These neuroscientists have spent years trying to find out if their mice are happy to understand the origin of human emotions.

It may seem counterintuitive because we have been talking about emotions for decades, but the truth is that even today, the neurobiological origins of emotions are still a mystery to science. We know many things, of course. But scientists still don't fully understand how emotions can almost miraculously arise from the complex circuits of the human brain.

Under normal circumstances, these same scientists would not hesitate for a second: they would trace the origin of these emotions in animals. This is what is done in the search for drugs or in comparative psychology research. However, with the emotional issue it has been more difficult. After all, how do we know that a mouse is happy or surprised or afraid? Yes, looking at it we can get used to the idea ... but can we be sure that we really understand what they feel?

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Julia Kuhl

Nejc Dolensek and his team asked this same question when trying to use artificial vision systems to read the faces of rodents and classify them accurately. What they did was record the rodents as they were exposed to sensory stimuli such as sweet or sour tastes and scary events, and identified different facial expressions that were systematically correlated with emotional descriptors such as pleasure, displeasure, and discomfort.

They then processed all of this with various machine learning algorithms. The first thing they discovered is that what they identified with emotions had characteristics very similar to human emotions. For example, these responses were shown to have "valence" and increased by repeatedly presenting the stimulus; something, which according to the authors, suggests they were "in correspondence with internal emotional states" and "were not mere reflexes".

Once emotions were identified, the scientists were able to use neuroimaging techniques to identify "facial" neurons that correlated with specific facial expressions in the mice. This "offers an essential objective analysis tool to understand the neurobiological mechanisms of emotions, to identify species-specific emotions and to study their variability between individuals," the researchers explained.

Image | Mert Guller

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