How many face expressions can you make

But researchers now say that human faces might only be able to make four universally recognized facial expressions. For a while, researchers thought that there were six faces that everybody in the world could identify: happiness, sadness, fear, anger, surprise and disgust.

They argue that fear and disgust share the same key facial signal: the wrinkled nose. The same goes for fear and surprise, both involve widened eyes and should be combined. There are 42 individual facial muscles in the face. For years, scientists studying facial expressions have focused their research on six primary emotions: happiness, surprise, anger, sadness, fear, and disgust. As a result generations of facial-expression research papers have included panels that look something like this:.

That one is from a paper about cultural differences in the perception of facial expressions. Pretty straightforward, right? Hate also involves the feeling of disgust and anger but, this time, the emphasis is on anger. Only as social behaviours started to develop, did these facial expressions take on a more communicative role. Credit: Alamy. The first cross-cultural field studies, carried out by Ekman in the s, backed up this hypothesis.

He tested the expression and perception of six key emotions — happiness, sadness, anger, fear, surprise and disgust — around the world, including in a remote population in New Guinea 2 , 3.

Ekman chose these six expressions for practical reasons, he told Nature. Some emotions, such as shame or guilt, do not have obvious readouts, he says. And later work supported the claim that some facial expressions might confer an adaptive advantage 5. In other words, our faces are powerless to hide our emotions.

The obvious problem with that assumption is that people can fake emotions, and can experience feelings without moving their faces. But a growing crowd of researchers argues that the variation is so extensive that it stretches the gold-standard idea to the breaking point. Their views are backed up by a vast literature review 6. A few years ago, the editors of the journal Psychological Science in the Public Interest put together a panel of authors who disagreed with one another and asked them to review the literature.

Instead of starting with a hypothesis, they waded into the data. Faces alone only reveal so much about mood. Scroll down for the full picture. At one extreme, the group cited studies that found no clear link between the movements of a face and an internal emotional state.

Trying to assess internal mental states from external markers is like trying to measure mass in metres, Crivelli concludes. Another reason for the lack of evidence for universal expressions is that the face is not the whole picture.

Other things, including body movement, personality, tone of voice and changes in skin tone have important roles in how we perceive and display emotion. For example, changes in emotional state can affect blood flow, and this in turn can alter the appearance of the skin.

Martinez and his colleagues have shown that people are able to connect changes in skin tone to emotions 7. Clockwise, from top left: basketball player Zion Williamson celebrates a dunk; Mexico fans celebrate a win in a World Cup group match; singer Adele wins Album of the Year at the Grammys in ; Justin Bieber fans cry at a concert in Mexico City.

In , responding to a critique from Barrett, he pointed to a body of work that he says supports his previous conclusions, including studies on facial expressions that people make spontaneously, and research on the link between expressions and underlying brain and bodily state.

His views have not changed, he says. Most people recognize an angry face when they see it, she adds, citing an analysis of nearly studies 9. Sauter and Tracy think that what is needed to make sense of facial expressions is a much richer taxonomy of emotions. Rather than considering happiness as a single emotion, researchers should separate emotional categories into their components; the happiness umbrella covers joy, pleasure, compassion, pride and so on. Expressions for each might differ or overlap.

Some studies use computers to randomly generate faces. Credit: C. Chen et al. At the heart of the debate is what counts as significant. She read his early papers as a PhD student. Significance aside, researchers also have to battle with subjectivity: many studies rely on the experimenter having labelled an emotion at the start of the test, so that the end results can be compared.

So Barrett, Jack and others are trying to find more neutral ways to study emotions. Barrett is looking at physiological measures, hoping to provide a proxy for anger, fear or joy.

Instead of using posed photographs, Jack uses a computer to randomly generate facial expressions, to avoid fixating on the common six. Others are asking participants to group faces into as many categories as they think are needed to capture the emotions, or getting participants from different cultures to label pictures in their own language. Software firms tend not to allow their algorithms such scope for free association. A typical artificial intelligence AI program for emotion detection is fed millions of images of faces and hundreds of hours of video footage in which each emotion has been labelled, and from which it can discern patterns.

Affectiva says it has trained its software on more than 7 million faces from 87 countries, and that this gives it an accuracy in the 90th percentile. The company declined to comment on the science underlying its algorithm.

Researchers on both sides of the debate are sceptical of this kind of software, however, citing concerns over the data used to train algorithms and the fact that the science is still debated. He has not heard back.