Rethinking primate facial expression: a predictive framework

Waller, B.M. ORCID: 0000-0001-6303-7458, Whitehouse, J. ORCID: 0000-0003-2607-5492 and Micheletta, J., 2017. Rethinking primate facial expression: a predictive framework. Neuroscience and Biobehavioral Reviews, 82, pp. 13-21. ISSN 0149-7634

[img]
Preview
Text
1372446_a1208_Whitehouse.pdf - Post-print

Download (438kB) | Preview

Abstract

Primate facial expression has long been studied within a framework of emotion that has heavily influenced both theoretical approaches and scientific methods. For example, our understanding of the adaptive function and cognition of facial expression is tied to the assumption that facial expression is accompanied by an emotional internal state, which is decipherable by others. Here, we challenge this view and instead support the alternative that facial expression should also be conceptualised as an indicator of future behaviour as opposed to current emotional state alone (Behavioural Ecology View, Fridlund, 1994). We also advocate the use of standardised, objective methodology Facial Action Coding System, to avoid making assumptions about the underlying emotional state of animals producing facial expressions. We argue that broadening our approach to facial expression in this way will open new avenues to explore the underlying neurobiology, cognition and evolution of facial communication in both human and non-human primates.

Item Type: Journal article
Publication Title: Neuroscience and Biobehavioral Reviews
Creators: Waller, B.M., Whitehouse, J. and Micheletta, J.
Publisher: Elsevier
Date: November 2017
Volume: 82
ISSN: 0149-7634
Identifiers:
NumberType
1372446Other
S0149763416303177Publisher Item Identifier
10.1016/j.neubiorev.2016.09.005DOI
Divisions: Schools > School of Social Sciences
Record created by: Linda Sullivan
Date Added: 06 Oct 2020 14:45
Last Modified: 31 May 2021 15:13
URI: https://irep.ntu.ac.uk/id/eprint/41186

Actions (login required)

Edit View Edit View

Views

Views per month over past year

Downloads

Downloads per month over past year