AI Identifies Gender Differences in Human Brain Structures Based on MRI Scans

Biological sex is a crucial variable in neuroscience studies where sex differences have been documented across cognitive functions and neuropsychiatric disorders. While gross statistical differences have been previously documented in macroscopic brain structure such as cortical thickness or region size, less is understood about sex-related cellular-level microstructural differences which could provide insight into brain health and disease. Studying these microstructural differences between men and women paves the way for understanding brain disorders and diseases that manifest differently in different sexes.White Matter Focus: Differences were found in the brain's white matter, crucial for inter-regional communication. AI models identified biological sex in MRI scans with 92%-98% accuracy. These variations were spotted in white matter, tissue primarily located in the human brain's innermost layer, which fosters communication between regions. Men and women are known to experience multiple sclerosis, autism spectrum disorder, migraines, and other brain issues at different rates and with varying symptoms.

Understanding sex-based brain differences can improve diagnostics and treatments for disorders like multiple sclerosis and autism. The study suggests that AI can accurately identify sex-based brain patterns invisible to human eyes. The findings were validated by three different AI models that could distinguish between biological male and female brains by spotting patterns in structure and complexity that were invisible to the human eye.

Researchers at NYU Langone Health used machine learning to analyze thousands of MRI brain scans from men and women, revealing distinct cellular-level differences in brain structures. The AI tools could report differences in brain-cell organization, highlighting the importance of diversity when studying diseases that arise in the human brain. The study classified sex based on genetic information and only included MRIs from cis-gendered men and women.

The results show that all models correctly identified the sex of subject scans between 92% and 98% of the time. Several features, such as the direction water could move through brain tissue, helped the machines make their determinations. The team plans to explore the development of sex-related brain structure differences over time to better understand environmental, hormonal, and social factors that could play a role in these changes.