Although alterations in resting-state functional connectivity between brain regions have previously been reported in Parkinson's disease, the spatial organization of these changes remains largely unknown. Here, we longitudinally studied brain network topology in Parkinson's disease in relation to clinical measures of disease progression, using magnetoencephalography and concepts from graph theory. We characterized whole-brain functional networks by means of a standard graph analysis approach, measuring clustering coefficient and shortest path length, as well as the construction of a minimum spanning tree, a novel approach that allows a unique and unbiased characterization of brain networks. We observed that brain networks in early stage untreated patients displayed lower local clustering with preserved path length in the delta frequency band in comparison to controls. Longitudinal analysis over a 4-year period in a larger group of patients showed a progressive decrease in local clustering in multiple frequency bands together with a decrease in path length in the alpha2 frequency band. In addition, minimum spanning tree analysis revealed a decentralized and less integrated network configuration in early stage, untreated Parkinson's disease that also progressed over time. Moreover, the longitudinal changes in network topology identified with both techniques were associated with deteriorating motor function and cognitive performance. Our results indicate that impaired local efficiency and network decentralization are very early features of Parkinson's disease that continue to progress over time, together with reductions in global efficiency. As these network changes appear to reflect clinically relevant phenomena, they hold promise as markers of disease progression.

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In this fMRI study in PD, we demonstrated a progressive loss of resting-state functional connectivity over a period of 3 years for multiple brain regions, especially in posterior parts of the brain. The strong correlation with decreasing cognitive performance supports the pathophysiologic role of reduced functional connectivity in cognitive decline and the development of dementia in PD.

The assessment of resting-state functional connectivity has become an important tool in studying brain disease mechanisms. Here we use magnetoencephalography to longitudinally evaluate functional connectivity changes in relation to clinical measures of disease progression in Parkinson's disease (PD).Using a source-space based approach with detailed anatomical mapping, functional connectivity was assessed for temporal, prefrontal and high order sensory association areas known to show neuropathological changes in early clinical disease stages.At baseline, early stage, untreated PD patients (n = 12) had lower parahippocampal and temporal delta band connectivity and higher temporal alpha1 band connectivity compared to controls. Longitudinal analyses over a 4-year period in a larger patient group (n = 43) revealed decreases in alpha1 and alpha2 band connectivity for multiple seed regions that were associated with motor or cognitive deterioration.In the earliest clinical stages of PD, delta and alpha1 band resting-state functional connectivity is altered in temporal cortical regions. With disease progression, a reversal of the initial changes in alpha1 and additional decreases in alpha2 band connectivity evolving in a more widespread cortical pattern. These changes in functional connectivity appear to reflect clinically relevant phenomena and therefore hold promise as a marker of disease progression, with potential predictive value for clinical outcome.

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