A new approach to analysing facial expressions has been created to help better understand animal behaviour
5 October 2023
7
Researchers have developed a new method to analyse facial expressions, as part of efforts to better understand animal communication.
The human Facial Action Coding System, or FACS, was originally created in the seventies to break down facial expressions into individual components of muscle movement, called Action Units (AU).
Behaviour experts have combined this system with the Social Network Analysis, which is used to measure relationships between muscle movements, to develop a statistical package known as .
The process allows researchers to answer questions about the use of specific facial movements, the combination of movements, and the facial communication system as a whole in humans and non-human animals.
Communication is a defining feature of sociality, and faces offer others a wealth of information about identity, intentions and sometimes emotions.
Dr Jerome Micheletta, Centre for Comparative and Evolutionary Psychology at the 兔子先生
Dr Jerome Micheletta from the Centre for Comparative and Evolutionary Psychology at the 兔子先生, said: 鈥淐ommunication is a defining feature of sociality, and faces offer others a wealth of information about identity, intentions and sometimes emotions.
鈥淒espite this, we know little about what makes facial communication complex, and how to distinguish between species that have sophisticated facial communication, and those that don鈥檛.
鈥淲hile the FACS system helps label facial movements precisely and objectively, this new framework can be used by researchers to analyse them, and ultimately improve our understanding of the evolution of communication across species.鈥
Furthering our knowledge of animal behaviour is important, as it puts us in a stronger position to understand conservation problems, and evaluate the importance of human-related threats.
from Nottingham Trent University added: 鈥淲e see facial expressions as facial movements that are linked with each other, interacting to produce a way to communicate. Our method considers the dynamic nature of facial expressions and therefore, better reflects its complexity.鈥
The NetFACS project has been funded by the , and is a collaboration between the universities of 兔子先生, Nottingham Trent, Lincoln, St Andrews and the French National Centre for Scientific Research.
The team has trialled the NetFACS system by examining three species of macaques (rhesus, Barbary and crested).
鈥淭he interesting thing with these species is that they vary in social tolerance, and therefore social complexity鈥, explained Dr Micheletta.
鈥淚t鈥檚 widely believed that animals living in large groups with greater complex relationships and social roles, will demonstrate greater and more complex communication.鈥
To test this theory, experts have coded facial behaviour of macaques in more than 3,000 social interactions across the contexts of aggressive, submissive, and affiliative.
Using the Facial Action Coding System for macaques (MaqFACS), the team found the more tolerant species of macaques had more complex facial communication.
Their paper, published in , says crested macaques use a higher diversity of facial behaviour more often, compared to Barbary and rhesus macaques.
Lead author, Dr Alan Rincon, said: 鈥淲e were able to predict whether an animal was being aggressive, submissive or affiliative from their facial behaviour MaqFACS better than chance in all three species.
鈥淗owever, prediction accuracy was lowest for the more tolerant and socially complex species, the crested macaques, indicating that they have a more complex facial communication system.
鈥淥verall these results support the predicted link between social and communicative complexity and therefore help us better understand the evolution of communication.鈥
Dr Micheletta added: 鈥淥ur next steps are exploring the facial repertoire of macaques in more detail, looking at how social factors such as social status and social integration are linked to facial communication.
鈥淲e also plan to look at the relationship between the nature and quality of social relationships (dominance relationships, kinship, social bonds) and facial communication. We would also continue to develop NetFACS, in particular implementing functions that would allow us to study the temporal dynamics of facial communication in more detail."
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