A new study published in Nature Communications finds robust but independent sex differences across how the brain functions, its structure and associated behaviours. Researchers Siyuan Liu and Armin Raznahan, working at the National Institute of Mental Health, show that while functional activation, grey matter volume and behavioural traits each reliably distinguish male and female profiles, the degree of sex typicality in one domain bears no relation to the others.
The team analysed data from nearly 1,000 healthy young adults who underwent functional magnetic resonance imaging while performing seven different tasks. The tasks spanned emotion processing, gambling, relational reasoning, social cognition, language processing, working memory and motor skills, allowing the researchers to assess task-specific brain activation as well as general patterns of activity.
The researchers found widespread sex differences in activation across about 85 per cent of the cerebral cortex. These differences were highly reproducible but largely task-specific, with some regions more active in females during language tasks and others more active in males during gambling tasks.
Beyond task-specific effects, a smaller number of regions—primarily involved in motor control and somatosensory processing—showed a general tendency toward higher activation in females across all seven tasks, though the effect sizes were small to moderate overall.
To determine whether functional differences aligned with anatomy, the team compared brain activation with structural MRI measures of grey matter volume in the same participants. They observed reproducible sex differences in grey matter across various cortical regions, but the spatial patterns did not align with the activation differences. Regions with volume differences did not consistently correspond to regions with task-related activation differences, suggesting that structural and functional sex differences arise as independent biological phenomena.
The scientists also incorporated behavioural data, analysing 86 traits from physical grip strength and visual judgment to anxiety and psychological distress. Using a machine-learning approach, they found that sex could be predicted from any of the three data domains: task activation (about 88 per cent accuracy), grey matter volume (about 86 per cent), and behaviour (about 91 per cent).
Within each domain, the models generated a sex typicality score—indicating how closely an individual’s data matched the average male or female profile. However, a person’s sex typicality in one domain did not predict their typicality in another; only a small proportion of individuals displayed a consistently male- or female-typical profile across all measures.
In the final analyses, the researchers examined interactions between sex, brain activation and behaviour through a brain-wide association approach. They confirmed measurable links between task-induced brain activation and certain behaviours within each sex, and when comparing men and women, the overall pattern was broadly similar. Isolated differences in brain-behaviour relationships did appear, but they did not preferentially involve behaviours that are heavily sex-biased.
The authors caution that the study is observational, identifying associations rather than establishing causation. It also defines sex by self-identification as male or female, rather than employing a psychosocial concept of gender. The imaging modalities used—task-based fMRI and structural gray matter measurements—capture only part of the brain’s complexity; other techniques such as resting-state fMRI or white matter connectivity could reveal different patterns of sex-based variation. The researchers call for future work to explore how these traits develop over the lifespan and change with brain aging.
The study, titled “Robust but independent sex differences in human brain function, structure, and behaviour,” lists Siyuan Liu, Bridget W. Mahony, Ethan T. Whitman, Stephen J. Gotts, Dustin Moraczewski, Adam Thomas, Alex Martin and Armin Raznahan as authors.
