Data-driven approaches in the investigation of social perception

Ralph Adolphs*, Lauri Nummenmaa, Alexander Todorov, James V. Haxby

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

33 Citations (Scopus)

Abstract

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 eye tracking studies in autism. We conclude with suggestions for particular topics that seem ripe for data-driven approaches, as well as caveats and limitations.

Original languageEnglish
JournalPHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY B: BIOLOGICAL SCIENCES
Volume371
Issue number1693
DOIs
Publication statusPublished - May 2016
MoE publication typeA1 Journal article-refereed

Keywords

  • Ecological validity
  • Face space
  • Intersubject brain correlation
  • Social neuroscience
  • Social perception

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