A whole-brain computational modeling approach to explain the alterations in resting-state functional connectivity during progression of Alzheimer's disease

Highlights

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Whole-brain resting state functional connectivity (FC) is investigated in subjects with preclinical Alzheimer’s disease (PAD), mild cognitive impairment due to AD (MCI) and mild dementia due to Alzheimer’s disease (AD).

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Mean and standard deviation of the whole-brain synchronization reduce during the progression of AD. Regional FC shows widespread decreases in AD group, whereas whole-brain computational modeling approach reveals the left temporal lobe as the core of these alterations.

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Systematically manipulating the dynamical regime of the model in healthy control subjects generates simulated FC patterns that match to the empirically observed FC in clinical groups (PAD, MCI, AD).

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Amyloid-beta CSF biomarker primarily reflects the connectivity alterations in clinical groups with respect to the healthy control group.

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Total tau and phosphorylated tau CSF biomarkers show distinct regional associations that are present also across clinical groups.

Abstract

Alzheimer's disease (AD) is the most common dementia with dramatic consequences. The research in structural and functional neuroimaging showed altered brain connectivity in AD. In this study, we investigated the whole-brain resting state functional connectivity (FC) of the subjects with preclinical Alzheimer's disease (PAD), mild cognitive impairment due to AD (MCI) and mild dementia due to Alzheimer's disease (AD), the impact of APOE4 carriership, as well as in relation to variations in core AD CSF biomarkers. The synchronization in the whole-brain was monotonously decreasing during the course of the disease progression. Furthermore, in AD patients we found widespread significant decreases in functional connectivity (FC) strengths particularly in the brain regions with high global connectivity. We employed a whole-brain computational modeling approach to study the mechanisms underlying these alterations. To characterize the causal interactions between brain regions, we estimated the effective connectivity (EC) in the model. We found that the significant EC differences in AD were primarily located in left temporal lobe. Then, we systematically manipulated the underlying dynamics of the model to investigate simulated changes in FC based on the healthy control subjects. Furthermore, we found distinct patterns involving CSF biomarkers of amyloid-beta (Aβ1 − 42) total tau (t-tau) and phosphorylated tau (p-tau). CSF Aβ1 − 42 was associated to the contrast between healthy control subjects and clinical groups. Nevertheless, tau CSF biomarkers were associated to the variability in whole-brain synchronization and sensory integration regions. These associations were robust across clinical groups, unlike the associations that were found for CSF Aβ1 − 42. APOE4 carriership showed no significant correlations with the connectivity measures.