A neuroimaging analysis from the ENIGMA Eating Disorders Working Group published in JAMA Psychiatry reveals that bulimia nervosa is linked to structural brain differences, specifically reduced nucleus accumbens volume and smaller temporal cortical surface area, offering concrete neurobiological insights into the condition.
Unlocking the Neurobiology of Bulimia Nervosa
Bulimia nervosa stands as the second most common eating disorder globally, carrying a heavy disease burden, yet its underlying brain architecture has stayed stubbornly elusive for decades. Past neuroimaging efforts often stumbled over small sample sizes and produced conflicting results. To cut through this fog, researchers launched a massive case-control study utilizing three-dimensional T1-weighted MRI scans and clinical data gathered between February 2022 and October 2025.
The global investigation pooled data across 17 international cohorts coordinated by the ENIGMA consortium. The final sample focused exclusively on 786 female participants, split between 369 individuals diagnosed with bulimia nervosa and 417 healthy controls. The mean age across the cohort sat at 23.6 years, spanning a wide age range from 12.0 to 53.6 years. Using standardized ENIGMA pipelines, researchers extracted regional cortical thickness, surface area, and subcortical volumes to map out structural divergences.
Pinpointing Reduced Nucleus Accumbens and Temporal Cortex Alterations
When researchers stacked the brain scans of affected participants against healthy controls, distinct anatomical markers emerged. Individuals with bulimia nervosa showed a lower nucleus accumbens volume, yielding a Cohen d of -0.20 with a 95% confidence interval ranging from -0.34 to -0.06. They also exhibited a lower surface area in the superior temporal cortex (d, -0.26; 95% CI, -0.41 to -0.12) and the transverse temporal cortex (d, -0.24; 95% CI, -0.38 to -0.10). Interestingly, the analysis detected no significant group-level differences in overall cortical thickness.

Most of these structural variations held steady even after adjusting for body mass index (BMI), illness duration, depressive symptoms, psychotropic medication use, and purging behaviors. The findings provide tangible proof that the condition ties directly to circuits governing reward, motivation, sensory processing, and social cognition. As Laura A. Berner, PhD, Director of the Center for Computational Psychiatry at Mount Sinai, noted about the scope of the project, “This study gives us the clearest evidence to date that bulimia nervosa is associated with reproducible differences in brain structure. We were surprised that the differences we identified in the brain’s outer layer involved a structural feature that is largely established early in development.”
Symptom Severity and Widespread Structural Shifts
Drilling down into symptom specifics revealed that binge-eating frequency correlates with broader anatomical changes. More frequent binge episodes tracked with a lower surface area across several additional regions, including the insula and the orbitofrontal cortex, with correlation coefficients ranging from -0.20 to -0.14. These areas play vital roles in cognitive control, reward value estimation, and emotional awareness.
By contrast, the frequency of compensatory behaviors—which clinicians typically rely on to gauge disease severity—showed no significant anatomical links whatsoever. This divergence suggests that specific clinical features like binge eating carry distinct neurobiological fingerprints. Because the study captured participants at a single snapshot in time, researchers emphasize that longitudinal work must follow to untangle whether these brain differences act as pre-existing vulnerabilities or consequences of the illness.
“Our findings raise important questions about whether some of these brain differences could be markers of vulnerability to developing the illness. At the same time, the findings should not be interpreted to mean that the brain is fixed, or that a person’s outcome is predetermined,”Dr. Berner stated.“We are excited about the next steps: understanding what these findings mean for the function of the affected brain circuits, and how these insights can ultimately help us identify better targets for prevention and treatment.”
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