Researchers at the Max Planck Institute of Neurobiology are the first to describe various emotional facial expressions for mice. Just like humans, a rat’s face looks completely different when it tastes something sweet or bitter, or when it becomes anxious. With this new possibility of measuring the emotions of mice, neurobiologists can now investigate the basic mechanisms of how emotions are produced and processed in the brain.

Happiness, disgust, fear – the facial expressions reflecting these feelings are the same in every human being. For example, if we hate something, our eyes become narrow, our nose wrinkles and our upper lips become asymmetrical in distortions.

Even newborns react with different facial expressions when they are unhappy, happy or disappointed. We also think to recognize emotions in our pets’ facial expressions. Conversely, the faces of other animals may appear expressionless to us. This is incorrect, as Max Planck scientists now show.

Using machine vision, the researchers were able to reliably link five emotional states to the facial expressions of the mice: happiness, disgust, nausea, pain, and fear were clearly different to computer algorithms. They could also measure the relative power of these feelings.

Joyful expression

Studies show that a mouse’s facial expression is not actually a response to the environment. This reflects the emotional value of the trigger. Nadine Gogola, who led the study, explains, “Rats licked a sugar solution when they were thirsty, they showed more cheerful facial expressions than satiated mice.”

Meanwhile, mice tasting the slightly saline solution showed a “satisfied” expression, while the very saline solution led to a “disgusting” face. From these and other experiments, researchers have concluded, untouched by sensory stimulation, facial expressions actually reflect the intrinsic, personal character of an emotion.

However, emotions are not simply responses to external stimuli – they are generated through mechanisms in the brain itself.

The researchers thus next investigated how neuronal activity in different areas of the brain affects facial expressions. Neurobiologists were able to reveal various emotional facial expressions when they light-activated specific brain regions known to play a role in emotional processing.

Mechanism behind emotions

The main advantage of exploring mouse facial expressions is that it is now possible to identify the mechanisms that give rise to emotions. This, until now, was precisely this problem: without a reliable measurement of emotions, it was difficult to study their origins in the brain.

The lead author of the study, Nejc Dolensek, says, “We can see subtle facial changes in human mice, but we can only identify the feeling behind it with a very good feel and rarely determine its intensity.” Huh.”

“With our automated face recognition system, we can now measure the intensity and nature of an emotion over a time frame of milliseconds and compare it to neuronal activity in the respective brain regions.” One such brain area is the insular cortex, which is associated with emotional behavior and the perception of emotions in animals and humans.

When scientists measured the activity of individual neurons using 2-photon microscopy and simultaneously recorded the emotional facial expressions of the mouse, something surprising came out: individual neurons in the insular cortex with the same strength Reacted and facial expression of the mouse in exactly the same way. In addition, each individual neuron was associated with only one emotion.

These results suggest the existence of “sense neurons”, each reflecting a specific sensation – at least in the insular cortex. “Entering facial expressions, we can now investigate the fundamental nervous system behind emotions in mouse animal models,” explained Nadine Gogola.

“This is an important prerequisite for investigating emotions and potential disorders in their processing, such as anxiety disorders or depression.”

Understanding the neuropsychological underpinnings of emotions depends on objective readouts of the individual’s emotional state, which remains a major challenge, especially in animal models.

We found that mice display facial expressions in response to emotionally saline events as well as targeted manipulation of emotion-related neuronal circuits.

Facial expressions were classified into different categories using machine learning and reflected the changing intrinsic value of the same sensory stimuli under different homostatic or affective conditions. There were feelings such as intensity, validity, and firmness in facial expressions. Two-photon imaging revealed insular cortical neuron activity correlated with specific facial expressions and different emotions can be encoded.

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