K. Sandberg, 2024. "Frontoparietal network topology as a neural marker of musical perceptual abilities," Nature Communications, Nature, vol. 15(1), pages 1-15, December.

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