Neural networks supporting social evaluation of bodies based on body shape

ABSTRACT

Body shape cues inferences regarding personality and health, but the neural processes underpinning such inferences remain poorly understood. Across two fMRI experiments, we test the extent to which neural networks associated with body perception and theory-of-mind (ToM) support social inferences based on body shape. Participants observed obese, muscular, and slim bodies that cued distinct social inferences as revealed in behavioural pilot experiments. To investigate judgment intentionality, the first fMRI experiment required participants to detect repeat presentations of bodies, whereas in fMRI Experiment 2 participants intentionally formed an impression. Body and ToM networks were localized using independent functional localisers. Experiment 1 revealed no differential network engagement for muscular or obese compared to slim bodies. By contrast, in Experiment 2, compared to slim bodies, forming impressions of muscular bodies engaged the body-network more, whereas the ToM-network was engaged more when forming impressions of obese bodies. These results demonstrate that social judgments based on body shape do not rely on a single neural mechanism, but rather on multiple mechanisms that are separately sensitive to body fat and muscularity. Moreover, dissociable responses are only apparent when intentionally forming an impression. Thus, these experiments show how segregated networks operate to extract socially-relevant information cued by body shape.

KEYWORDS:

• Functional MRI
• body perception
• theory-of-mind
• body shape

Acknowledgments

This work was funded by a grant from the Economic and Social Research Council (grant number: ES/K001884/1 to R.R.). We thank Kohinoor Darda for help constructing region of interest masks in our supplementary analyses.

Disclosure statement

No potential conflict of interest was reported by the authors.

Supplementary material

Supplemental data for this article can be accessed here.

Additional information

Funding

This work was supported by the Economic and Social Research Council [ES/K001884/1];