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, 39 (3), 1118-1129

Functional Connectivity in Dementia With Lewy Bodies: A Within- And Between-Network Analysis


Functional Connectivity in Dementia With Lewy Bodies: A Within- And Between-Network Analysis

Julia Schumacher et al. Hum Brain Mapp.


Dementia with Lewy bodies (DLB) is a common form of dementia and is characterized by cognitive fluctuations, visual hallucinations, and Parkinsonism. The phenotypic expression of the disease may, in part, relate to alterations in functional connectivity within and between brain networks. This resting-state study sought to clarify this in DLB, how networks differed from Alzheimer's disease (AD), and whether they were related to clinical symptoms in DLB. Resting-state networks were estimated using independent component analysis. We investigated functional connectivity changes in 31 DLB patients compared to 31 healthy controls and a disease comparator group of 29 AD patients using dual regression and FSLNets. Within-network connectivity was generally decreased in DLB compared to controls, mainly in motor, temporal, and frontal networks. Between-network connectivity was mainly intact; only the connection between a frontal and a temporal network showed increased connectivity in DLB. Differences between AD and DLB were subtle and we did not find any significant correlations with the severity of clinical symptoms in DLB. This study emphasizes the importance of reduced connectivity within motor, frontal, and temporal networks in DLB with relative sparing of the default mode network. The lack of significant correlations between connectivity measures and clinical scores indicates that the observed reduced connectivity within these networks might be related to the presence, but not to the severity of motor and cognitive impairment in DLB patients. Furthermore, our results suggest that AD and DLB may show more similarities than differences in patients with mild disease.

Keywords: Alzheimer's disease; FSLNets; Parkinsonism; basal ganglia; dual regression; neurodegeneration; resting-state networks.


Figure 1
Figure 1
Spatial maps of the 27 resting‐state networks (RSNs) obtained from the independent healthy control group. RSN maps are thresholded at 3 < z < 12. Images are shown in radiological convention, that is, the left side of the image corresponds to the right hemisphere [Color figure can be viewed at]
Figure 2
Figure 2
Dual regression results for comparison between DLB and HC. RSN maps are shown in red‐yellow. (a–f) Clusters with decreased connectivity in DLB; HC > DLB, p < .05, threshold free cluster enhancement (TFCE) corrected, shown in blue. (g) Clusters with increased connectivity in DLB; DLB > HC, p < .05, TFCE corrected, shown in green. See Table 2 for more information on cluster locations and sizes. All images are shown in radiological convention [Color figure can be viewed at]
Figure 3
Figure 3
Correlation matrices from FSLNets analysis for (a) HC, (b) AD, and (c) DLB. Upper triangular matrices show full correlations while partial correlations are plotted in the lower triangular matrices. (d) Boxplots show z scores for edges with significant group differences for full correlations (black squares in panel a–c, p < .05, FWE corrected for multiple comparisons). OPN, occipital pole network; LFPN, left fronto‐parietal network; TPN, temporal pole network; ACN, anterior cingulate network [Color figure can be viewed at]

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