Physical attraction to reliable, low variability nervous systems: reaction time variability predicts attractiveness

Emily E. Butler, Christopher W. N. Saville, Robert Ward, Richard Ramsey*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

The human face cues a range of important fitness information, which guides mate selection towards desirable others. Given humans’ high investment in the central nervous system (CNS), cues to CNS function should be especially important in social selection. We tested if facial attractiveness preferences are sensitive to the reliability of human nervous system function. Several decades of research suggest an operational measure for CNS reliability is reaction time variability, which is measured by standard deviation of reaction times across trials. Across two experiments, we show that low reaction time variability is associated with facial attractiveness. Moreover, variability in performance made a unique contribution to attractiveness judgements above and beyond both physical health and sex-typicality judgements, which have previously been associated with perceptions of attractiveness. In a third experiment, we empirically estimated the distribution of attractiveness preferences expected by chance and show that the size and direction of our results in Experiments 1 and 2 are statistically unlikely without reference to reaction time variability. We conclude that an operating characteristic of the human nervous system, reliability of information processing, is signalled to others through facial appearance.
Original languageEnglish
Pages (from-to)81-89
Number of pages9
JournalCognition
Volume158
DOIs
Publication statusPublished - Jan 2017
Externally publishedYes

Keywords

  • face perception
  • attractiveness
  • reaction time variability
  • central nervous system

Fingerprint

Dive into the research topics of 'Physical attraction to reliable, low variability nervous systems: reaction time variability predicts attractiveness'. Together they form a unique fingerprint.

Cite this