Abstract
According to the two-systems account of theory of mind (ToM), understanding mental states of others involves both fast social-perceptual processes, as well as slower, reflexive cognitive operations (Frith and Frith, 2008; Apperly and Butterfill, 2009). To test the respective roles of specific abilities in either of these processes we administered 15 experimental procedures to a large sample of 343 participants, testing ability in face recognition and holistic perception, language, and reasoning. ToM was measured by a set of tasks requiring ability to track and to infer complex emotional and mental states of others from faces, eyes, spoken language, and prosody. We used structural equation modeling to test the relative strengths of a social-perceptual (face processing related) and reflexive-cognitive (language and reasoning related) path in predicting ToM ability. The two paths accounted for 58% of ToM variance, thus validating a general two-systems framework. Testing specific predictor paths revealed language and face recognition as strong and significant predictors of ToM. For reasoning, there were neither direct nor mediated effects, albeit reasoning was strongly associated with language. Holistic face perception also failed to show a direct link with ToM ability, while there was a mediated effect via face recognition. These results highlight the respective roles of face recognition and language for the social brain, and contribute closer empirical specification of the general two-systems account.
Highlights
The ability to make sense of the behavior of others is fundamental for social interaction (Hampton et al, 2008; Slaughter et al, 2015)
In the present study we provide an empirical test of this theoretical framework, expecting that individual differences in theory of mind (ToM) are predicted by individual differences in holistic face perception and face recognition as perceptual processed and by language and reasoning as cognitive processes
Comparative fit index (CFI = 0.952) as well as root-mean square error of approximation (RMSEA) and its confidence interval (RMSEA = 0.034, 90% CI for RMSEA = [0.018, 0.048]) both indicated good or very good model fit, respectively. Such results patterns with conflicting results from the χ2 test and alternative fit indices are frequent in structural equation modeling (SEM) studies
Summary
The ability to make sense of the behavior of others is fundamental for social interaction (Hampton et al, 2008; Slaughter et al, 2015). Newer findings from research fields such as developmental psychology, social neuroscience, and research on disorders characterized by social deficits (e.g., autism, schizophrenia) showed that ToM is a complex construct comprising various processes (Mitchell, 2005; Kennedy and Adolphs, 2012; Schaafsma et al, 2015; Rice et al, 2016). Understanding and predicting behavior of others certainly involves attribution and/or inferring feelings, intentions, and beliefs from observable cues conveyed in human action, motion, and facial expression (Schaafsma et al, 2015).
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