Abstract
Background: Functional imaging methods, such as resting-state functional magnetic resonance imaging, reflect changes in neural connectivity and may help to assess the widespread consequences of disease-specific network changes in Parkinson's disease. In this study we used a relatively new graph analysis approach in functional imaging: eigenvector centrality mapping. This model-free method, applied to all voxels in the brain, identifies prominent regions in the brain network hierarchy and detects localized differences between patient populations. In other neurological disorders, eigenvector centrality mapping has been linked to changes in functional connectivity in certain nodes of brain networks.Objectives: Examining changes in functional brain connectivity architecture on a whole brain and network level in patients with Parkinson's disease.Methods: Whole brain resting-state functional architecture was studied with a recently introduced graph analysis approach (eigenvector centrality mapping). Functional connectivity was further investigated in relation to eight known resting-state networks. Cross-sectional analyses included group comparison of functional connectivity measures of Parkinson's disease patients (n = 107) with control subjects (n = 58) and correlations with clinical data, including motor and cognitive impairment and a composite measure of predominantly non-dopaminergic symptoms.Results: Eigenvector centrality mapping revealed that frontoparietal regions were more prominent in the whole-brain network function in patients compared to control subjects, while frontal and occipital brain areas were less prominent in patients. Using standard resting-state networks, we found predominantly increased functional connectivity, namely within sensorimotor system and visual networks in patients. Regional group differences in functional connectivity of both techniques between patients and control subjects partly overlapped for highly connected posterior brain regions, in particular in the posterior cingulate cortex and precuneus. Clinico-functional imaging relations were not found.Conclusions: Changes on the level of functional brain connectivity architecture might provide a different perspective of pathological consequences of Parkinson's disease. The involvement of specific, highly connected (hub) brain regions may influence whole brain functional network architecture in Parkinson's disease.
Highlights
Parkinson’s disease (PD) is characterized by a broad spectrum of motor and non-motor symptoms, which are linked to a progressive formation of α-synuclein (α-SynA) aggregates in presynaptic terminals, Lewy neurites and Lewy bodies in neurons of the central and peripheral nervous system [1, 2]. α-synuclein aggregates (α-SynA) are not randomly distributed in the brain, but appear in select regions, which likely are affected because of shared anatomical and functional properties among neurons [3, 4]
Using the novel graph analysis approach (ECM), we found that frontoparietal regions display a stronger connectivity to the whole-brain network function in PD patients compared to control subjects, while a decreased connectivity was found for frontal and occipital areas of the brain (Figures 1, 3)
The frontoparietal regions identified with eigenvector centrality mapping (ECM) partly overlapped with increased regional functional connectivity identified by standard resting-state network analysis within the sensorimotor system network, including the sensorimotor, primary motor and premotor cortex, and SMA (Figures 1– 3)
Summary
Parkinson’s disease (PD) is characterized by a broad spectrum of motor and non-motor symptoms, which are linked to a progressive formation of α-synuclein (α-SynA) aggregates in presynaptic terminals, Lewy neurites and Lewy bodies in neurons of the central and peripheral nervous system [1, 2]. α-SynA are not randomly distributed in the brain, but appear in select regions, which likely are affected because of shared anatomical and functional properties among neurons [3, 4]. Compelling evidence shows that α-SynA-related synaptic dysfunction antedates nerve cell loss, suggesting that altered neuronal connectivity is a key feature in PD [5] Functional imaging methods, such as resting-state functional magnetic resonance imaging (fMRI), reflect changes in neural connectivity and may help to assess the widespread consequences of disease-specific network changes in neurodegenerative diseases [6]. Most of these studies focused on functional connectivity of (multiple) brain regions or networks of interest, precluding inferences on a whole-brain level of integrated networks that are spatially distributed, but functionally linked Functional imaging methods, such as resting-state functional magnetic resonance imaging, reflect changes in neural connectivity and may help to assess the widespread consequences of disease-specific network changes in Parkinson’s disease. Eigenvector centrality mapping has been linked to changes in functional connectivity in certain nodes of brain networks
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
