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The morphological changes in cortical parcellated regions during aging and whether these atrophies may cause brain structural network intra- and inter-lobe connectivity alterations are subjects that have been minimally explored. In this study, a novel fractal dimension-based structural network was proposed to measure atrophy of 68 parcellated cortical regions. Alterations of structural network parameters, including intra- and inter-lobe connectivity, were detected in a middle-aged group (30-45 years old) and an elderly group (50-65 years old). The elderly group exhibited significant lateralized atrophy in the left hemisphere, and most of these fractal dimension atrophied regions were included in the regions of the "last-in, first-out" model. Globally, the elderly group had lower modularity values, smaller component size modules, and fewer bilateral association fibers. They had lower intra-lobe connectivity in the frontal and parietal lobes, but higher intra-lobe connectivity in the temporal and occipital lobes. Both groups exhibited similar inter-lobe connecting pattern. The elderly group revealed separations, sparser long association fibers, commissural fibers, and lateral inter-lobe connectivity lost effect, mainly in the right hemisphere. New wiring and reconfiguring modules may have occurred within the brain structural network to compensate for connectivity, decreasing and preventing functional loss in cerebral intra- and inter-lobe connectivity.
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http://dx.doi.org/10.3390/e22080826 | DOI Listing |
FASEB J
July 2025
Sorbonne Université, Muséum National d'Histoire Naturelle, UMR CNRS 7590, Institut de Minéralogie, de Physique des Matériaux et de Cosmochimie, IMPMC, Paris, France.
The Major Facilitator Superfamily (MFS) is the largest known family of secondary transporters. These proteins share a common architecture comprising two lobes, each including 6 transmembrane (TM) helices, related by twofold pseudosymmetry. They transport a wide range of substrates through large conformational changes relying on the opening and closing of gates located on either side of biological membranes.
View Article and Find Full Text PDFAnnu Int Conf IEEE Eng Med Biol Soc
July 2024
Given the non-Euclidean topology inherent in electroencephalogram (EEG) electrode configurations, graph-based approaches, particularly graph neural networks, have shown notable success across diverse EEG classification tasks. However, since the cerebral cortex lobes function individually and/or collaboratively across diverse tasks, there exist substantial differences between intra-lobe and inter-lobe brain intrinsic functional connectivity. Existing graph networks for EEG classification are based on homogeneous graphs, yet the nature of the cerebral cortex aligns more closely with a heterogeneous graph structure.
View Article and Find Full Text PDFProg Brain Res
October 2024
Institute of Biophotonics, National Yang Ming Chiao Tung University, Taipei, Taiwan; College of Medicine, Fu-Jen Catholic University, New Taipei City, Taiwan; Applied Cognitive Neuroscience Group, Institute of Cognitive Neuroscience, University College London, London, United Kingdom; Dementia Center
Migraine, one of the most prevalent and debilitating neurological disorders, can be classified based on attack frequency into episodic migraine (EM) and chronic migraine (CM). Medication overuse headache (MOH), a type of chronic headache, arises when painkillers are overused by individuals with untreated or inadequately treated headaches. This study compares regional cortical morphological alterations and brain structural network changes among these headache subgroups.
View Article and Find Full Text PDFCereb Cortex
November 2023
Beijing Dementia Key Lab, Dementia Care and Research Center, Peking University Institute of Mental Health (Sixth Hospital), Beijing 100191, China.
Electroencephalography can assess connectivity between brain hemispheres, potentially influencing cognitive functions. Much of the existing electroencephalography research primarily focuses on undirected connectivity, leaving uncertainties about directed connectivity alterations between left-right brain hemispheres or frontal-posterior lobes in mild cognitive impairment. We analyzed resting-state electroencephalography data from 34 mild cognitive impairment individuals and 23 normal controls using directed transfer function and graph theory for directed network analysis.
View Article and Find Full Text PDFHum Brain Mapp
February 2023
Department of Radiology, First Affiliated Hospital to Army Medical University, Chongqing, People's Republic of China.
This study explored how the neural efficiency and proficiency worked in athletes with different skill levels from the perspective of effective connectivity brain network in resting state. The deconvolved conditioned Granger causality (GC) analysis was applied to functional magnetic resonance imaging (fMRI) data of 35 elite athletes (EAs) and 42 student-athletes (SAs) of racket sports as well as 39 normal controls (NCs), to obtain the voxel-wised hemodynamic response function (HRF) parameters representing the functional segregation and effective connectivity representing the functional integration. The results showed decreased time-to-peak of HRF in the visual attention brain regions in the two athlete groups compared with NC and decreased response height in the advanced motor control brain regions in EA comparing to the nonelite groups, suggesting the neural efficiency represented by the regional HRF was different in early and advanced skill levels.
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