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Cortical Thickness and Surface Area Networks in Healthy Aging, Alzheimer’s Disease and Behavioral Variant Fronto-Temporal Dementia
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Roger T Staff,
Trevor Ahearn,
Alison D Murray,
Claude M Wischik
International Journal of Neural Systems, Volume: 29, Issue: 06, Start page: 1850055
Swansea University Author:
Vesna Vuksanovic
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DOI (Published version): 10.1142/s0129065718500557
Abstract
Models of the human brain as a complex network of inter-connected sub-units are important in helping to understand the structural basis of the clinical features of neurodegenerative disorders. The aim of this study was to characterize in a systematic manner the differences in the structural correlat...
| Published in: | International Journal of Neural Systems |
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| ISSN: | 0129-0657 1793-6462 |
| Published: |
World Scientific Pub Co Pte Lt
2019
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| Online Access: |
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa60502 |
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| Abstract: |
Models of the human brain as a complex network of inter-connected sub-units are important in helping to understand the structural basis of the clinical features of neurodegenerative disorders. The aim of this study was to characterize in a systematic manner the differences in the structural correlation networks in cortical thickness (CT) and surface area (SA) in Alzheimer’s disease (AD) and behavioral variant Fronto-Temporal Dementia (bvFTD). We have used the baseline magnetic resonance imaging (MRI) data available from a large population of patients from three clinical trials in mild to moderate AD and mild bvFTD and compared this to a well-characterized healthy aging cohort. The study population comprised 202 healthy elderly subjects, 213 with bvFTD and 213 with AD. We report that both CT and SA network architecture can be described in terms of highly correlated networks whose positive and inverse links map onto the intrinsic modular organization of the four cortical lobes. The topology of the disturbance in structural network is different in the two disease conditions, and both are different from normal aging. The changes from normal are global in character and are not restricted to fronto-temporal and temporo-parietal lobes, respectively, in bvFTD and AD, and indicate an increase in both global correlational strength and in particular nonhomologous inter-lobar connectivity defined by inverse correlations. These inverse correlations appear to be adaptive in character, reflecting coordinated increases in CT and SA that may compensate for corresponding impairment in functionally linked nodes. The effects were more pronounced in the cortical thickness atrophy network in bvFTD and in the surface area network in AD. Although lobar modularity is preserved in the context of neurodegenerative disease, the hub-like organization of networks differs both from normal and between the two forms of dementia. This implies that hubs may be secondary features of the connectivity adaptation to neurodegeneration and may not be an intrinsic property of the brain. However, analysis of the topological differences in hub-like organization CT and SA networks, and their underlying positive and negative correlations, may provide a basis for assisting in the differential diagnosis of bvFTD and AD. |
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| Keywords: |
Structural correlation networks; behavioral variant frontotemporal dementia; Alzheimer’s disease |
| College: |
Faculty of Medicine, Health and Life Sciences |
| Funders: |
We would like to acknowledge the support of the Maxwell compute cluster funded by the University of Aberdeen. |
| Issue: |
06 |
| Start Page: |
1850055 |