A large-scale study on the effects of sex on gray matter asymmetry
Research on sex-related brain asymmetries has not yielded consistent results. Despite its importance to further understanding of normal brain development and mental disorders, the field remains relatively unexplored. Here we employ a recently developed asymmetry measure, based on the Dice coefficient, to detect sex-related gray matter asymmetries in a sample of 457 healthy participants (266 men and 191 women) obtained from 5 independent databases. Results show that women’s brains are more globally symmetric than men’s (p < 0.001). Although the new measure accounts for asymmetries distributed all over the brain, several specific structures were identified as systematically more symmetric in women, such as the thalamus and the cerebellum, among other structures, some of which are typically involved in language production. These sex-related asymmetry differences may be defined at the neurodevelopmental stage and could be associated with functional and cognitive sex differences, as well as with proneness to develop a mental disorder.
KeywordsStructural neuroimaging Global asymmetry Dice coefficient Neurodevelopment Sex differences Language
This work was supported by a Miguel Servet contract (CP09/00292) and grants PI10/02479 and PI14/00047 from the Instituto de Salud Carlos III—Subdirección General de Evaluación y Fomento de la Investigación Sanitaria—co-funded by the European Regional Development Fund (ERDF)—to GB, and contract PTA2011-4983-I from the Ministerio de Ciencia e Innovación, Spain to CS-O. We thank both openfmri.org and schizconnect.org projects for hosting the data and for making them publicly available. Data collection and sharing for the schizconnect.org project was funded by NIMH cooperative agreement 1U01 MH097435. Part of these data were downloaded from the COllaborative Informatics and Neuroimaging Suite Data Exchange tool (COINS; http://coins.mrn.org/dx) and this data collection was performed at the Mind Research Network, and funded by a Center of Biomedical Research Excellence (COBRE) Grant 5P20RR021938/P20GM103472 from the NIH to Dr. Vince Calhoun. Other parts of these data were obtained from the NU Schizophrenia Data and Software Tool (NUSDAST) database (http://central.xnat.org/REST/projects/NUDataSharing); data collection and sharing for this project was funded by NIMH grant 1R01 MH084803. The last part of the data from schizconnect.org used in this work was collected and shared by [University of Iowa, University of Minnesota, University of New Mexico, Massachusetts General Hospital] the Mind Research Network supported by the Department of Energy under Award Number DE-FG02-08ER64581.
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Conflict of interest
The authors declare that they have no conflicts of interest.
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