Data-driven approaches in the investigation of social perception

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

Research output: Contribution to journalReview articlepeer-review

62 Scopus citations


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 (US)
JournalPhilosophical Transactions of the Royal Society B: Biological Sciences
Issue number1693
StatePublished - May 5 2016

All Science Journal Classification (ASJC) codes

  • General Biochemistry, Genetics and Molecular Biology
  • General Agricultural and Biological Sciences


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


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