Data-driven approaches in the investigation of social perception.
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.
['Adolphs|Ralph|R|', 'Nummenmaa|Lauri|L|', 'Todorov|Alexander|A|', 'Haxby|James V|JV|']
D003463:Cues D005145:Face D006801:Humans D007398:Interpersonal Relations D010465:Perception D012879:Skin Physiological Phenomena D012919:Social Behavior
social perception ecological validity face space intersubject brain correlation social neuroscience