Crowdsourcing in Cognitive and Systems Neuroscience

Brian P. Johnson*, Eran Dayan, Nitzan Censor, Leonardo G. Cohen

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

9 Scopus citations

Abstract

Behavioral research in cognitive and human systems neuroscience has been largely carried out in-person in laboratory settings. Underpowering and lack of reproducibility due to small sample sizes have weakened conclusions of these investigations. In other disciplines, such as neuroeconomics and social sciences, crowdsourcing has been extensively utilized as a data collection tool, and a means to increase sample sizes. Recent methodological advances allow scientists, for the first time, to test online more complex cognitive, perceptual, and motor tasks. Here we review the nascent literature on the use of online crowdsourcing in cognitive and human systems neuroscience. These investigations take advantage of the ability to reliably track the activity of a participant’s computer keyboard, mouse, and eye gaze in the context of large-scale studies online that involve diverse research participant pools. Crowdsourcing allows for testing the generalizability of behavioral hypotheses in real-life environments that are less accessible to lab-designed investigations. Crowdsourcing is further useful when in-laboratory studies are limited, for example during the current COVID-19 pandemic. We also discuss current limitations of crowdsourcing research, and suggest pathways to address them. We conclude that online crowdsourcing is likely to widen the scope and strengthen conclusions of cognitive and human systems neuroscience investigations.

Original languageEnglish
Pages (from-to)425-437
Number of pages13
JournalNeuroscientist
Volume28
Issue number5
DOIs
StatePublished - Oct 2022

Funding

FundersFunder number
National Institutes of Health
National Institute of Neurological Disorders and StrokeZIANS002978

    Keywords

    • behavioral neuroscience
    • cognitive neuroscience
    • crowdsourcing
    • motor control
    • motor learning
    • systems neuroscience

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