Axonal myelination and repair, critical processes for brain development, maturation, and aging, remain controlled by sexual hormones. Whether this influence is reflected in structural brain differences between sexes, and whether it can be quantified by neuroimaging, remains controversial. Diffusion-weighted magnetic resonance imaging (dMRI) is an in vivo method that can track myelination changes throughout the lifespan. We utilize a large, multisite sample of harmonized dMRI data (n = 551, age = 9-65 years, 46% females/54% males) to investigate the influence of sex on white matter (WM) structure. We model lifespan trajectories of WM using the most common dMRI measure fractional anisotropy (FA). Next, we examine the influence of both age and sex on FA variability. We estimate the overlap between male and female FA and test whether it is possible to label individual brains as male or female. Our results demonstrate regionally and spatially specific effects of sex. Sex differences are limited to limbic structures and young ages. Additionally, not only do sex differences diminish with age, but tracts within each subject become more similar to one another. Last, we show the high overlap in FA between sexes, which implies that determining sex based on WM remains open.
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http://dx.doi.org/10.1093/cercor/bhaa220 | DOI Listing |
J Neurosci
January 2025
Department of Anatomy, Physiology, and Pharmacology, College of Veterinary Medicine, Auburn University, Auburn, AL, USA.
Animal models are commonly used to investigate developmental processes and disease risk, but humans and model systems (e.g., mice) differ substantially in the pace of development and aging.
View Article and Find Full Text PDFJ Neurointerv Surg
January 2025
Department of Neuroradiology, Medical Center - University of Freiburg, Freiburg, Germany
Background: Cerebrospinal fluid (CSF) loss in spontaneous intracranial hypotension (SIH) is accompanied by volume shifts between the intracranial compartments. This study investigated tricompartimental and longitudinal volume shifts after closure of a CSF leak.
Methods: Patients with SIH and suitable pre-therapeutic and post-therapeutic imaging for volumetric analysis were identified from our tertiary care center between 2020 and 2023.
Neuroimage
January 2025
Department of Neuroscience, Monash University, Melbourne, VIC, Australia; Gastroenterology, Immunology, Neuroscience (GIN) Discovery Program. Electronic address:
Persistent post-surgical pain (PPSP) occurs in a proportion of patients following surgical interventions. Research suggests that specific microbiome components are important for brain development and function, with recent studies demonstrating that chronic pain results in changes to the microbiome. Consumption of a high fat, high sugar (HFHS) diet can drastically alter composition of the microbiome and is a modifiable risk factor for many neuroinflammatory conditions.
View Article and Find Full Text PDFMed Image Anal
January 2025
Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA. Electronic address:
The relationship between brain connections and non-imaging phenotypes is increasingly studied using deep neural networks. However, the local and global properties of the brain's white matter networks are often overlooked in convolutional network design. We introduce TractGraphFormer, a hybrid Graph CNN-Transformer deep learning framework tailored for diffusion MRI tractography.
View Article and Find Full Text PDFAnn Clin Transl Neurol
January 2025
Department of Neuro-Urology, Balgrist University Hospital, University of Zürich, Zürich, Switzerland.
Objective: To characterize structural integrity of the lumbosacral enlargement and conus medullaris within one month after spinal cord injury (SCI).
Methods: Lumbosacral cord MRI data were acquired in patients with sudden onset (<7 days) SCI at the cervical or thoracic level approximately one month after injury and in healthy controls. Tissue integrity and loss were evaluated through diffusion tensor (DTI) and T2*-weighted imaging (cross-sectional area [CSA] measurements).
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