Journal
NEUROSCIENCE BULLETIN
Volume 34, Issue 6, Pages 921-938Publisher
SPRINGER
DOI: 10.1007/s12264-018-0256-0
Keywords
Brain stimulation; Functional connectivity; Whole-brain modeling; Parkinson's disease; Individual variability
Categories
Funding
- Chinese Academy of Sciences [XDB02050006]
- National Natural Science Foundation of China [81571300, 81527901, 31771174, 81271518, 81471387]
- National Key R&D Program of China [2017YFC1310400]
- Natural Science Foundation
- Major Basic Research Program of Shanghai [16JC1420100]
- Shanghai JiaoTong University School of Medicine-Institute of Neuroscience Research Center for Brain Disorders
- Shanghai JiaoTong University K.C. Wong Medical Fellowship Fund
- Michael J. Fox Foundation
- Abbott
- Avid Radiopharmaceuticals
- Biogen Idec
- Bristol-Myers Squibb
- Covance
- Ian
- GE Healthcare
- Genentech
- GlaxoSmithKline
- Lundbeck
- Lilly
- Merck
- Meso Scale Discovery
- Pfizer
- Piramal
- Roche
- Servier
- UCB
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Neurostimulation remarkably alleviates the symptoms in a variety of brain disorders by modulating the brain-wide network. However, how brain-wide effects on the direct and indirect pathways evoked by focal neurostimulation elicit therapeutic effects in an individual patient is unknown. Understanding this remains crucial for advancing neural circuit-based guidance to optimize candidate patient screening, pre-surgical target selection, and post-surgical parameter tuning. To address this issue, we propose a functional brain connectome-based modeling approach that simulates the spreading effects of stimulating different brain regions and quantifies the rectification of abnormal network topology in silico. We validated these analyses by pinpointing nuclei in the basal ganglia circuits as top-ranked targets for 43 local patients with Parkinson's disease and 90 patients from a public database. Individual connectome-based analysis demonstrated that the globus pallidus was the best choice for 21.1% and the subthalamic nucleus for 19.5% of patients. Down-regulation of functional connectivity (up to 12%) at these prioritized targets optimally maximized the therapeutic effects. Notably, the priority rank of the subthalamic nucleus significantly correlated with motor symptom severity (Unified Parkinson's Disease Rating Scale III) in the local cohort. These findings underscore the potential of neural network modeling for advancing personalized brain stimulation therapy, and warrant future experimental investigation to validate its clinical utility.
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