OYour brain is shaped by our experiences – whether you’re a bird watcher, a book lover or a chess player. And a new study provides a clearer picture of how sex and gender affect the brain, too.
Researchers used artificial intelligence to analyze data from MRI scans of thousands of children and found that they could predict the sex or gender of a study participant – albeit imperfectly – by looking at how brain regions interact with each other. Notably, the patterns of attachment that predicted sex, which is largely driven by biology, were not the same as the patterns that predicted gender, determined by a person’s sense of identity.
The authors found that sex-related brain networks were more likely to involve brain regions involved in vision; sensory processing; movement regulation; and planning and decision making. By comparison, gender-related networks were not as strongly associated with specific brain regions.
The study, published Friday in the journal Science Advances, leaves many questions unanswered, such as how these brain connections might differ in sex- and gender-mismatched children, when these network differences arise, and how they differ. them over time. But the authors point out that the results underscore the importance of collecting both sex- and gender-specific data at a time when this is not standard practice in neurological studies.
“Moving forward, we really need to consider sex and gender separately if we want to better understand the brain,” said Elvisha Dhamala, lead author of the study. “Moving beyond the scope of this study itself, the future of biomedical research really depends on us considering sex and gender separately.”
The terms sex and gender are often used interchangeably in everyday life, but have precise meanings for researchers. Sex is a biological variable, shaped by our body’s hormones, anatomy and genetics, while gender is a cultural construct, shaped both by our sense of self and our interactions with others.
Researchers have long known that brain disorders such as Alzheimer’s and attention deficit hyperactivity disorder are diagnosed and occur at different rates depending on sex and gender, although it has been complicated to determine how much each factor contributes to these disparities. That’s because while sex data has been collected more routinely in biological research since a 2015 directive from the National Institutes of Health, gender is often not included as a separate category.
In the latest study, researchers analyzed data from the Adolescent Brain Cognitive Development Study, the nation’s largest long-term study of children’s brain development. They looked at functional MRI (fMRI) data from 4,757 participants between the ages of 9 and 10, whose gender was split about 50-50. The researchers also had gender data for all participants based on self-reported responses or those of a parent.
fMRI measures brain activity by following blood flow and electrical activity, allowing researchers to understand which regions are communicating with each other. The research team then used machine learning algorithms to predict a person’s sex or gender based on their brain’s connectivity patterns.
The authors first found brain network patterns that could predict sex and gender. But it wasn’t clear from that analysis whether gender affected the brain in a way that went beyond the influence of a person’s sex. To explore this question, the authors analyzed data from males and females separately to isolate the effects of sex. They found that gender-related network patterns differed from sex-related ones, regardless of whether they looked at parent- or child-reported gender. The research team argued that this finding meant that sex and gender influences on the brain were not the same.
But Daniel Bayless, a neurobiologist at the Salk Institute who was not involved in the study, said the authors’ data do not fully support that claim.
Bayless applauded the study’s inclusion of gender, but he noted that when the researchers built a predictive model for gender with results from both males and females, they found that the associations associated with gender and sex largely overlapped.
He also noted that the study did not separate and analyze data from children whose sex assigned at birth differs from their gender identity. This is a point the authors acknowledged during a press conference with reporters, explaining that they considered gender in this study on a continuum rather than separate categories.
Despite the study’s focus on sex and gender, these factors accounted for only half of the variation in first-brain network patterns among participants, meaning there are other important contributing factors. And the paper only looked at participants at a single point in time. The researchers are now planning to track individuals to see how these patterns change during puberty and adulthood.