Data-driven approaches in the investigation of social perception

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  • Ralph Adolphs
    Division of the Humanities and Social Sciences, California Institute of Technology, Pasadena, CA, USA
  • Lauri Nummenmaa
    Department of Neuroscience and Biomedical Engineering, School of Science, Aalto University, Espoo, Finland
  • Alexander Todorov
    Department of Psychology, Princeton University, Princeton, NJ, USA
  • James V. Haxby
    Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, USA

説明

<jats:p>The complexity of social perception poses a challenge to traditional approaches to understand its psychological and neurobiological underpinnings. Data-driven methods are particularly well suited to tackling the often high-dimensional nature of stimulus spaces and of neural representations that characterize social perception. Such methods are more exploratory, capitalize on rich and large datasets, and attempt to discover patterns often without strict hypothesis testing. We present four case studies here: behavioural studies on face judgements, two neuroimaging studies of movies, and eyetracking studies in autism. We conclude with suggestions for particular topics that seem ripe for data-driven approaches, as well as caveats and limitations.</jats:p>

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