Kuceyeski et al. (bioRxiv preprint, Feb 2026) report that sex differences in brain connectivity are minimal in childhood but increase "drastically" at puberty and continue diverging through adulthood, based on fMRI data from 1,286 people aged 8–100. The study is not peer-reviewed. The claims it makes cannot be supported by the study design it uses.

Cross-sectional data cannot track development

This study scanned different people at different ages — it did not follow the same individuals over time. Describing age-stratified snapshots from different people as showing how sex differences "evolve over the lifespan" is methodologically misleading. Older participants represent survival-enriched cohorts with systematically different health profiles, education levels, socioeconomic backgrounds, and life experiences than younger cohorts born decades later. These cohort effects cannot be disentangled from true developmental trajectories without longitudinal data.

An 80-year-old woman scanned today grew up in the 1940s–50s with radically different educational access, occupational opportunities, physical activity patterns, and social roles than a 20-year-old woman scanned today. The brain connectivity differences between them reflect six decades of divergent gendered experience layered on top of any biological signal. Calling this "development" is a category error.

The brain mosaic problem

Joel et al. (2015) demonstrated that individual brains are heterogeneous mosaics of features rather than internally consistent "male" or "female" types. This finding has held up better than strict dimorphism models. More critically, many reported sex differences in brain connectivity are eliminated when total brain volume is controlled for — suggesting allometric scaling, not sex-specific architecture, drives much of the observed variance.

The actual effect size of sex on brain connectivity is small and critically sensitive to methodology. Current brain connectivity findings do not adequately explain observed male/female differences in behavior, interests, or mental health, raising fundamental questions about their functional significance.

The neuroplasticity confound is fatal

Brain connectivity is shaped by experience throughout life. Men and women have systematically different life trajectories: physical activity patterns, occupational exposures, caregiving responsibilities, stress profiles, and social interactions. This study has no data on gender identity, occupation, daily activities, or lived experience. It cannot distinguish biological sex effects from the neural signatures of gendered socialization.

This is not a minor limitation — it is a validity crisis for causal interpretation. Observed connectivity divergences in youth may reflect different rates of brain maturation between sexes (developmental tempo) rather than categorical dimorphic traits. Without controlling for experience, every "sex difference" found could be an "experience difference" misattributed to biology.

The AI tool raises overfitting concerns

The study uses "Krakencoder," an AI/ML classifier, to identify sex-linked connectivity patterns in ~1,286 subjects. Complex AI pattern recognition applied to relatively small neuroimaging samples with no apparent pre-registration creates serious multiple comparisons and overfitting risks. High classification accuracy does not prove biological dimorphism — ML classifiers can achieve impressive performance by aggregating many individually tiny, potentially noise-driven effects. Without independent validation on external datasets, claims of discovering "true" sex-based connectivity patterns are premature.

The depression extrapolation is reverse inference

The suggestion that stronger default mode network (DMN) connectivity in women explains higher depression rates is textbook reverse inference. Causal claims linking DMN hyperconnectivity to depression rely on correlation; longitudinal evidence establishing directionality is lacking. Does DMN hyperconnectivity cause depression, or does depression and its associated rumination produce hyperconnectivity? Without prospective studies showing connectivity changes precede symptom onset, or intervention studies demonstrating causal manipulation (e.g., TMS modulating DMN connectivity reduces depression), this remains speculative.

Extending a cross-sectional connectivity observation to a causal explanation for sex differences in psychopathology, in a preprint, without peer review, is precisely the kind of inferential overreach that generates misleading headlines.

Bottom line

The study documents statistical associations between sex and brain connectivity patterns across age groups. Everything beyond that — developmental trajectories, biological causation, mental health implications — is interpretive overreach unsupported by the cross-sectional design, uncontrolled for experience, and not yet peer-reviewed. Brain connectivity differences between men and women are real but small, methodologically fragile, and cannot be attributed to sex biology without ruling out the lifelong experience confound. No study has done this. This one does not try.

Research powered by BIOS.