Athanasia Metoki, Roselyne J Chauvin, Evan M Gordon, Timothy O Laumann, Benjamin P Kay, Babatunde Adeyemo, Samuel R Krimmel, Scott Marek, Anxu Wang, Andrew N Van, Noah J Baden, Vahdeta Suljic, Kristen M Scheidter, Julia Monk, Forrest I Whiting, Nadeshka J Ramirez-Perez, Deanna M Barch, Aristeidis Sotiras, Nico U F Dosenbach
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引用次数: 0
Abstract
Understanding sex differences in the adolescent brain is crucial, as they relate to sex-specific neurological and psychiatric conditions. Predicting sex from adolescent brain data may reveal how these differences influence neurodevelopment. Recently, attention has shifted toward socially-identified gender (distinct from sex assigned at birth) recognizing its explanatory power. This study evaluates whether resting-state functional connectivity (rsFC), cortical thickness, or cortical volume better predicts sex and sex/gender alignment (congruence between sex and gender) in preadolescents. Using Adolescent Brain Cognitive Development (ABCD) Study data and machine learning, rsFC predicted sex more accurately (85 %) than cortical thickness (76 %) and cortical volume (70 %). Brain regions most predictive of sex belonged to association (default mode, dorsal attention, parietal memory) and visual networks. The rsFC classifier trained on sex/gender aligned youth classified more accurately unseen youth with sex/gender alignment (n = 2013) than unalignment (n = 1116). The female rsFC sex profile was positively associated with sex/gender alignment, while in males, there was a negative association. However, neither brain modality predicted sex/gender alignment. These findings suggest that while rsFC predicts sex in the adolescent brain more accurately, it does not directly capture sex/gender alignment, underscoring the need for further investigation into the neural underpinnings of gender.
期刊介绍:
The journal publishes theoretical and research papers on cognitive brain development, from infancy through childhood and adolescence and into adulthood. It covers neurocognitive development and neurocognitive processing in both typical and atypical development, including social and affective aspects. Appropriate methodologies for the journal include, but are not limited to, functional neuroimaging (fMRI and MEG), electrophysiology (EEG and ERP), NIRS and transcranial magnetic stimulation, as well as other basic neuroscience approaches using cellular and animal models that directly address cognitive brain development, patient studies, case studies, post-mortem studies and pharmacological studies.