Scientists have found evidence of differences in the brains of men and women

Scientists have found evidence of differences in the brains of men and women

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It has long been known that men and women think differently. However, there were virtually no scientifically documented differences in the structure of the brain in people of different genders. However, researchers from Stanford University of Medicine were able to prove this by developing a deep neural network model.

Relationship experts and popular psychologists have long argued that men and women think differently, and new research has proven them right.

Scientists have developed an artificial intelligence model that was able to determine the difference in brain activity between men and women with an accuracy of more than 90%.

Most of these differences are found in the brain’s passive mode network, striatum, and limbic network—regions involved in a wide range of processes, including daydreaming, remembering the past, planning for the future, decision making, and smell.

Scientists at Stanford University School of Medicine said they are optimistic that the work will help shed light on brain diseases that affect men and women differently.

For example, autism and Parkinson’s disease are more common in men, while multiple sclerosis and depression are more common in women.

“A key motivation for this study is that gender plays a critical role in human brain development, aging, and the expression of psychiatric and neurological disorders,” said Vinod Menon, senior author of the study and professor of psychiatry and behavioral sciences at Stanford.

“Identifying consistent and reproducible sex differences in the healthy adult brain is an important step toward a better understanding of gender-specific vulnerabilities in psychiatric and neurological disorders,” he added.

To explore whether brains differ by gender, Menon and his team developed a deep neural network model that could learn to classify brain scans as male or female.

They started by showing the AI ​​a series of functional magnetic resonance imaging scans and telling it whether it was looking at a male or female brain. Through this process, artificial intelligence began to understand which parts of the brain have subtle differences depending on gender.

When the artificial intelligence received about 1,500 brain scans from a different set than the ones it was trained on, it successfully predicted the gender of the brain’s owner more than 90% of the time.

These brain scans were taken from men and women in the US and Europe, suggesting that the AI ​​model can differentiate between genders even if there are other differences such as language, culture, etc.

“This is very convincing evidence that gender is a strong determinant of human brain organization,” Menon said.

One of the main differences between this team’s AI model and others like it is that it is “explainable.” Scientists often criticize artificial intelligence for being a “black box” – it can collect information and produce results, but how it came to those conclusions often remains a mystery. Not so with the Stanford team’s model.

In the study in question, scientists were able to deduce which parts of the brain are most important for AI to determine a person’s gender. The three areas the AI ​​focused on were the default mode network, the striatum, and the limbic network.

The default mode network is active when a person daydreams, remembers something, or otherwise thinks about himself. The striatum is important for coordinating cognition, including planning, decision making, and motivation. And the limbic network supports a number of brain functions, such as emotions, long-term memory and the human sense of smell.

In addition to distinguishing a man’s brain from a woman’s, the scientists tried to see if they could use the scans to predict how well a person would do on a laboratory cognitive test.

They found that no AI model could predict the performance of every subject. This suggests that characteristics that differ between men and women influence behavior differently depending on gender.

“These models worked very well because we successfully separated brain structures between the sexes. This tells me that ignoring sex differences in brain organization may cause us to miss key factors underlying neuropsychiatric disorders,” explains Vinod Menon.

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