Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Letter
  • Published:

Spontaneous neural encoding of social network position

Nature Human Behaviour volume 1, Article number: 0072 (2017) Cite this article

Subjects

Abstract

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.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

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.

Similar content being viewed by others

References

  1. Shultz, S. & Dunbar, R. I. M. Bondedness and sociality. Behaviour 147, 775–803 (2010).

    Article  Google Scholar 

  2. Dunbar, R. I. M. & Shultz, S. Evolution in the social brain. Science 317, 1344–1347 (2007).

    Article  CAS  PubMed  Google Scholar 

  3. Ellwardt, L., Labianca, G. & Wittek, R. Who are the objects of positive and negative gossip at work? Soc. Networks 34, 193–205 (2012).

    Article  Google Scholar 

  4. Burt, R. S., Kilduff, M. & Tasselli, S. Social network analysis: foundations and frontiers on advantage. Annu. Rev. Psychol. 64, 527–547 (2013).

    Article  PubMed  Google Scholar 

  5. Burt, R. S. & Knez, M. Kinds of third-party effects on trust. Ration. Soc. 7, 255–292 (1995).

    Article  Google Scholar 

  6. Brent, L. J. N. Friends of friends: are indirect connections in social networks important to animal behaviour? Anim. Behav. 103, 211–222 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  7. Uleman, J. S ., Newman, L. S. & Moskowitz, G. B. in Advances in Experimental Social Psychology Vol. 28 (ed. Zanna, P. ) 211–279 (Academic, 1996).

    Google Scholar 

  8. Todorov, A., Gobbini, M. I., Evans, K. K. & Haxby, J. V. Spontaneous retrieval of affective person knowledge in face perception. Neuropsychologia 45, 163–173 (2007).

    Article  PubMed  Google Scholar 

  9. Bonacich, P. Power and centrality: a family of measures. Am. J. Sociol. 92, 1170–1182 (1987).

    Article  Google Scholar 

  10. Kriegeskorte, N., Mur, M. & Bandettini, P. Representational similarity analysis: connecting the branches of systems neuroscience. Front. Syst. Neurosci. 2, 4 (2008).

    PubMed  PubMed Central  Google Scholar 

  11. Chikazoe, J., Lee, D. H., Kriegeskorte, N. & Anderson, A. K. Population coding of affect across stimuli, modalities and individuals. Nat. Neurosci. 17, 1114–1122 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Tennie, C., Frith, U. & Frith, C. D. Reputation management in the age of the world-wide web. Trends Cogn. Sci. 14, 482–488 (2010).

    Article  PubMed  Google Scholar 

  13. Krienen, F. M., Tu, P.-C. & Buckner, R. L. Clan mentality: evidence that the medial prefrontal cortex responds to close others. J. Neurosci. 30, 13906–13915 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Parkinson, C., Liu, S. & Wheatley, T. A common cortical metric for spatial, temporal, and social distance. J. Neurosci. 34, 1979–1987 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Gauthier, B. & van Wassenhove, V. Time is not space: core computations and domain-specific networks for mental travels. J. Neurosci. 36, 11891–11903 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Yamazaki, Y., Hashimoto, T. & Iriki, A. The posterior parietal cortex and non-spatial cognition. F1000 Biol. Rep. 1, 74 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  17. Parkinson, C. & Wheatley, T. Old cortex, new contexts: re-purposing spatial perception for social cognition. Front. Hum. Neurosci. 7, 645 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  18. Parkinson, C. & Wheatley, T. The repurposed social brain. Trends Cogn. Sci. 19, 133–141 (2015).

    Article  PubMed  Google Scholar 

  19. Tavares, R. M. et al. A map for social navigation in the human brain. Neuron 87, 231–243 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Fowler, J. H., Dawes, C. T. & Christakis, N. A. Model of genetic variation in human social networks. Proc. Natl Acad. Sci. USA 106, 1720–1724 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Burt, R. S. Network-related personality and the agency question: multirole evidence from a virtual world. Am. J. Sociol. 118, 543–591 (2012).

    Article  Google Scholar 

  22. Wagner, D. D., Haxby, J. V. & Heatherton, T. F. The representation of self and person knowledge in the medial prefrontal cortex. Wiley Interdiscip. Rev. Cogn. Sci. 3, 451–470 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  23. Hassabis, D. et al. Imagine all the people: how the brain creates and uses personality models to predict behavior. Cereb. Cortex 24, 1979–1987 (2014).

    Article  PubMed  Google Scholar 

  24. Kriegeskorte, N., Formisano, E., Sorger, B. & Goebel, R. Individual faces elicit distinct response patterns in human anterior temporal cortex. Proc. Natl Acad. Sci. USA 104, 20600–20605 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Nestor, A., Plaut, D. C. & Behrmann, M. Unraveling the distributed neural code of facial identity through spatiotemporal pattern analysis. Proc. Natl Acad. Sci. USA 108, 9998–10003 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Feiler, D. C. & Kleinbaum, A. M. Popularity, similarity, and the network extraversion bias. Psychol. Sci. 26, 593–603 (2015).

    Article  PubMed  Google Scholar 

  27. Zerubavel, N., Bearman, P. S., Weber, J. & Ochsner, K. N. Neural mechanisms tracking popularity in real-world social networks. Proc. Natl Acad. Sci. USA 112, 15072–15077 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Jones, B. C. et al. Facial cues of dominance modulate the short-term gaze-cuing effect in human observers. Proc. R. Soc. B 277, 617–624 (2010).

    Article  PubMed  Google Scholar 

  29. Dalmaso, M., Pavan, G., Castelli, L. & Galfano, G. Social status gates social attention in humans. Biol. Lett. 8, 450–452 (2012).

    Article  PubMed  Google Scholar 

  30. Klein, J. T., Shepherd, S. V. & Platt, M. L. Social attention and the brain. Curr. Biol. 19, R958–R962 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Shepherd, S. V., Deaner, R. O. & Platt, M. L. Social status gates social attention in monkeys. Curr. Biol. 16, R119–R120 (2006).

    Article  CAS  PubMed  Google Scholar 

  32. Marsh, A. A., Blair, K. S., Jones, M. M., Soliman, N. & Blair, R. J. R. Dominance and submission: the ventrolateral prefrontal cortex and responses to status cues. J. Cogn. Neurosci. 21, 713–724 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  33. Cloutier, J. & Gyurovski, I. Ventral medial prefrontal cortex and person evaluation: forming impressions of others varying in financial and moral status. Neuroimage 100, 535–543 (2014).

    Article  PubMed  Google Scholar 

  34. Karafin, M. S., Tranel, D. & Adolphs, R. Dominance attributions following damage to the ventromedial prefrontal cortex. J. Cogn. Neurosci. 16, 1796–1804 (2004).

    Article  PubMed  Google Scholar 

  35. Pinker, S. Decline of violence: taming the devil within us. Nature 478, 309–311 (2011).

    Article  CAS  PubMed  Google Scholar 

  36. Grossman, E. D., Battelli, L. & Pascual-Leone, A. Repetitive TMS over posterior STS disrupts perception of biological motion. Vision Res. 45, 2847–2853 (2005).

    Article  PubMed  Google Scholar 

  37. Mukamel, R., Ekstrom, A. D., Kaplan, J., Iacoboni, M. & Fried, I. Single-neuron responses in humans during execution and observation of actions. Curr. Biol. 20, 750–756 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Wheatley, T., Milleville, S. C. & Martin, A. Understanding animate agents: distinct roles for the social network and mirror system. Psychol. Sci. 18, 469–474 (2007).

    Article  PubMed  Google Scholar 

  39. Burt, R. S. Structural Holes: The Social Structure of Competition (Harvard Univ. Press, 1992).

    Book  Google Scholar 

  40. Kleinbaum, A. M., Jordan, A. H. & Audia, P. G. An altercentric perspective on the origins of brokerage in social networks: how perceived empathy moderates the self-monitoring effect. Organ. Sci. 26, 1226–1242 (2015).

    Article  Google Scholar 

  41. R Core Development Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2012).

  42. Csardi, G. & Nepusz, T. The igraph software package for complex network research. InterJ. Complex Syst. 1695 (2006).

  43. Connolly, A. C. et al. The representation of biological classes in the human brain. J. Neurosci. 32, 2608–2618 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Said, C. P., Moore, C. D., Engell, A. D. & Haxby, J. V. Distributed representations of dynamic facial expressions in the superior temporal sulcus. J. Vis. 10, 1–12 (2010).

    Article  Google Scholar 

  45. Bates, D., Mächler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48 (2015).

    Article  Google Scholar 

  46. Satterthhwaite, F. E. An approximate distribution of estimates of variance components. Biometrics 2, 110–114 (1946).

    Article  Google Scholar 

  47. Kuznetsova, A., Brockhoff, P. B. & Christensen, R. H. B. lmerTest: tests in linear mixed effects models. R Package v 2.0-33 (CRAN, 2016).

  48. Cox, R. W. AFNI: software for analysis and visualization of functional magnetic resonance neuroimages. Comput. Biomed. Res. 29, 162–173 (1996).

    Article  CAS  PubMed  Google Scholar 

  49. Hanke, M. et al. PyMVPA: a unifying approach to the analysis of neuroscientific data. Front. Neuroinform. 3, 3 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  50. Oliphant, T. E. SciPy: open source scientific tools for Python. Comput. Sci. Eng. 9, 10–20 (2007).

    Article  CAS  Google Scholar 

  51. Talairach, J. & Tournoux, P. Co-Planar Stereotaxis Atlas of the Human Brain (Thieme Medical, 1988).

    Google Scholar 

  52. Winkler, A. M., Ridgway, G. R., Webster, M. A., Smith, S. M. & Nichols, T. E. Permutation inference for the general linear model. Neuroimage 92, 381–397 (2014).

    Article  PubMed  Google Scholar 

  53. Jenkinson, M ., Beckmann, C. F ., Behrens, T. E. J ., Woolrich, M. W. & Smith, S. M. FSL. NeuroImage 62, 782–790 (2012).

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

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

Authors and Affiliations

  1. Department of Psychology, University of California, Los Angeles, 1285 Franz Hall, Box 951563, Los Angeles, 90095, California, USA

    Carolyn Parkinson

  2. Tuck School of Business, Dartmouth College, 100 Tuck Hall, Hanover, 03755, New Hampshire, USA

    Adam M. Kleinbaum

  3. Department of Psychological and Brain Sciences, Dartmouth College, 6207 Moore Hall, Hanover, 03755, New Hampshire, USA

    Thalia Wheatley

Authors
  1. Carolyn Parkinson
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Adam M. Kleinbaum
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Thalia Wheatley
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

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.

Corresponding author

Correspondence to Carolyn Parkinson.

Ethics declarations

Competing interests

The authors declare no competing interests.

Supplementary information

Supplementary Information

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

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

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

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1038/s41562-017-0072

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing