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Brain area that recognises facial expressions found

April 20, 2016 04:00 pm | Updated November 26, 2021 10:23 pm IST - Washington

Researchers, including Ramprakash Srinivasan from Ohio State University placed 10 college students into an fMRI machine and showed them more than 1,000 photographs of people making facial expressions.

Researchers from Ohio State University in the U.S. used functional magnetic resonance imaging (fMRI) to identify a region of pSTS as the part of the brain activated when test subjects looked at images of people making different facial expressions. For representational purpose only. File Photo. AP.

Researchers, including one of Indian-origin, have pinpointed the area of the brain responsible for recognising human facial expressions.

The area is on the right side of the brain behind the ear, in a region called the posterior superior temporal sulcus (pSTS).

Researchers from Ohio State University in the U.S. used functional magnetic resonance imaging (fMRI) to identify a region of pSTS as the part of the brain activated when test subjects looked at images of people making different facial expressions.

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They discovered that neural patterns within the pSTS are specialised for recognising movement in specific parts of the face. One pattern is tuned to detect a furrowed brow, another is tuned to detect the upturn of lips into a smile, and so on.

“That suggests that our brains decode facial expressions by adding up sets of key muscle movements in the face of the person we are looking at,” said Aleix Martinez from Ohio State University.

Researchers were able to create a machine learning algorithm that uses this brain activity to identify what facial expression a person is looking at based solely on the fMRI signal.

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“Humans use a very large number of facial expressions to convey emotion, other non-verbal communication signals and language,” said Mr. Martinez.

“Yet, when we see someone make a face, we recognise it instantly, seemingly without conscious awareness. In computational terms, a facial expression can encode information, and we have long wondered how the brain is able to decode this information so efficiently,” he said.

Using this fMRI data, researchers developed a machine learning algorithm that had about a 60 per cent success rate in decoding human facial expressions, regardless of the facial expression and regardless of the person viewing it.

“That is a very powerful development, because it suggests that the coding of facial expressions is very similar in your brain and my brain and most everyone else’s brain,” said Mr. Martinez.

Researchers, including Ramprakash Srinivasan from Ohio State University placed 10 college students into an fMRI machine and showed them more than 1,000 photographs of people making facial expressions.

The expressions corresponded to seven different emotional categories — disgusted, happily surprised, happily disgusted, angrily surprised, fearfully surprised, sadly fearful and fearfully disgusted.

While some of the expressions were positive and others negative, they all had some commonalities among them. For instance, “happily surprised,” “angrily surprised” and “fearfully surprised” all include raised eyebrows, though other parts of the face differ when we express these three emotions.

The findings were published in the Journal of Neuroscience .

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