Relationship columnists and popular psychologists have long claimed that men and women are wired differently, and a new study has proven them right.
Scientists developed an artificial intelligence model that was able to distinguish between scans of men’s and women’s brain activity with more than 90 percent accuracy.
Most of these differences are found in the default mode network, the striatum, and the limbic network, areas involved in a wide range of processes including daydreaming, remembering the past, planning for the future, making decisions, and smelling.
With these results, Stanford Medicine scientists add a new piece to the puzzle, supporting the idea that biological sex shapes the brain.
The researchers said they are optimistic that this work will help shed light on brain conditions that affect men and women differently.
Scientists have long debated whether sex differences appear in the brain. This new study suggests they can, if scientists look in the right places
For example, autism and Parkinson’s are more common in men, while multiple sclerosis and depression are more common in women.
“A key motivation for this study is that sex plays a crucial role in human brain development, aging and the manifestation of psychiatric and neurological disorders,” said the study’s senior author, Vinod Menon, professor of psychiatry and behavioral sciences at Stanford. , in a sentence.
This image from the new study shows which parts of the brain are most important for distinguishing between men and women: the striatum and areas involved in the default mode network and the limbic network.
“Identifying consistent and replicable sex differences in the healthy adult brain is a critical step toward a deeper understanding of sex-specific vulnerabilities in psychiatric and neurological disorders,” he added.
To explore the question of sex-specific brain differences, 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 (fMRI) scans and telling it whether it was looking at a male or female brain.
Through this process, he began to understand which parts of the brain showed subtle differences depending on sex.
A new AI model was trained with images of men’s and women’s brains. Once trained, he could distinguish between men and women with about 90 percent accuracy.
When the AI received about 1,500 brain scans from a different set than the one it was trained on, it successfully predicted the sex of the brain’s owner more than 90 percent of the time.
These brain scans came from men and women in the US and Europe, suggesting that the AI model could discriminate by sex even when there were other differences, such as language, diet and culture.
“This is very strong evidence that sex is a strong determinant of human brain organization,” Menon said.
An important difference between this team’s AI model and others like it is that it is “explainable.”
Scientists often criticize AI for being a “black box”: it can receive information and return results, but how it reached its conclusions is often a mystery.
The same is not true of the Stanford team’s model.
The main differences that the AI model identified were in the default mode network, the striatum, and the limbic network.
In this study, the team was able to conclude which parts of the brain were most important for the AI to determine a person’s sex.
The three areas the AI focused on were the default mode network, the striatum, and the limbic network.
The default network mode is active when a person daydreams, remembers memories, or thinks about themselves. The striatum is important for coordinating cognition, including planning, decision making, and motivation. And the limbic network supports a variety of brain functions such as emotions, long-term memory, and a person’s sense of smell.
He study appeared today in Proceedings of the National Academy of Sciences.
Beyond distinguishing men’s brains from women’s, scientists sought to see if they could use the scans to predict how well someone would perform on a laboratory cognition test.
What they discovered was that no AI model could predict everyone’s performance. Both men’s and women’s performance could be predicted, but neither could predict both.
This suggests that characteristics that differ between men and women have different implications for behavior depending on sex.
“These models worked very well because we were able to separate brain patterns between sexes,” Menon said.
“This tells me that overlooking sex differences in brain organization could lead us to overlook key factors underlying neuropsychiatric disorders.”