Summary: A new, large-scale study has reshaped our understanding of neurodevelopment by showing that a child’s socioeconomic environment leaves a stronger and more consistent imprint on the developing brain than any single biological, behavioral, or psychological factor. Investigators analyzed neuroimaging data from nearly 12,000 children ages 9–10 enrolled in the NIH-funded Adolescent Brain Cognitive Development (ABCD) Study to compare dozens of lifestyle, health, and environmental measures against brain structure and function.
Scientists examined 649 distinct variables across 12 categories and found that socioeconomic indicators explained roughly 16% of the variance in measures of brain function—far more than factors such as parenting, medical history, or IQ. Rather than indicating an innate difference in intelligence, the socioeconomic signature corresponded to patterns typically produced by chronic stress and disrupted sleep, suggesting a modifiable pathway linking environment to brain health.
Key Facts
- Socioeconomics dominate: Of the top 40 variables associated with functional brain networks, 37 were socioeconomic measures; of the top 40 linked to cortical structure, 35 were socioeconomic. Family income, homeownership, neighborhood poverty rates, and access to transportation stood out among the strongest predictors.
- Sensory-motor networks affected: The cortical regions most strongly tied to socioeconomic disadvantage were primary motor and sensory areas—regions that are highly sensitive to daily sleep loss and stress—rather than higher-order cognitive regions associated with complex thinking.
- Rethinking brain-IQ links: The researchers found that many previously reported associations between brain anatomy and IQ were confounded by socioeconomic factors. After statistically adjusting for socioeconomic status, about 70% of brain–IQ associations lost significance.
- IQ and high-affluence groups: In analyses restricted to children from high-socioeconomic backgrounds, IQ showed no measurable correlation with brain structure or functional network strength, indicating that the apparent brain correlates of IQ in broader samples may reflect environmental privilege rather than innate neurobiology.
- Cortical thickness and functional connectivity: Using advanced MRI measures, the team assessed cortical thickness and the strength of resting functional networks to map how nonimaging variables relate to brain organization.
- Modifiable targets: Because the socioeconomic pattern overlapped with markers of sleep deprivation and stress, the study suggests practical, changeable targets—improving sleep quality and reducing chronic stress—that could shift neurodevelopmental trajectories.
Source: WUSTL
What shapes a child’s brain? Children’s brains are molded by many interacting influences—biological, behavioral, social, and environmental. To understand which of these leave the most stable marks on brain structure and function, researchers at Washington University School of Medicine compared hundreds of variables on the same footing and mapped them to neuroimaging measures from the ABCD Study.
Their analyses show that socioeconomic conditions—both at the family level and in the surrounding neighborhood—have the strongest and most reproducible relationship with children’s brain organization. These effects manifested primarily in brain regions that respond to arousal, sleep deprivation, and stress, rather than in classical higher-order cognitive circuits.
“We set out to compare hundreds of influences on the developing brain on a level playing field, and for the first time at this scale, we showed that socioeconomic conditions leave the deepest imprint of any factor we looked at,” said senior author Nico U. Dosenbach, MD, PhD. He and colleagues emphasize that the socioeconomic signal appears to operate largely through everyday burdens like poor sleep and chronic stress—factors that can be addressed.
Mapping the factors associated with brain structure and function
Traditional brain-wide association studies (BWAS) have linked brain imaging measures to single traits such as IQ or psychiatric symptoms, but often without simultaneously accounting for diverse environmental and behavioral influences. To broaden that approach, the WashU team included 649 nonimaging variables grouped into 12 categories:
- socioeconomics
- screen time
- cognitive abilities (test scores, memory)
- demographics (race, sex)
- culture and environment (language, religion, noise, pollution)
- physical health
- mental health
- social adjustment (friendships, bullying)
- substance use and exposure
- parenting
- personality traits (extraversion, self-control)
- medical history
Using MRI measures of cortical thickness and resting-state functional connectivity, the team asked which variables consistently mapped onto brain structure or network strength, and whether apparent brain–IQ links held up after accounting for socioeconomic context. Data from 11,878 children in the ABCD cohort enabled robust, multivariable comparisons across a large, diverse sample.
Socioeconomic measures clustered at the top of the results: 37 of the top 40 variables associated with functional networks and 35 of the top 40 tied to cortical structure were socioeconomic in nature. Beyond family income and homeownership, key neighborhood-level features—local poverty rates and transportation access—strongly predicted brain differences. Sleep, screen time, and stress-related measures also appeared among the influential variables.
Importantly, socioeconomic associations concentrated in motor and sensory regions, which are known to reflect arousal and sleep states. Cognitive control and reasoning areas in frontal and parietal cortices showed weaker ties to socioeconomic variables, suggesting that the visible brain differences reflect day-to-day burdens (fatigue, stress) rather than an intrinsic reduction in cognitive capacity.
Brain imaging reveals no reliable signature of IQ scores
Searches for a clear neuroanatomical signature of intelligence have produced inconsistent findings. This study suggests why: many previous brain–IQ correlations were likely confounded by socioeconomic privilege. When the researchers statistically removed the influence of socioeconomic status, roughly 70% of brain–IQ associations disappeared. Analyses limited to children from higher socioeconomic backgrounds found no correlation between IQ and brain measures.
“If we look at children’s brain scans, we can tell how well off their family is and how much sleep and screen time they get, but we can’t tell their IQ, at least not after adjusting for socioeconomic opportunity,” said first author Scott Marek, PhD. The results point to environmental drivers—sleep and stress—as plausible mechanisms behind previously reported IQ–brain links, and, crucially, as modifiable targets for intervention.
Funding: This research received support from multiple NIH grants, the National Science Foundation, the Jacobs Foundation, and the Kiwanis Foundation.
Conflict of interest disclosures note that several authors have financial interests related to FIRMM motion monitoring software and are affiliated with Turing Medical Inc.
Key Questions Answered:
A: No. The study indicates that brains of children from lower socioeconomic backgrounds show patterns resembling chronic sleep loss and stress, particularly in sensory-motor regions. These are not fixed deficits in intelligence but signs of modifiable physiological burden. Improving sleep and reducing stress could change these patterns.
A: By statistically controlling for socioeconomic influence and by analyzing only high-socioeconomic-status children. Adjusting for socioeconomic factors eliminated most brain–IQ associations, and in the affluent-only subgroup IQ showed no measurable correlation with brain structure or network strength, suggesting previously observed links were confounded by environment.
A: Prioritize sleep hygiene and stress reduction. Consistent bedtimes, limiting screens before sleep, and creating calm routines are low-cost strategies that can protect children’s sleep and lower daily stress—factors shown to relate to healthier brain patterns.
Editorial Notes:
- This article was edited by a Neuroscience News editor and reviewed against the full journal paper.
- Additional context was provided by editorial staff to clarify implications and limitations of the research.
About this research news
Author: Jessica Church
Source: WUSTL
Contact: Jessica Church – WUSTL
Image: Image credited to Neuroscience News
Original Research: Open access. “Patterns of brain-wide associations reflect socioeconomics” by Marek S et al., published in Science. DOI: 10.1126/science.aee6213
Abstract
Patterns of brain-wide associations reflect socioeconomics
INTRODUCTION
Brain-wide association studies (BWAS) aim to relate individual differences in behavior or living conditions—such as IQ or socioeconomic status—to variability in brain function and structure using MRI-derived measures like resting-state functional connectivity and cortical thickness. While large samples improve reproducibility, the relative importance of environmental variables and how they shape brain patterns has remained unclear.
RATIONALE
With thousands of participants, researchers can map hundreds of nonimaging variables to brain measures simultaneously and compare them against known neurobiological patterns. For example, sleep deprivation and stress characteristically affect primary motor and sensory regions, whereas higher-order cognition involves frontal and parietal areas. Using these reference patterns helps interpret the meaning of BWAS results and identify potential confounds.
RESULTS
Across 649 nonimaging variables in 9- to 10-year-olds, socioeconomic measures showed the strongest, most replicable brain-wide associations. The single strongest association related to socioeconomic features of a child’s zip code. The socioeconomic brain pattern aligned spatially with markers of arousal and stress and negatively correlated with maps of higher-order cognition. IQ’s BWAS map resembled the socioeconomic pattern; when socioeconomics were accounted for, brain–IQ associations diminished and shifted toward cognitive regions.
CONCLUSION
Neighborhood and family socioeconomic circumstances have a more powerful and reproducible relationship with brain function and structure in childhood than other variables tested. The dominant socioeconomic pattern matches known effects of sleep deprivation and stress, primarily affecting primary motor and sensory regions while sparing frontal and parietal cognitive areas. These findings indicate that environmental factors indexed by socioeconomic status—especially sleep and stress—are principal axes shaping childhood brain organization and that accounting for socioeconomics improves the interpretation and generalizability of BWAS results.