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Dopamine Depletion Alters Macroscopic Network Dynamics in Parkinsons Disease

By James M. Shine, Peter T Bell, Elie Matar, Russell A. Poldrack, Simon JG Lewis, Glenda Halliday, Claire O’Callaghan

Posted 02 Aug 2018
bioRxiv DOI: 10.1101/382994 (published DOI: 10.1093/brain/awz034)

Parkinsons disease is primarily characterised by diminished dopaminergic function, however the impact of these impairments on large-scale brain dynamics remains unclear. It has been difficult to disentangle the direct effects of Parkinsons disease from compensatory changes that reconfigure the functional signature of the whole brain network. To examine the causal role of dopamine depletion in network-level topology, we investigated time-varying network structure in 37 individuals with idiopathic Parkinsons disease, both On and Off dopamine replacement therapy, along with 50 age-matched, healthy control subjects using resting-state functional MRI. By tracking dynamic network-level topology, we found that the Parkinsons disease Off state was associated with greater network-level integration than in the On state. The extent of integration in the Off state inversely correlated with motor symptom severity, suggesting that a shift toward a more integrated network topology may be a compensatory mechanism associated with preserved motor function in the dopamine depleted Off state. Furthermore, we were able to demonstrate that measures of both cognitive and brain reserve (i.e. premorbid intelligence and whole brain grey matter volume) had a positive relationship with the relative increase in network integration observed in the dopaminergic Off state. This suggests that each of these factors plays an important role in promoting network integration in the dopaminergic Off state. Our findings provide a mechanistic basis for understanding the PD Off state and provide a further conceptual link with network-level reconfiguration. Together, our results highlight the mechanisms responsible for pathological and compensatory change in Parkinsons disease.

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