Ovarian hormones fluctuations across the menstrual cycle are experienced by about 58% of women in their fertile age. Maladaptive brain sensitivity to these changes likely leads to the severe psychological, cognitive, and physical symptoms repeatedly experienced by women with Premenstrual Dysphoric Disorder (PMDD) during the late luteal phase of the menstrual cycle. However, the neuroanatomical correlates of these symptoms are unknown. The relationship between grey matter structure and PMDD symptom severity was delineated using structural magnetic resonance imaging during the late luteal phase of fifty-one women diagnosed with PMDD, combined with Voxel- and Surface-Based Morphometry, as well as subcortical volumetric analyses. A negative correlation was found between depression-related symptoms and grey matter volume of the bilateral amygdala. Moreover, the severity of affective and somatic PMDD symptoms correlated with cortical thickness, gyrification, sulcal depth, and complexity metrics, particularly in the prefrontal, cingulate, and parahippocampal gyri. The present findings provide the first evidence of grey matter morphological characteristics associated with PMDD symptomatology in brain regions expressing ovarian hormone receptors and of relevance to cognitive-affective functions, thus potentially having important implications for understanding how structural brain characteristics relate to PMDD symptomatology.
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http://dx.doi.org/10.1038/s41598-022-07109-3 | DOI Listing |
Neurol Genet
February 2025
Memory Center, Keio University School of Medicine, Tokyo, Japan.
Background And Objectives: A previous postmortem study of men with Christianson syndrome, a disorder caused by loss-of-function mutations in the gene , reported a mechanistic link between pathologic tau accumulation and progressive symptoms such as cerebellar atrophy and cognitive decline. This study aimed to characterize the relationships between neuropathologic manifestations and tau accumulation in heterozygous women with mutation.
Methods: We conducted a multimodal neuroimaging and plasma biomarker study on 3 middle-aged heterozygous women with mutations (proband 1: mid-50s; proband 2: early 50s; proband 3: mid-40s) presenting with progressive extrapyramidal symptoms.
Sci Rep
January 2025
Department of Radiology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330006, Jiangxi, China.
The conventional statistical approach for analyzing resting state functional MRI (rs-fMRI) data struggles to accurately distinguish between patients with multiple sclerosis (MS) and those with neuromyelitis optic spectrum disorders (NMOSD), highlighting the need for improved diagnostic efficacy. In this study, multilevel functional metrics including resting state functional connectivity, amplitude of low frequency fluctuation (ALFF), and regional homogeneity (ReHo) were calculated and extracted from 116 regions of interest in the anatomical automatic labeling atlas. Subsequently, classifiers were developed using different combinations of these selected features to distinguish between MS and NMOSD.
View Article and Find Full Text PDFProg Neuropsychopharmacol Biol Psychiatry
January 2025
MOE-LCSM, School of Mathematics and Statistics, Hunan Normal University, Changsha 410006, PR China; Key Laboratory of Applied Statistics and Data Science, Hunan Normal University, College of Hunan Province, Changsha 410006, PR China. Electronic address:
Aging of the human brain involves intricate biological processes, resulting in complex changes in structure and function. While the effects of aging on gray matter (GM) connectivity are extensively studied, white matter (WM) functional changes have received comparatively less attention. This study examines age-related WM functional dynamics using resting-state fMRI across the adult lifespan.
View Article and Find Full Text PDFNeuroimage
January 2025
Department of Radiology, Columbia University Irving Medical Center, New York, NY; Department of Biomedical Engineering, Columbia University, New York, NY. Electronic address:
Background: The cortical gray matter-white matter interface (GWI) is a natural transition zone where the composition of brain tissue abruptly changes and is a location for pathologic change in brain disorders. While diffusion magnetic resonance imaging (dMRI) is a reliable and well-established technique to characterize brain microstructure, the GWI is difficult to assess with dMRI due to partial volume effects and is normally excluded from such studies.
Methods: In this study, we introduce an approach to characterize the dMRI microstructural profile across the GWI and to assess the sharpness of the microstructural transition from cortical gray matter (GM) to white matter (WM).
Neurophysiol Clin
January 2025
Developmental Neurosciences, UCL Great Ormond Street Institute of Child Health, London, WC1N 1EH, UK; Department of Neurosurgery, Great Ormond Street Hospital for Children, London, WC1N 3JH, UK.
Objectives: Computer-assisted planning (CAP) allows faster SEEG planning and improves grey matter sampling, orthogonal drilling angles to the skull, reduces risk scores and minimises intracerebral electrode length. Incorporating prior SEEG trajectories enhances CAP planning, refining output with centre-specific practices. This study significantly expands on the previous work, compares priors libraries between two centres, and describes differences between SEEG in adults and children in these centres.
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