Spontaneous neural encoding of social network position


Unlike many species that enact social behaviour in loose aggregations (such as swarms or herds), humans form groups comprising many long-term, intense, non-reproductive bonds with non-kin1. The cognitive demands of navigating such groups are thought to have significantly influenced human brain evolution2. Yet little is known about how and to what extent the human brain encodes the structure of the social networks in which it is embedded. We characterized the social network of an academic cohort (N = 275); a subset (N = 21) completed a functional magnetic resonance imaging (fMRI) study involving viewing individuals who varied in terms of ‘degrees of separation’ from themselves (social distance), the extent to which they were well-connected to well-connected others (eigenvector centrality) and the extent to which they connected otherwise unconnected individuals (brokerage). Understanding these characteristics of social network position requires tracking direct relationships, bonds between third parties and the broader network topology. Pairing network data with multi-voxel pattern analysis, we show that information about social network position is accurately perceived and spontaneously activated when encountering familiar individuals. These findings elucidate how the human brain encodes the structure of its social world and underscore the importance of integrating an understanding of social networks into the study of social perception.

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Figure 1: Social network characterization.
Figure 2: Stimulus set construction and paradigm for neuroimaging study.
Figure 3: GLM decomposition searchlight.
Figure 4: Neural encoding of social network position.


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This work was supported by a graduate fellowship from the Neukom Institute for Computational Science and a Dartmouth Graduate Alumni Research Award to C.P. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. The authors thank W. Haslett for assistance with the optical flow analysis.

Author information




C.P., A.M.K. and T.W. conceived and designed the study. C.P. and A.M.K. collected the data. C.P. analysed the data. C.P., A.M.K. and T.W. wrote the paper.

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Correspondence to Carolyn Parkinson.

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The authors declare no competing interests.

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Supplementary Figures 1–4, Supplementary Tables 1–3, Supplementary Methods, Supplementary References. (PDF 586 kb)

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Parkinson, C., Kleinbaum, A. & Wheatley, T. Spontaneous neural encoding of social network position. Nat Hum Behav 1, 0072 (2017). https://doi.org/10.1038/s41562-017-0072

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