Research has discarded the commonly-held belief that human beings have six basic emotions that are reflected via facial expressions.
There are actually four basic emotions - and not six - which are universally recognised and easily interpreted through specific facial expressions, regardless of language or culture.
They reached the conclusion by studying the range of different muscles within the face - or Action Units as researchers refer to them - involved in signalling different emotions, as well as the time-frame over which each muscle was activated.
"This is the first such study to objectively examine the 'temporal dynamics' of facial expressions, made possible by using a unique generative face grammar platform developed at the University of Glasgow," said lead researcher Rachael Jack.
Through this method, the team from University's institute of neuroscience and psychology found that the signals for fear/surprise and anger/disgust were confused at the early stage of transmission and only became clearer later when other Action Units were activated.
The team claims that fear and surprise share a common signal - the wide open eyes - while anger and disgust share the wrinkled nose.
It is these early signals that could represent more basic danger signals.
Later, in the signalling dynamics, facial expressions transmit signals that distinguish all six 'classic' facial expressions of emotion - happiness, sadness, fear, anger, surprise and disgust.
"Our results are consistent with evolutionary predictions, where signals are designed by both biological and social evolutionary pressures to optimise their function," said Jack.
"Our research shows that not all facial muscles appear simultaneously during facial expressions, but rather develop over time supporting a hierarchical biologically-basic to socially-specific information over time," Jack explained.
The generative face grammar uses cameras to capture a three-dimensional image of faces of individuals specially trained to be able to activate all 42 individual facial muscles independently.
From this, a computer can then generate specific or random facial expressions on a 3D model based on the activation of different Actions Units or groups of units to mimic all facial expressions, says research published in the journal Current Biology.
"Our findings shows that 'basic' facial expression signals are perceptually segmented across time and follow an evolving hierarchy of signals over time - from the biologically-rooted basic signals to more complex socially-specific signals," the researchers added.
