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Item Type: | Preprint |
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Title: | Vascular cognitive impairment in the mouse reshapes visual, spatial network functional connectivity |
Creators Name: | Hall, G.R., Boehm-Sturm, P., Dirnagl, U., Finke, C., Foddis, M., Harms, C., Koch, S.P., Kuchling, J., Madan, C.R., Mueller, S., Sassi, C., Sotiropoulos, S.N., Trueman, R.C., Wallis, M., Yildirim, F. and Farr, T.D. |
Abstract: | Connectome analysis of neuroimaging data is a rapidly expanding field to identify disease specific biomarkers. Structural diffusion MRI connectivity has been useful in individuals with radiological features of small vessel disease, such as white matter hyperintensities. Global efficiency, a network metric calculated from the structural connectome, is an excellent predictor of cognitive decline. To dissect the biological underpinning of these changes, animal models are required. We tested whether the structural connectome is altered in a mouse model of vascular cognitive impairment. White matter damage was more pronounced by 6 compared to 3 months. Global efficiency remained intact, but the visual association cortex exhibited increased structural connectivity with other brain regions. Exploratory resting state functional MRI connectivity analysis revealed diminished default mode network activity in the model compared to shams. Further perturbations were observed in a primarily cortical hub and the retrosplenial and visual cortices, and the hippocampus were the most affected nodes. Behavioural deficits were observed in the cued water maze, supporting the suggestion that the visual and spatial memory networks are affected. We demonstrate specific circuitry is rendered vulnerable to vascular stress in the mouse, and the model will be useful to examine pathophysiological mechanisms of small vessel disease. |
Keywords: | Vascular Dementia, Vascular Cognitive Impairment, White Matter, Mouse Brain Connectivity, Resting Stafunctional MRI, Diffusion Tensor Imaging, Animals, Mice |
Source: | bioRxiv |
Publisher: | Cold Spring Harbor Laboratory Press |
Article Number: | 2020.11.04.366294 |
Date: | 5 November 2020 |
Official Publication: | https://doi.org/10.1101/2020.11.04.366294 |
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