Timing is everything: dance aesthetics depend on the complexity of movement kinematics

Orlandi, A., Cross, E. S. and Orgs, G. (2020) Timing is everything: dance aesthetics depend on the complexity of movement kinematics. Cognition, 205, 104446. (doi: 10.1016/j.cognition.2020.104446) (PMID:32932073)

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Abstract

What constitutes a beautiful action? Research into dance aesthetics has largely focussed on subjective features like familiarity with the observed movement, but has rarely studied objective features like speed or acceleration. We manipulated the kinematic complexity of observed actions by creating dance sequences that varied in movement timing, but not in movement trajectory. Dance-naïve participants rated the dance videos on speed, effort, reproducibility, and enjoyment. Using linear mixed-effects modeling, we show that faster, more predictable movement sequences with varied velocity profiles are judged to be more effortful, less reproducible, and more aesthetically pleasing than slower sequences with more uniform velocity profiles. Accordingly, dance aesthetics depend not only on which movements are being performed but on how movements are executed and linked into sequences. The aesthetics of movement timing may apply across culturally-specific dance styles and predict both preference for and perceived difficulty of dance, consistent with information theory and effort heuristic accounts of aesthetic appreciation.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Cross, Professor Emily and Orlandi, Andrea
Authors: Orlandi, A., Cross, E. S., and Orgs, G.
College/School:College of Medical Veterinary and Life Sciences > Institute of Neuroscience and Psychology
Journal Name:Cognition
Publisher:Elsevier
ISSN:0010-0277
ISSN (Online):1873-7838
Published Online:12 September 2020
Copyright Holders:Copyright © 2020 The Authors
First Published:First published in Cognition 205:104446
Publisher Policy:Reproduced under a Creative Commons licence

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
303930SOCIAL ROBOTSEmily CrossEuropean Research Council (ERC)677270NP - Centre for Neuroscience
304215Philip Leverhulme Prize - ECEmily CrossLeverhulme Trust (LEVERHUL)PLP-2018-152NP - Centre for Neuroscience