summary: Researchers have developed an artificial intelligence model that accurately determines an individual’s gender based on brain scans, achieving a success rate of over 90%. This groundbreaking discovery supports the theory that significant sex differences exist in brain organization and challenges a long-standing debate.
The AI model focused on dynamic MRI scans and identified specific brain networks, including the default mode, striatum, and limbic networks, as important in differentiating male and female brains. .
This research not only advances our understanding of brain development and aging, but also opens new avenues for addressing gender-specific vulnerabilities in psychiatric and neurological diseases.
Important facts:
- Highly accurate gender determination: The ability of an AI model to distinguish between male and female brain scans with more than 90% accuracy highlights inherent sex differences in brain organization.
- Identifying major brain networks: Explainable AI tool identifies default mode network, striatum, and limbic network as key regions that the model analyzed to determine gender in brain scans, and their role in cognitive function and behavior I emphasized.
- Possibilities of personalized medicine: The findings suggest that recognizing sex differences in brain organization is essential for developing targeted treatments for neuropsychiatric disorders, paving the way for personalized medicine approaches.
sauce: stanford
A new study by Stanford Medicine researchers reveals a new artificial intelligence model that was more than 90% successful in determining whether scans of brain activity came from a woman or a man.
The survey results were published on February 19th. Proceedings of the National Academy of Sciences, This study helps resolve a long-standing debate about whether reliable sex differences exist in the human brain, and understanding these differences could help address neuropsychiatric conditions that differentially affect women and men. suggests that it may be important to
“A key motivation for this study is that sex plays an important role in human brain development, aging, and the manifestation of psychiatric and neurological diseases,” said Professor of Psychiatry and Behavioral Sciences and director of Stanford University. said Dr. Vinod Menon.Cognitive and Systems Neuroscience Laboratory
“Identifying consistent and reproducible sex differences in the healthy adult brain is an important step toward a deeper understanding of sex-specific vulnerabilities in psychiatric and neurological diseases.”
Menon is the study’s senior author. The first authors are Senior Researcher Dr. Srikanth Ryali and Academic Staff Researcher Dr. Yuan Zhang.
The “hot spots” that most helped the model distinguish between male and female brains included the default mode network, a brain system that helps process self-referential information, and lines involved in learning and responding to rewards. Includes striatal and limbic networks. .
The researchers noted that this study did not. We examine whether sex-related differences arise early in life or are caused by hormonal differences or differences in the social situations men and women are likely to encounter.
Revealing differences in the brain
The extent to which a person’s gender influences the organization and behavior of the brain has long been a matter of debate among scientists. We know that the sex chromosomes we are born with help determine the combination of hormones our brains are exposed to, especially during early development, adolescence, and aging, but research Researchers have long struggled to link sex to specific differences in the human brain.
Brain structures tend to look similar in men and women, and previous studies of how brain regions work together have rarely revealed consistent indicators of the brain’s gender. Not yet.
In the current study, Menon and his team leverage recent advances in artificial intelligence and access to multiple large datasets to pursue more powerful analysis than previously employed. did.
First, they created a deep neural network model that learned to classify brain imaging data. When the researchers showed the brain scans to the models and told them they were looking at a male or female brain, the models began to “notice” what was subtle. Patterns can help tell the difference.
The model showed superior performance compared to previous studies, in part because it used a deep neural network to analyze dynamic MRI scans. This approach captures the complex interactions between different brain regions. When the researchers tested the model on about 1,500 brain scans, it was almost always able to tell whether the scans were from a woman or a man.
The success of this model suggests that detectable sex differences exist in the brain, but have simply not been reliably detected until now. The fact that it performed so well on a variety of datasets, including brain scans from multiple sites in the United States and Europe, makes this result particularly It makes it convincing.
“This is very strong evidence that sex is a strong determinant of human brain organization,” Menon said.
make a prediction
Until recently, models like the one employed by Menon’s team helped researchers classify brains into different groups, but they provided no information about how the classification was done. . But researchers now have access to a tool called “explainable AI,” which allows them to sift through vast amounts of data. explain How model decisions are made.
Menon and his team used explainable AI to identify the brain networks that were most important in helping the model determine whether a brain scan was from a man or a woman. They found that the model mostly referred to and made calls to the default mode network, striatal, and limbic networks.
The team then wondered if they could create another model that could predict how well participants would perform certain cognitive tasks based on the different functional characteristics of the brain between women and men.
They developed gender-specific models of cognitive ability. One model effectively predicted the cognitive ability of men but not women, and the other effectively predicted the cognitive ability of women but not men. The results of this study demonstrate that the functional characteristics of the brain, which differ between the sexes, have a significant impact on behavior.
“These models worked very well because they were able to separate the brain patterns between men and women,” Menon said. “This shows that if we overlook sex differences in brain organization, we may miss important factors underlying neuropsychiatric disorders.”
While the research team applied deep neural network models to questions about gender differences, Menon said the model could be used to answer questions about how nearly every aspect of brain connectivity relates to all kinds of cognitive abilities and behaviors. states that it can be applied to answer. He and his team plan to make the model publicly available for any researcher to use.
“Our AI model has very broad applicability,” Menon says. “Researchers can use our model to look for brain differences associated with learning disabilities or differences in social functioning, for example, to help individuals adapt and overcome these challenges. This is an aspect we would like to understand better.”
Funding: This research was sponsored by the National Institutes of Health (grants MH084164, EB022907, MH121069, K25HD074652, AG072114), Transdisciplinary Initiative, Uytengsu-Hamilton 22q11 Programs, Stanford Maternal and Child Health Research Institute, and a NARSAD Young Investigator Award.
About this artificial intelligence research news
author: erin digital
sauce: stanford
contact: Erin Digital – Stanford
image: Image credited to Neuroscience News
Original research: The findings appear below PNAS
