Back to Search Start Over

Sex differences associated with corpus callosum development in human infants: A longitudinal multimodal imaging study

Authors :
Astrid Schmied
Takahiro Soda
Guido Gerig
Martin Styner
Meghan R. Swanson
Jed T. Elison
Mark D. Shen
Robert C. McKinstry
John R. Pruett, Jr.
Kelly N. Botteron
Annette M. Estes
Stephen R. Dager
Heather C. Hazlett
Robert T. Schultz
Joseph Piven
Jason J. Wolff
Source :
NeuroImage, Vol 215, Iss , Pp 116821- (2020)
Publication Year :
2020
Publisher :
Elsevier, 2020.

Abstract

The corpus callosum (CC) is the largest connective pathway in the human brain, linking cerebral hemispheres. There is longstanding debate in the scientific literature whether sex differences are evident in this structure, with many studies indicating the structure is larger in females. However, there are few data pertaining to this issue in infancy, during which time the most rapid developmental changes to the CC occur. In this study, we examined longitudinal brain imaging data collected from 104 infants at ages 6, 12, and 24 months. We identified sex differences in brain-size adjusted CC area and thickness characterized by a steeper rate of growth in males versus females from ages 6–24 months. In contrast to studies of older children and adults, CC size was larger for male compared to female infants. Based on diffusion tensor imaging data, we found that CC thickness is significantly associated with underlying microstructural organization. However, we observed no sex differences in the association between microstructure and thickness, suggesting that the role of factors such as axon density and/or myelination in determining CC size is generally equivalent between sexes. Finally, we found that CC length was negatively associated with nonverbal ability among females.

Details

Language :
English
ISSN :
10959572
Volume :
215
Issue :
116821-
Database :
Directory of Open Access Journals
Journal :
NeuroImage
Publication Type :
Academic Journal
Accession number :
edsdoj.1c0788dfd0e948f1acb6fbeccea3e34e
Document Type :
article
Full Text :
https://doi.org/10.1016/j.neuroimage.2020.116821