Palesi, F;
Castellazzi, G;
Casiraghi, L;
Sinforiani, E;
Vitali, P;
Gandini Wheeler-Kingshott, CAM;
D'Angelo, E;
(2016)
Exploring patterns of Alteration in Alzheimer's disease brain networks: A combined structural and functional connectomics analysis.
Frontiers in Neuroscience
, 10
, Article 380. 10.3389/fnins.2016.00380.
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Abstract
Alzheimer's disease (AD) is a neurodegenerative disorder characterized by a severe derangement of cognitive functions, primarily memory, in elderly subjects. As far as the functional impairment is concerned, growing evidence supports the "disconnection syndrome" hypothesis. Recent investigations using fMRI have revealed a generalized alteration of resting state networks (RSNs) in patients affected by AD and mild cognitive impairment (MCI). However, it was unclear whether the changes in functional connectivity were accompanied by corresponding structural network changes. In this work, we have developed a novel structural/functional connectomic approach: resting state fMRI was used to identify the functional cortical network nodes and diffusion MRI to reconstruct the fiber tracts to give a weight to internodal subcortical connections. Then, local and global efficiency were determined for different networks, exploring specific alterations of integration and segregation patterns in AD and MCI patients compared to healthy controls (HC). In the default mode network (DMN), that was the most affected, axonal loss, and reduced axonal integrity appeared to compromise both local and global efficiency along posterior-anterior connections. In the basal ganglia network (BGN), disruption of white matter integrity implied that main alterations occurred in local microstructure. In the anterior insular network (AIN), neuronal loss probably subtended a compromised communication with the insular cortex. Cognitive performance, evaluated by neuropsychological examinations, revealed a dependency on integration and segregation of brain networks. These findings are indicative of the fact that cognitive deficits in AD could be associated not only with cortical alterations (revealed by fMRI) but also with subcortical alterations (revealed by diffusion MRI) that extend beyond the areas primarily damaged by neurodegeneration, toward the support of an emerging concept of AD as a "disconnection syndrome." Since only AD but not MCI patients were characterized by a significant decrease in structural connectivity, integrated structural/functional connectomics could provide a useful tool for assessing disease progression from MCI to AD.
| Type: | Article |
|---|---|
| Title: | Exploring patterns of Alteration in Alzheimer's disease brain networks: A combined structural and functional connectomics analysis |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.3389/fnins.2016.00380 |
| Publisher version: | http://doi.org/10.3389/fnins.2016.00380 |
| Language: | English |
| Additional information: | © 2016 Palesi, Castellazzi, Casiraghi, Sinforiani, Vitali, Gandini Wheeler-Kingshott and D'Angelo. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
| Keywords: | AD, connectomics, disconnection syndrome, probabilistic tractography, resting state networks |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Neuroinflammation |
| URI: | https://discovery.ucl.ac.uk/id/eprint/1528332 |
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