ArticleBrain structure & function2022
Investigating sexual dimorphism in human brain structure by combining multiple indexes of brain morphology and source-based morphometry.
Article in Brain structure & function, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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5 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.
- Complexity in disguise: a systematic review of fractal analysis in psychiatric neuroimaging.European radiology · 2026Pooled it
- Brain structural changes and molecular analyses in children with benign epilepsy with centrotemporal spikes.Pediatric research · 2024Article
- Resting-state fMRI functional connectome of C9orf72 mutation status.Annals of clinical and translational neurology · 2024Article
- Subcortical volume in middle-aged adults with fetal alcohol spectrum disorders.Brain communications · 2024Article
- Cingulate cortex morphology impacts on neurofunctional activity and behavioral performance in interference tasks.Scientific reports · 2022Article
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Authors and funding
6 authors at 2 institutions in 2 countries.
Funding
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Abstract
Computational morphometry of magnetic resonance images represents a powerful tool for studying macroscopic differences in human brains. In the present study (N participants = 829), we combined different techniques and measures of brain morphology to investigate one of the most compelling topics in neuroscience: sexual dimorphism in human brain structure. When accounting for overall larger male brains, results showed limited sex differences in gray matter volume (GMV) and surface area. On the other hand, we found larger differences in cortical thickness, favoring both males and females, arguably as a result of region-specific differences. We also observed higher values of fractal dimension, a measure of cortical complexity, for males versus females across the four lobes. In addition, we applied source-based morphometry, an alternative method for measuring GMV based on the independent component analysis. Analyses on independent components revealed higher GMV in fronto-parietal regions, thalamus and caudate nucleus for females, and in cerebellar- temporal cortices and putamen for males, a pattern that is largely consistent with previous findings.
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