Abstract
ObjectiveIt is important to identify brain-based biomarkers that progressively deteriorate from healthy to mild cognitive impairment (MCI) to Alzheimer’s disease (AD). Cortical thickness, amyloid-ß deposition, and graph measures derived from functional connectivity (FC) networks obtained using functional MRI (fMRI) have been previously identified as potential biomarkers. Specifically, in the latter case, betweenness centrality (BC), a nodal graph measure quantifying information flow, is reduced in both AD and MCI. However, all such reports have utilized BC calculated from undirected networks that characterize synchronization rather than information flow, which is better characterized using directed networks.MethodsTherefore, we estimated BC from directed networks using Granger causality (GC) on resting-state fMRI data (N = 132) to compare the following populations (p < 0.05, FDR corrected for multiple comparisons): normal control (NC), early MCI (EMCI), late MCI (LMCI) and AD. We used an additional metric called middleman power (MP), which not only characterizes nodal information flow as in BC, but also measures nodal power critical for information flow in the entire network.ResultsMP detected more brain regions than BC that progressively deteriorated from NC to EMCI to LMCI to AD, as well as exhibited significant associations with behavioral measures. Additionally, graph measures obtained from conventional FC networks could not identify a single node, underscoring the relevance of GC.ConclusionOur findings demonstrate the superiority of MP over BC as well as GC over FC in our case. MP obtained from GC networks could serve as a potential biomarker for progressive deterioration of MCI and AD.
Highlights
Alzheimer’s disease (AD) is a neurodegenerative disorder [1–3] that is initially characterized by memory loss, and cognitive decline and incapacitation as the disease progresses
middleman power (MP) detected more brain regions than betweenness centrality (BC) that progressively deteriorated from normal control (NC) to early Mild cognitive impairment (MCI) (EMCI) to late MCI (LMCI) to AD, as well as exhibited significant associations with behavioral measures
Our findings demonstrate the superiority of MP over BC as well as Granger causality (GC) over functional connectivity (FC) in our case
Summary
Alzheimer’s disease (AD) is a neurodegenerative disorder [1–3] that is initially characterized by memory loss, and cognitive decline and incapacitation as the disease progresses. Resting-state functional magnetic resonance imaging (RS-fMRI) is a promising modality that can noninvasively characterize distributed brain networks [8, 9]. RS-fMRI has been widely used to study the inter-regional functional connectivity (FC) between healthy and disease. Studies have found that AD is associated with alteration of FC among different brain regions [11, 12]. Connectivity alterations in AD patients’ brain have been shown to occur in medial frontal, medial parietal and posterior cingulate cortex; those regions exhibit high resting-state metabolism and are part of the “defaultmode network” [15]. Reduced resting-state FC [17] has been found in the default-mode network of MCI patients. A small number of previous studies have found increased FC in MCI/AD, which were attributed as compensatory mechanisms for losses in cognitive functionality [18, 19]. The deterioration hypothesis (reduced connectivity) is a more mainstream view with wider acceptability since it has roots in molecular/cellular level events in AD [20]; we adopted it in this study
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