ID 326 – Functional connectivity alterations and their relation to pathophysiological changes in mild cognitive impairment. Issue 3 (March 2016)

• Record Type: Journal Article
• Authors: Bujnoskova, E.; Marecek, R.; Mikl, M.; Fousek, J.; Selnes, P.; Hessen, E.; Bjornerud, A.; Fladby, T.; Rektorova, I.
• Is Part Of: Clinical neurophysiology. Volume 127:Issue 3(2016:Mar.)
• Page Start: e126
• Page End: e127
• Publication Date: 2016-03
• Subjects: Neurophysiology -- Periodicals; Electroencephalography -- Periodicals; Electromyography -- Periodicals; Neurology -- Periodicals; 612.8
• DOI: 10.1016/j.clinph.2015.11.429
• Languages: English
• ISSNs: 1388-2457

Abstract

Abstract : So far many studies have addressed the issue of connectivity changes in mild cognitive impairment (MCI) and Alzheimer's disease (AD) using different methods, including whole-brain network analyses describing structural and functional topology. In this study we address an association between network topology and brain pathology in MCI. We investigated functional connectivity of MCI subjects ( n = 84) and age-matched healthy controls (HC; n = 32) defined on AAL atlas. In the MCI group we assessed how changes in brain topology correlate with cognitive performance and CSF levels of AD biomarkers in order to shed further light on underlying pathophysiological mechanisms. We used following parameters to describe brain topology: clustering coefficient, path length, node strength, and eigenvector centrality. We found shorter global path length, changes in frontal, occipital and subcortical regions, and more homogeneous hub distribution in MCI as compared to HC. Worse cognitive performance was related to topological changes in mentioned regions. Network properties correlated with CSF biomarkers in frontal and occipital regions. We observed a shift in MCI networks towards random topology with extensive regional changes, parallels can be found in literature. Network results are supported by cognitive results and CSF biomarkers levels, combined bringing unique information to current knowledge of MCI changes.