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Parkinson's disease is a common and debilitating condition, caused by aberrant activity in a complex basal ganglia-thalamocortical circuit. Therapeutic advances rely on characterising interactions in this circuit. However, recording electrophysiological responses over the entire circuit is impractical. Dynamic causal modelling offers large-scale models of predictive value based on a limited or partial sampling of complex networks. Using dynamic causal modelling, we determined the network changes underlying the pathological excess of beta oscillations that characterise the Parkinsonian state. We modelled data from five patients undergoing surgery for deep brain stimulation of more than one target. We found that connections to and from the subthalamic nucleus were strengthened and promoted beta synchrony, in the untreated compared to the treated Parkinsonian state. Dynamic causal modelling was able to replicate the effects of lesioning this nucleus and may provide a new means of directing the search for therapeutic targets.

Original publication

DOI

10.1016/j.neuroimage.2012.10.088

Type

Journal article

Journal

Neuroimage

Publication Date

01/02/2013

Volume

66

Pages

301 - 310

Keywords

Basal ganglia, Deep brain stimulation, Effective connectivity, Electroencephalography, Parkinson's disease, Adult, Basal Ganglia, Cerebral Cortex, Deep Brain Stimulation, Electrodes, Implanted, Electroencephalography, Electrophysiology, Female, Humans, Male, Middle Aged, Models, Neurological, Nerve Net, Parkinson Disease, Subthalamic Nucleus