Abstract
Deep brain stimulation (DBS) for Parkinson’s disease is a highly effective treatment in controlling otherwise debilitating symptoms. Yet the underlying brain mechanisms are currently not well understood. Whole-brain computational modeling was used to disclose the effects of DBS during resting-state functional Magnetic Resonance Imaging in ten patients with Parkinson’s disease. Specifically, we explored the local and global impact that DBS has in creating asynchronous, stable or critical oscillatory conditions using a supercritical bifurcation model. We found that DBS shifts global brain dynamics of patients towards a Healthy regime. This effect was more pronounced in very specific brain areas such as the thalamus, globus pallidus and orbitofrontal regions of the right hemisphere (with the left hemisphere not analyzed given artifacts arising from the electrode lead). Global aspects of integration and synchronization were also rebalanced. Empirically, we found higher communicability and coherence brain measures during DBS-ON compared to DBS-OFF. Finally, using our model as a framework, artificial in silico DBS was applied to find potential alternative target areas for stimulation and whole-brain rebalancing. These results offer important insights into the underlying large-scale effects of DBS as well as in finding novel stimulation targets, which may offer a route to more efficacious treatments.
Highlights
A first study demonstrated a reversal in cortico-thalamic coupling during voluntary movements in Parkinson’s disease patients with subthalamic nucleus (STN) DBS25, while a follow-up study used dynamic causal modeling (DCM) of the STN network to further characterize the effective connectivity of resting state motor networks[26]
Most of the Deep brain stimulation (DBS)-ON measures were still lower than the Healthy controls, we found that the standard deviation of phase consistency was restored to a value significantly similar to that of the age-matched healthy controls (H-AM)
The research presented here has led to novel insights into the mechanisms of DBS, using computational connectomics to model the large-scale changes elicited by therapeutic DBS in Parkinson’s disease
Summary
FMRI and electroencephalography (EEG) were used to track the changes following DBS of the nucleus accumbens (NAc) in patients with obsessive-compulsive disorder which was found to reduce excessive connectivity between the NAc and prefrontal cortex, with decreased frontal low-frequency oscillations during symptom provocation[27] Taken together these studies lend strong support to the idea that therapeutic DBS works by re-balancing the brain activity of the functional and structural networks in the diseased brain[11]. We used the tools from computational connectomics to investigate the fMRI responses in the right hemisphere of ten Parkinson’s disease patients with DBS ON and OFF compared with 49 Healthy age-matched (as well as 16 non age-matched) participants This allowed us to explore the local and global impact that DBS has on resting state brain dynamics[30]. In the light of earlier findings addressing large-scale changes caused by Parkinson’s disease[18, 31, 32] and previous research on DBS mechanisms[33], we predicted that therapeutic DBS for Parkinson’s disease would create both global and local changes in the large-scale dynamics
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