Abstract
Functional magnetic resonance imaging recordings in the resting-state (RS) from the human brain are characterized by spontaneous low-frequency fluctuations in the blood oxygenation level dependent signal that reveal functional connectivity (FC) via their spatial synchronicity. This RS study applied network analysis to compare FC between late-life depression (LLD) patients and control subjects. Raw cross-correlation matrices (CM) for LLD were characterized by higher FC. We analyzed the small-world (SW) and modular organization of these networks consisting of 110 nodes each as well as the connectivity patterns of individual nodes of the basal ganglia. Topological network measures showed no significant differences between groups. The composition of top hubs was similar between LLD and control subjects, however in the LLD group posterior medial-parietal regions were more highly connected compared to controls. In LLD, a number of brain regions showed connections with more distant neighbors leading to an increase of the average Euclidean distance between connected regions compared to controls. In addition, right caudate nucleus connectivity was more diffuse in LLD. In summary, LLD was associated with overall increased FC strength and changes in the average distance between connected nodes, but did not lead to global changes in SW or modular organization.
Highlights
Late-life depression (LLD) is a common psychiatric disorder that typically occurs after 60 years of age
The values of L and C suggest a SW architecture of the functional connectivity (FC) networks. This is confirmed by high values of small-worldness σ (2.30 ± 0.07 and 2.27 ± 0.13, respectively) and consistent with the ratio of path lengths γ (2.78 ± 0.25 and 2.80 ± 0.21) and of clustering coefficients λ (1.20 ± 0.08 and 1.23 ± 0.11) between FC and benchmark random networks with the same number of nodes and edges
These findings indicate that the LLD group preserved SW and modular characteristics despite the mental changes caused by depression
Summary
Late-life depression (LLD) is a common psychiatric disorder that typically occurs after 60 years of age. In this study, resting-state (RS) functional magnetic resonance imaging (rs-fMRI) is used to observe functional connectivity (FC) indicating correlated activity patterns in different parts of the brain (Fox and Raichle, 2007; Auer, 2008). In rs-fMRI, spontaneous low-frequency fluctuations (SLFs, 0.01–0.1 Hz) occur in the blood oxygenation level dependent (BOLD) signal in globally distributed brain areas, which form functionally related networks, termed RS networks (RSNs; Fox and Raichle, 2007; Auer, 2008; van den Heuvel and Hulshoff Pol, 2010). Default Mode Network (DMN) SLFs are negatively correlated with tasks requiring focused attention (Raichle et al, 2001; Greicius et al, 2003; Buckner et al, 2008). Primary sensory or motor regions are absent from the DMN (Buckner et al, 2008)
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