Functional Connectivity-Based Modelling Simulates Subject-Specific Network Spreading Effects of Focal Brain Stimulation.
10.1007/s12264-018-0256-0
- Author:
Xiaoyu CHEN
1
;
Chencheng ZHANG
2
;
Yuxin LI
1
;
Pei HUANG
3
;
Qian LV
1
;
Wenwen YU
1
;
Shengdi CHEN
3
;
Bomin SUN
4
;
Zheng WANG
5
Author Information
1. Institute of Neuroscience, State Key Laboratory of Neuroscience, Chinese Academy of Sciences Center for Excellence in Brain Science and Intelligence Technology, Shanghai Institute for Biological Sciences, Chinese Academy of Sciences, Shanghai, 200031, China.
2. Department of Functional Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
3. Department of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
4. University of Chinese Academy of Sciences, Beijing, 100049, China. sbm11224@rjh.com.cn.
5. Institute of Neuroscience, State Key Laboratory of Neuroscience, Chinese Academy of Sciences Center for Excellence in Brain Science and Intelligence Technology, Shanghai Institute for Biological Sciences, Chinese Academy of Sciences, Shanghai, 200031, China. zheng.wang@ion.ac.cn.
- Publication Type:Journal Article
- Keywords:
Brain stimulation;
Functional connectivity;
Individual variability;
Parkinson’s disease;
Whole-brain modeling
- MeSH:
Adult;
Aged;
Brain Mapping;
Connectome;
Deep Brain Stimulation;
methods;
Female;
Humans;
Image Processing, Computer-Assisted;
Magnetic Resonance Imaging;
Male;
Middle Aged;
Neural Pathways;
diagnostic imaging;
physiology;
Oxygen;
blood;
Parkinson Disease;
diagnostic imaging;
pathology;
therapy;
ROC Curve;
United Kingdom
- From:
Neuroscience Bulletin
2018;34(6):921-938
- CountryChina
- Language:English
-
Abstract:
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.
