Dynamic Network Connectivity Reveals Markers of Response to Deep Brain Stimulation in Parkinson’s Disease

Abstract

Background: Neuronal loss in Parkinson’s Disease (PD) leads to widespread neural network dysfunction. While graph theory allows for analysis of whole brain networks, patterns of functional connectivity (FC) associated with motor response to deep brain stimulation of the subthalamic nucleus (STN-DBS) have yet to be explored.Objective/Hypothesis: To investigate the distributed network properties associated with STN-DBS in patients with advanced PD.Methods: Eighteen patients underwent 3-Tesla resting state functional MRI (rs-fMRI) prior to STN-DBS. Improvement in UPDRS-III scores following STN-DBS were assessed 1 year after implantation. Independent component analysis (ICA) was applied to extract spatially independent components (ICs) from the rs-fMRI. FC between ICs was calculated across the entire time series and for dynamic brain states. Graph theory analysis was performed to investigate whole brain network topography in static and dynamic states.Results: Dynamic analysis identified two unique brain states: a relative hypoconnected state and a relative hyperconnected state. Time spent in a state, dwell time, and number of transitions were not correlated with DBS response. There were no significant FC findings, but graph theory analysis demonstrated significant relationships with STN-DBS response only during the hypoconnected state – STN-DBS was negatively correlated with network assortativity.Conclusion: Given the widespread effects of dopamine depletion in PD, analysis of whole brain networks is critical to our understanding of the pathophysiology of this disease. Only by leveraging graph theoretical analysis of dynamic FC were we able to isolate a hypoconnected brain state that contained distinct network properties associated with the clinical effects of STN-DBS.

Deep Brain Stimulation Modulates Multiple Abnormal Resting-State Network Connectivity in Patients With Parkinson’s Disease

“…This indicated the limitations of DBS for network modulation. Wu et al noted that STN-DBS did not improve global network measures but was negatively associated with network assortativity ( Wu et al, 2021 ), which consisted with our findings.…”

Deep brain stimulation for Parkinson's disease

“…Investigations of the new brain targets mentioned above, and maybe of other brain areas, will continue aiming to further improving outcome [110]. This will be facilitated by improved imaging of the brain, including functional MRI [118] and connectivity imaging [119,120]. Additionally, from DBS having been initially the exclusivity of one company, there are now at least three major DBS companies, resulting in several technical DBS innovations that are already being implemented or investigated [121][122][123], such as MRI-compatible DBS hardware; neuropacemakers with rechargeable batteries and extended life up to 25 years; neuropacemakers with sensing technology allowing to record the depth electroencephalogram, especially beta activity, and adapt the stimulation accordingly, so called closed loop stimulation, with the potential to decrease side effects and battery drain; directional DBS electrodes allowing the electric current to be focused precisely on the region of interest, again to decrease side effects such as dysarthria and improve outcome; remote web-based follow-up programming and troubleshooting of the stimulation to help patients who live far away from the DBS centre; and new modes of stimulation based on judicious use of more flexible electric parameters (such as pulse width, pulse shape, frequency, amplitude, etc.…”

Effects of Combined Intervention of rTMS and Neurotransmitter Drugs on the Brain Functional Networks in Patients with Cognitive Impairment

“…The visual network (VN) consists of the bilateral occipital lobe (OL). The auditory network (AN) primarily includes the bilateral superior temporal gyrus (STG) [ 2 , 27 , 33 , 34 , 35 , 36 , 37 , 38 ] (as shown in Figure 2 ).…”