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.

Physiological synchrony is associated with attraction in a blind date setting

Abstract

Humans are social animals whose well-being is shaped by the ability to attract and connect with one another, often through brief interactions. In addition to physical features, a choreography of movements, physical reactions and subtle expressions may help promote attraction. Here, we measured the physiological dynamics between pairs of participants during real-life dating interactions outside the laboratory. Participants wore eye-tracking glasses with embedded cameras and devices to measure physiological signals including heart rate and skin conductance. We found that overt signals such as smiles, laughter, eye gaze or the mimicry of those signals were not significantly associated with attraction. Instead, attraction was predicted by synchrony in heart rate and skin conductance between partners, which are covert, unconscious and difficult to regulate. Our findings suggest that interacting partners’ attraction increases and decreases as their subconscious arousal levels rise and fall in synchrony.

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

Relevant articles

Open Access articles citing this article.

Access options

Buy article

Get time limited or full article access on ReadCube.

$32.00

All prices are NET prices.

Fig. 1: Experimental set-up and outline.
Fig. 2: Correlation table summarizing associations between real dyad’s expressions, eye gaze and physiology across three interaction time periods (based on Spearman’s rank-order correlations with false discovery rate correction, N = 162).
Fig. 3: Line graphs representing slopes extracted from the multilevel linear mixed model.
Fig. 4: Face and body AOIs.

Data availability

The datasets generated during and/or analysed during the current study are available at DataverseNL: https://dataverse.nl/dataset.xhtml?persistentId=doi:10.34894/RFUGGD.

Code availability

The codes generated during and/or analysed during the current study are available at DataverseNL: https://dataverse.nl/dataset.xhtml?persistentId=doi:10.34894/RFUGGD.

References

  1. Walster, E., Aronson, V., Abrahams, D. & Rottman, L. Importance of physical attractiveness in dating behavior. J. Pers. Soc. Psychol. 4, 508–516 (1966).

    CAS  PubMed  Google Scholar 

  2. Eastwick, P. W. & Finkel, E. J. Sex differences in mate preferences revisited: do people know what they initially desire in a romantic partner? J. Pers. Soc. Psychol. 94, 245–264 (2008).

    PubMed  Google Scholar 

  3. Tahhan, D. A. Touching at depth: the potential of feeling and connection. Emot. Sp. Soc. 7, 45–53 (2013).

    Google Scholar 

  4. Wheatley, T., Kang, O., Parkinson, C. & Looser, C. E. From mind perception to mental connection: synchrony as a mechanism for social understanding. Soc. Personal. Psychol. Compass 6, 589–606 (2012).

    Google Scholar 

  5. Berscheid, E. & Wastler, E. in Foundations of Interpersonal Attraction (ed. Huston T.L.) 356–381 (Academic, 1974).

  6. Finkel, E. J., Eastwick, P. W. & Matthews, J. Speed-dating as an invaluable tool for studying romantic attraction: a methodological primer. Pers. Relatsh. 14, 149–166 (2007).

    Google Scholar 

  7. Damasio, A. R. The somatic marker hypothesis and the possible functions of the prefrontal cortex. Philos. Trans. R. Soc. B 351, 1413–1420 (1996).

    CAS  Google Scholar 

  8. Palumbo, R. V. et al. Interpersonal autonomic physiology: a systematic review of the literature. Pers. Soc. Psychol. Rev. 21, 99–141 (2017).

    PubMed  Google Scholar 

  9. Reed, R. G., Randall, A. K., Post, J. H. & Butler, E. A. Partner influence and in-phase versus anti-phase physiological linkage in romantic couples. Int. J. Psychophysiol. 88, 309–316 (2013).

    PubMed  Google Scholar 

  10. Papp, L. M., Pendry, P., Simon, C. D. & Adam, E. K. Spouses’ cortisol associations and moderators: testing physiological synchrony and connectedness in everyday life. Fam. Process 52, 284–298 (2013).

    PubMed  Google Scholar 

  11. Levenson, R. W. & Ruef, A. M. Empathy: a physiological substrate. J. Pers. Soc. Psychol. 63, 234–246 (1992).

    CAS  PubMed  Google Scholar 

  12. Helm, J. L., Sbarra, D. A. & Ferrer, E. Coregulation of respiratory sinus arrhythmia in adult romantic partners. Emotion 14, 522–531 (2014).

    PubMed  Google Scholar 

  13. Levenson, R. W. & Gottman, J. M. Marital interaction: physiological linkage and affective exchange. J. Pers. Soc. Psychol. 45, 587–597 (1983).

    CAS  PubMed  Google Scholar 

  14. Helm, J., Sbarra, D. & Ferrer, E. Assessing cross-partner associations in physiological responses via coupled oscillator models. Emotion 12, 748 (2012).

    PubMed  Google Scholar 

  15. de Waal, F. B. M. & Preston, S. D. Mammalian empathy: behavioural manifestations and neural basis. Nat. Rev. Neurosci. 18, 498–509 (2017).

    PubMed  Google Scholar 

  16. Prochazkova, E. & Kret, M. E. Connecting minds and sharing emotions through mimicry: a neurocognitive model of emotional contagion. Neurosci. Biobehav. Rev. 80, 99–114 (2017).

    PubMed  Google Scholar 

  17. Hasson, U., Ghazanfar, A. A., Galantucci, B., Garrod, S. & Keysers, C. Brain-to-brain coupling: a mechanism for creating and sharing a social world. Trends Cogn. Sci. 16, 1–8 (2012).

    Google Scholar 

  18. Behrens, F. et al. Physiological synchrony is associated with cooperative success in real-life interactions. Sci. Rep. 10, 1–9 (2020).

    Google Scholar 

  19. Prochazkova, E. et al. Pupil mimicry promotes trust through the theory-of-mind network. Proc. Natl Acad. Sci. U. S. A. 115, E7265–E7274 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  20. Singh, R. et al. On the importance of trust in interpersonal attraction from attitude similarity. J. Soc. Pers. Relat. 32, 829–850 (2015).

    Google Scholar 

  21. McAssey, M. P., Helm, J., Hsieh, F., Sbarra, D. A. & Ferrer, E. Methodological advances for detecting physiological synchrony during dyadic interactions. Methodology 9, 41–53 (2013).

    Google Scholar 

  22. Chatel-Goldman, J., Congedo, M., Jutten, C. & Schwartz, J.-L. Touch increases autonomic coupling between romantic partners. Front. Behav. Neurosci. 8, 95 (2014).

    PubMed  PubMed Central  Google Scholar 

  23. Chartrand, T. L. & Lakin, J. L. The antecedents and consequences of human behavioral mimicry. Annu. Rev. Psychol. 64, 285–308 (2013).

    PubMed  Google Scholar 

  24. Boker, S. M., Xu, M., Rotondo, J. L. & King, K. Windowed cross-correlation and peak picking for the analysis of variability in the association between behavioral time series. Psychol. Methods 7, 338–355 (2002).

    PubMed  Google Scholar 

  25. Gould, R. A Modern Approach to Regression with R. J. Stat. Softw. 33, 1–3 (2010).

    Google Scholar 

  26. Mogan, R., Fischer, R. & Bulbulia, J. A. To be in synchrony or not? A meta-analysis of synchrony’s effects on behavior, perception, cognition and affect. J. Exp. Soc. Psychol. 72, 13–20 (2017).

    Google Scholar 

  27. Chartrand, T. L. & van Baaren, R. in Advances in Experimental Social Psychology vol. 41 (ed. Zanna M.) 219–274 (Academic Press, 2009).

  28. Chartrand, T. L. & Bargh, J. A. The chameleon effect: the perception–behavior link and social interaction. J. Pers. Soc. Psychol. 76, 893–910 (1999).

    CAS  PubMed  Google Scholar 

  29. Goffman, E. The arrangement between the sexes. Theory Soc. 4, 301–331 (1977).

    Google Scholar 

  30. Grammer, K. Strangers meet: laughter and nonverbal signs of interest in opposite-sex encounters. J. Nonverbal Behav. 14, 209–236 (1990).

    Google Scholar 

  31. Givens, D. B. The nonverbal basis of attraction: flirtation, courtship, and seduction. Psychiatry 41, 346–359 (1978).

    CAS  PubMed  Google Scholar 

  32. Hall, J. A. & Xing, C. The verbal and nonverbal correlates of the five flirting styles. J. Nonverbal Behav. 39, 41–68 (2015).

    Google Scholar 

  33. Montoya, R. M., Kershaw, C. & Prosser, J. L. A meta-analytic investigation of the relation between interpersonal attraction and enacted behavior. Psychol. Bull. 144, 673–709 (2018).

    PubMed  Google Scholar 

  34. Bryant, J. & Miron, D. in Communication and Emotion: Essays in Honor of Dolf Zillmann (eds Bryant J., Roskov-Ewoldsen D. R. & Cantor J.) 31–59 (Routledge, 2003).

  35. Cohen, B., Waugh, G. & Place, K. At the movies: an unobtrusive study of arousal-attraction. J. Soc. Psychol. 129, 691–693 (1989).

    Google Scholar 

  36. Meston, C. M. & Frohlich, P. F. Love at first fright: partner salience moderates roller-coaster-induced excitation transfer. Arch. Sex. Behav. 32, 537–544 (2003).

    PubMed  Google Scholar 

  37. Zillmann, D. Excitation transfer in communication-mediated aggressive behavior. J. Exp. Soc. Psychol. 7, 419–434 (1971).

    Google Scholar 

  38. Hatfield, E., Cacioppo, J. T. & Rapson, R. L. Emotional contagion. Curr. Dir. Psychol. Sci. 2, 240 (1993).

    Google Scholar 

  39. Levenson, R. W. & Gottman, J. M. Physiological and affective predictors of change in relationship satisfaction. J. Pers. Soc. Psychol. 49, 85–94 (1985).

    CAS  PubMed  Google Scholar 

  40. Quadt, L., D.Critchley, H. & Garfinkel, S. N. in The Interoceptive Mind: From Homeostasis to Awareness (eds Tsakiris, M. & De Preester, H.) 123–143 (Oxford Univ. Press, 2018).

  41. Hasson, U., Nir, Y., Levy, I., Fuhrmann, G. & Malach, R. Intersubject synchronization of cortical activity during natural vision. Science (80-.). (2004).

  42. Kret, M. E., Fischer, A. H. & De Dreu, C. K. W. Pupil mimicry correlates with trust in in-group partners with dilating pupils. Psychol. Sci. 26, 1401–1410 (2015).

    CAS  PubMed  Google Scholar 

  43. Galvez-Pol, A., Antoine, S., Li, C. & Kilner, J. M. Direct perception of other people’s heart rate. https://psyarxiv.com/7f9pq/ (2020).

  44. Changizi, M. A., Zhang, Q. & Shimojo, S. Bare skin, blood and the evolution of primate colour vision. Biol. Lett. 2, 217–221 (2006).

    PubMed  PubMed Central  Google Scholar 

  45. Hasson, U., Nir, Y., Levy, I., Fuhrmann, G. & Malach, R. Intersubject synchronization of cortical activity during natural vision. Science 303, 1634–1640 (2004).

    CAS  PubMed  Google Scholar 

  46. Thomsen, D. G. & Gilbert, D. G. Factors characterizing marital conflict states and traits: physiological, affective, behavioral and neurotic variable contributions to marital conflict and satisfaction. Pers. Individ. Dif. 25, 833–855 (1998).

    Google Scholar 

  47. Liebowitz, M. R. Social phobia. Mod. Probl. Pharmacopsychiatry 3, 141–173 (1987).

    Google Scholar 

  48. Watson, D., Clark, L. A. & Tellegen, A. Development and validation of brief measures of positive and negative affect: the PANAS scales. J. Pers. Soc. Psychol. 54, 1063–1070 (1988).

    CAS  PubMed  Google Scholar 

  49. Spector, I. P., Carey, M. P. & Steinberg, L. The sexual desire inventory: development, factor structure, and evidence of reliability. J. Sex. Marital Ther. 22, 175–190 (1996).

    CAS  PubMed  Google Scholar 

  50. Kret, M. E. & De Dreu, C. K. W. Pupil-mimicry conditions trust in partners: moderation by oxytocin and group membership. Proc. R. Soc. Lond. B 284, 1–10 (2017).

    Google Scholar 

  51. Diedenhofen, B. & Musch, J. Cocor: a comprehensive solution for the statistical comparison of correlations. PLoS ONE 10, e0121945 (2015).

    PubMed  PubMed Central  Google Scholar 

  52. Fujiwara, K. & Daibo, I. Evaluating interpersonal synchrony: wavelet transform toward an unstructured conversation. Front. Psychol. 7, 516 (2016).

    PubMed  PubMed Central  Google Scholar 

  53. Tschacher, W., Rees, G. M. & Ramseyer, F. Nonverbal synchrony and affect in dyadic interactions. Front. Psychol. 5, 1323 (2014).

    PubMed  PubMed Central  Google Scholar 

  54. Behrens, F., Moulder, R. G., Boker, S. M., & Kret, M. E.. Quantifying physiological synchrony through windowed cross-correlation analysis: statistical and theoretical considerations. https://www.biorxiv.org/content/10.1101/2020.08.27.269746v1 (2020).

  55. Kohavi, R. A study of cross-validation and bootstrap for accuracy estimation and model selection. IJCAI 14, 1137–1145 (1995).

    Google Scholar 

  56. Sjak-Shie, E. PhysioData Toolbox (version 0.4) computer software (2018).

Download references

Acknowledgements

The authors thank M. Rojek-Giffin for helpful feedback and W. Boekel for proof-reading the scripts and helping with the control analysis scripts, as well as T. Wilderjans and J. Folz for statistical advice. Research was supported by the Netherlands Science Foundation (016.VIDI.185.036) to M.E.K., Talent Grant (no. 406-15-026) from Nederlandse Organisatie voor Wetenschappelijk Onderzoek (NWO) to M.E.K. and E.P. and the European Research Council (ERC) (Starting Grant #802979) to M.E.K.

Author information

Authors and Affiliations

Authors

Contributions

E.P. conceived the idea. E.P., M.E.K. and F.B. designed the experiment and, with contributions from D.L. and E.E.S.-S., conducted the experiment. E.P., E.E.S.-S. and D.L. performed the analyses and computational modelling with contributions from M.E.K. and F.B.. E.P. wrote the paper with contributions from M.E.K. and F.B. All authors discussed the results and implications and commented on the manuscript at all stages.

Corresponding authors

Correspondence to E. Prochazkova or M. E. Kret.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature Human Behaviour thanks Eli Finkel, Sebastian Wallot and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary information

Supplementary Figs. S1–S3, Tables S1–S20 and quantification of synchrony.

Reporting summary

Supplementary Video 1

Video 1. An example of measures. The video shows a non-verbal interaction where participants were instructed not to talk (825–945 s). The female’s and male’s Z-scored SC and HR are shown in the top two rows. In four rows below, selection of measured expressions is depicted (touch face, head shake, smile and laugh). In addition, gaze fixations were collected (not depicted). Notice the contagious spread of emotional information; at 886 s, the female smiles and the male partner reciprocates with a smile back. During this moment, we observe an increase in the female’s and male’s SC and HR. Again, at 903 s, the female laughs; in response, the male smiles, and we again observe synchrony in HR and SC (highlighted by orange cursor). Although non-verbal, during this 2 min interaction, the couple’s physiological synchrony and attraction increased.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Prochazkova, E., Sjak-Shie, E., Behrens, F. et al. Physiological synchrony is associated with attraction in a blind date setting. Nat Hum Behav 6, 269–278 (2022). https://doi.org/10.1038/s41562-021-01197-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41562-021-01197-3

This article is cited by

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