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Background: Although white matter hyperintensity (WMH) is closely associated with cognitive decline, the precise neurobiological mechanisms underlying this relationship are not fully elucidated. Connectome studies have identified a primary-to-transmodal gradient in functional brain networks that support the spectrum from sensation to cognition. However, whether connectome gradient structure is altered as WMH progresses and how this alteration is associated with WMH-related cognitive decline remain unknown.
Methods: A total of 758 WMH individuals completed cognitive assessment and resting-state functional MRI (rs-fMRI). The functional connectome gradient was reconstructed based on rs-fMRI by using a gradient decomposition framework. Interrelations among the spatial distribution of WMH, functional gradient measures, and specific cognitive domains were explored.
Results: As the WMH volume increased, the executive function (r = -0.135, p = 0.001) and information-processing speed (r = -0.224, p = 0.001) became poorer, the gradient range (r = -0.099, p = 0.006), and variance (r = -0.121, p < 0.001) of the primary-to-transmodal gradient reduced. A narrower gradient range (r = 0.131, p = 0.001) and a smaller gradient variance (r = 0.136, p = 0.001) corresponded to a poorer executive function. In particular, the relationship between the frontal/occipital WMH and executive function was partly mediated by gradient range/variance of the primary-to-transmodal gradient.
Conclusions: These findings indicated that WMH volume, the primary-to-transmodal gradient, and cognition were interrelated. The detrimental effect of the frontal/occipital WMH on executive function was partly mediated by the decreased differentiation of the connectivity pattern between the primary and transmodal areas.
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http://dx.doi.org/10.1111/cns.14843 | DOI Listing |
Front Netw Physiol
August 2025
Neural Information Processing Group, Fakultät IV, Technische Universität Berlin, Berlin, Germany.
The human brain is a complex dynamical system which displays a wide range of macroscopic and mesoscopic patterns of neural activity, whose mechanistic origin remains poorly understood. Whole-brain modelling allows us to explore candidate mechanisms causing the observed patterns. However, it is not fully established how the choice of model type and the networks' spatial resolution influence the simulation results, hence, it remains unclear, to which extent conclusions drawn from these results are limited by modelling artefacts.
View Article and Find Full Text PDFNeuroinformatics
August 2025
Tianjin Key lab of cognitive computing and application, College of Intelligence and Computing, Tianjin University, Yaguan Road, Tianjin, 300350, Tianjin, China.
Early diagnosis of mild hepatic encephalopathy is important for the reversion of hepatic encephalopathy. Brain hyper-connectivity networks with hyperedges have showed good performance for diagnosis of neurological disorders. However, the previous hyper-connectivity networks is essentially low-level since the temporal synchronization of regional signal fluctuation is merely considered.
View Article and Find Full Text PDFFront Neurosci
July 2025
Department of Radiology, Boston Children's Hospital and Harvard Medical School, Boston, MA, United States.
Early and accurate assessment of brain microstructure using diffusion Magnetic Resonance Imaging (dMRI) is crucial for identifying neurodevelopmental disorders in neonates, but remains challenging due to low signal-to-noise ratio (SNR), motion artifacts, and ongoing myelination. In this study, we propose a rotationally equivariant Spherical Convolutional Neural Network (sCNN) framework tailored for neonatal dMRI. We predict the Fiber Orientation Distribution (FOD) from multi-shell dMRI signals acquired with a reduced set of gradient directions (30% of the full protocol), enabling faster and more cost-effective acquisitions.
View Article and Find Full Text PDFbioRxiv
July 2025
Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA.
The mossy fiber (MF) connections to pyramidal cells in hippocampal CA3 are hypothesized to participate in pattern separation and memory encoding, yet no large-scale neuronal wiring diagram exists for these connections. We assembled a 3D electron microscopy volume (~1×1×0.1mm) from mouse hippocampal CA3.
View Article and Find Full Text PDFCNS Neurosci Ther
August 2025
Department of Radiology, The Third Affiliated Hospital of Zunyi Medical University (The First People's Hospital of Zunyi), Zunyi, Guizhou, China.
Background: The prevalence of autism spectrum disorder (ASD) is significantly higher in males than in females; although the underlying etiology remains unclear. This study aimed to investigate the multi-scale reorganization of brain networks in preschool-aged boys with ASD and their impact on clinical symptoms.
Methods: A total of 54 children with ASD (40 boys and 14 girls) and 44 typically developing (TD) children (28 boys and 16 girls), aged between 2 and 6 years, were recruited for this study.