American scientists from Stanford University in California have created an artificial intelligence model that determines a person’s gender by scanning their brain activity with 90% accuracy. The study was published in the scientific journal magazine Proceedings of the National Academy of Sciences (PNAS).
This discovery supports the hypothesis that there are significant differences in the brain activity of men and women.
Previous research has shown that gender plays an important role at various stages of brain development, from early development to adolescence and aging. There is also a marked disparity in the prevalence and presentation of neuropsychiatric diseases between genders. Women are more likely to develop depression, anxiety, and eating disorders, while men are more likely to develop autism, attention-deficit/hyperactivity disorder, and schizophrenia.
The research involved the development and application of an end-to-end spatiotemporal deep neural network model combined with the XAI artificial intelligence framework to analyze resting-state functional MRI (rsfMRI) data. The data was collected from a large group of approximately 1,000 young people aged 20 to 35.
The study identified specific brain regions and networks that contribute to observed sex differences in the functional organization of the brain.
Regions associated with the passive brain network, including the posterior cingulate cortex, precuneus, and ventromedial prefrontal cortex, emerged as key differentiators between male and female brains.
Additionally, the analysis revealed significant differences in the striatum and limbic network, which are involved in reward sensitivity, reinforcement learning, and emotional regulation. These differences may have profound implications for understanding gender-based vulnerability to mental and neurological disorders and for the development of targeted interventions.
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