Regression of functional brain networks in early Alzheimer’s disease
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1
Technische Universität München, Germany
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2
Ludwig-Maximilians-Universitaet, Germany
The maturing brain has recently been analyzed with resting-state functional connectivity MRI (rs-fcMRI). Spatial patterns of synchronous, intrinsic brain activity were found to be similar to resting-state networks (RSNs) previously described in adults. However distant regions of the default network have only been sparsely connected. The brain functional connectivity (FC) has also been analyzed in subjects at a later stage of life span. Here a disruption of long-range connections was reported that split the default network in an anterior and posterior part. Recently we described selectively disturbed default and executive attention networks among several RSNs in patients with mild cognitive impairment (MCI) at high risk for Alzheimer‘s Disease (AD). Are long-range connections in age-associated disorders like AD affected by pathological changes prior to short-range connections? We analyzed RSNs of healthy subjects and patients with MCI at high risk for AD for the influence of regional proximity on FC. Methods: We constructed spherical ROIs (r = 6mm) around previ¬ously described peak voxel of 4 RSNs and extracted the voxelwise BOLD timecourse (tc). For each ROI the first eigenvector was derived with singular value decomposition yielding the most prominent proportion in the BOLD signal. The tc was bandpass-filtered (0.009 < f < 0.079Hz) and the signal from global gray matter, CSF and deep white matter was removed from the data through linear regression. A Fisher’s Z-transformation was applied to yield normal distribution. We then calculated the pairwise Pearson‘s correlation coefficients (r) for the 31 ROIs in both groups. Between-Group effects were calculated using two-sample t-tests and a correction for multiple comparisons was applied. The cross-correlation matrices of both groups were transformed in a two/three-dimensional functional space using multi-dimensional scaling (MDS). The purpose of MDS is to provide a visual representation of the pattern of proximities (i.e., similarities or distances) among a set of objects (e.g. distances of several cities are projected on a map). To best conform the maps of all subjects a final procrustes analysis was applied. Procrustes method is used to align several shapes by rotating, shifting and stretching similar to warping images in the SPM normalization step. Results: The bootstrap analysis revealed no differences in the variance of all ROIs between the two groups proofing the homogeneity of the data. The cross-correlation matrices yielded 180 significant pairs with eight correlations significantly differing between patients and controls. The correlations in four right hemispheric pairs and left PCC/HC were absent in patients while the correlation between right DLPFC and inferior temporal gyrus increased in this group. The analysis of the functional space revealed an explicit distribution across functionally defined dimensions in controls that was absent in patients. At the same time the functional space of patients was clearly explained by anatomically labeled dimensions, which was less prominent in controls. Discussion: We provide evidence for a disruption of interlobar long-range connections in early stages of AD. The transformation of the correlation matrix in a functional distance space further suggests an arrangement of the brain space along two axes: a structural (anterior-posterior) and a functional (intrinsic-extrinsic) axis. In the light of findings in developmental rs-fcMRI we interpret these results as a regression of functional brain networks in early AD that have been developed during lifetime while short-range connections are highly preserved.
Conference:
10th International Conference on Cognitive Neuroscience, Bodrum, Türkiye, 1 Sep - 5 Sep, 2008.
Presentation Type:
Poster Presentation
Topic:
Cognitive Aging
Citation:
Riedl
V,
Sorg
C and
Wohlschlaeger
A
(2008). Regression of functional brain networks in early Alzheimer’s disease.
Conference Abstract:
10th International Conference on Cognitive Neuroscience.
doi: 10.3389/conf.neuro.09.2009.01.176
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Received:
08 Dec 2008;
Published Online:
08 Dec 2008.
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Correspondence:
Valentin Riedl, Technische Universität München, Munich, Germany, riedl@lrz.tum.de