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Zhang Z, Huang Y, Chen X, Li J, Yang Y, Lv L, Wang J, Wang M, Wang Y, Wang Z. State-specific Regulation of Electrical Stimulation in the Intralaminar Thalamus of Macaque Monkeys: Network and Transcriptional Insights into Arousal. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024:e2402718. [PMID: 38938001 DOI: 10.1002/advs.202402718] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/15/2024] [Revised: 06/03/2024] [Indexed: 06/29/2024]
Abstract
Long-range thalamocortical communication is central to anesthesia-induced loss of consciousness and its reversal. However, isolating the specific neural networks connecting thalamic nuclei with various cortical regions for state-specific anesthesia regulation is challenging, with the biological underpinnings still largely unknown. Here, simultaneous electroencephalogram-fuctional magnetic resonance imaging (EEG-fMRI) and deep brain stimulation are applied to the intralaminar thalamus in macaques under finely-tuned propofol anesthesia. This approach led to the identification of an intralaminar-driven network responsible for rapid arousal during slow-wave oscillations. A network-based RNA-sequencing analysis is conducted of region-, layer-, and cell-specific gene expression data from independent transcriptomic atlases and identifies 2489 genes preferentially expressed within this arousal network, notably enriched in potassium channels and excitatory, parvalbumin-expressing neurons, and oligodendrocytes. Comparison with human RNA-sequencing data highlights conserved molecular and cellular architectures that enable the matching of homologous genes, protein interactions, and cell types across primates, providing novel insight into network-focused transcriptional signatures of arousal.
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Affiliation(s)
- Zhao Zhang
- Department of Anesthesiology, Huashan Hospital, Fudan University, 12 Urumqi Middle Rd, Jing'an District, Shanghai, 200040, China
| | - Yichun Huang
- School of Psychological and Cognitive Sciences, Beijing Key Laboratory of Behavior and Mental Health, State Key Laboratory of General Artificial Intelligence, IDG/McGovern Institute for Brain Research, Peking-Tsinghua Center for Life Sciences, Peking University, 5 Yiheyuan Rd, Haidian District, Beijing, 100871, China
| | - Xiaoyu Chen
- Institute of Natural Sciences and School of Mathematical Sciences, Shanghai Jiao Tong University, 800 Dongchuan RD, Minhang District, Shanghai, 200240, China
| | - Jiahui Li
- School of Psychological and Cognitive Sciences, Beijing Key Laboratory of Behavior and Mental Health, State Key Laboratory of General Artificial Intelligence, IDG/McGovern Institute for Brain Research, Peking-Tsinghua Center for Life Sciences, Peking University, 5 Yiheyuan Rd, Haidian District, Beijing, 100871, China
| | - Yi Yang
- Department of Neurosurgery, Brain Computer Interface Transition Research Center, Beijing Tiantan Hospital, Capital Medical University, 119 South Fourth Ring Rd West, Fengtai District, Beijing, 100070, China
| | - Longbao Lv
- National Resource Center for Non-Human Primates, Kunming Primate Research Center, National Research Facility for Phenotypic & Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, 32 East of Jiaochang Rd, Kunming, Yunnan, 650223, China
| | - Jianhong Wang
- National Resource Center for Non-Human Primates, Kunming Primate Research Center, National Research Facility for Phenotypic & Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, 32 East of Jiaochang Rd, Kunming, Yunnan, 650223, China
| | - Meiyun Wang
- Department of Medical Imaging, Henan Provincial People's Hospital & the People's Hospital of Zhengzhou University, No. 7 Weiwu Road, Zhengzhou, Henan, 450003, China
| | - Yingwei Wang
- Department of Anesthesiology, Huashan Hospital, Fudan University, 12 Urumqi Middle Rd, Jing'an District, Shanghai, 200040, China
| | - Zheng Wang
- School of Psychological and Cognitive Sciences, Beijing Key Laboratory of Behavior and Mental Health, State Key Laboratory of General Artificial Intelligence, IDG/McGovern Institute for Brain Research, Peking-Tsinghua Center for Life Sciences, Peking University, 5 Yiheyuan Rd, Haidian District, Beijing, 100871, China
- School of Biomedical Engineering, Hainan University, 58 Renmin Avenue, Haikou, Hainan, 570228, China
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Fang H, Berman SA, Wang Y, Yang Y. Robust adaptive deep brain stimulation control of in-silico non-stationary Parkinsonian neural oscillatory dynamics. J Neural Eng 2024; 21:036043. [PMID: 38834058 DOI: 10.1088/1741-2552/ad5406] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Accepted: 06/04/2024] [Indexed: 06/06/2024]
Abstract
Objective. Closed-loop deep brain stimulation (DBS) is a promising therapy for Parkinson's disease (PD) that works by adjusting DBS patterns in real time from the guidance of feedback neural activity. Current closed-loop DBS mainly uses threshold-crossing on-off controllers or linear time-invariant (LTI) controllers to regulate the basal ganglia (BG) Parkinsonian beta band oscillation power. However, the critical cortex-BG-thalamus network dynamics underlying PD are nonlinear, non-stationary, and noisy, hindering accurate and robust control of Parkinsonian neural oscillatory dynamics.Approach. Here, we develop a new robust adaptive closed-loop DBS method for regulating the Parkinsonian beta oscillatory dynamics of the cortex-BG-thalamus network. We first build an adaptive state-space model to quantify the dynamic, nonlinear, and non-stationary neural activity. We then construct an adaptive estimator to track the nonlinearity and non-stationarity in real time. We next design a robust controller to automatically determine the DBS frequency based on the estimated Parkinsonian neural state while reducing the system's sensitivity to high-frequency noise. We adopt and tune a biophysical cortex-BG-thalamus network model as an in-silico simulation testbed to generate nonlinear and non-stationary Parkinsonian neural dynamics for evaluating DBS methods.Main results. We find that under different nonlinear and non-stationary neural dynamics, our robust adaptive DBS method achieved accurate regulation of the BG Parkinsonian beta band oscillation power with small control error, bias, and deviation. Moreover, the accurate regulation generalizes across different therapeutic targets and consistently outperforms current on-off and LTI DBS methods.Significance. These results have implications for future designs of closed-loop DBS systems to treat PD.
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Affiliation(s)
- Hao Fang
- MOE Frontier Science Center for Brain Science and Brain-machine Integration, Zhejiang University, Hangzhou 310058, People's Republic of China
- Nanhu Brain-computer Interface Institute, Hangzhou 311100, People's Republic of China
| | - Stephen A Berman
- College of Medicine, University of Central Florida, Orlando, FL 32816, United States of America
| | - Yueming Wang
- Nanhu Brain-computer Interface Institute, Hangzhou 311100, People's Republic of China
- Qiushi Academy for Advanced Studies, Hangzhou 310058, People's Republic of China
- College of Computer Science and Technology, Zhejiang University, Hangzhou 310058, People's Republic of China
- State Key Laboratory of Brain-machine Intelligence, Hangzhou 310058, People's Republic of China
| | - Yuxiao Yang
- MOE Frontier Science Center for Brain Science and Brain-machine Integration, Zhejiang University, Hangzhou 310058, People's Republic of China
- Nanhu Brain-computer Interface Institute, Hangzhou 311100, People's Republic of China
- College of Computer Science and Technology, Zhejiang University, Hangzhou 310058, People's Republic of China
- State Key Laboratory of Brain-machine Intelligence, Hangzhou 310058, People's Republic of China
- Department of Neurosurgery, Second Affiliated Hospital, School of Medicine, Hangzhou 310058, People's Republic of China
- NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou 310058, People's Republic of China
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Liu B, Mao Z, Yan X, Yang H, Xu J, Feng Z, Zhang Y, Yu X. Structural network topologies are associated with deep brain stimulation outcomes in Meige syndrome. Neurotherapeutics 2024:e00367. [PMID: 38679556 DOI: 10.1016/j.neurot.2024.e00367] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2023] [Revised: 04/18/2024] [Accepted: 04/19/2024] [Indexed: 05/01/2024] Open
Abstract
Deep brain stimulation (DBS) is an effective therapy for Meige syndrome (MS). However, the DBS efficacy varies across MS patients and the factors contributing to the variable responses remain enigmatic. We aim to explain the difference in DBS efficacy from a network perspective. We collected preoperative T1-weighted MRI images of 76 MS patients who received DBS in our center. According to the symptomatic improvement rates, all MS patients were divided into two groups: the high improvement group (HIG) and the low improvement group (LIG). We constructed group-level structural covariance networks in each group and compared the graph-based topological properties and interregional connections between groups. Subsequent functional annotation and correlation analyses were also conducted. The results indicated that HIG showed a higher clustering coefficient, longer characteristic path length, lower small-world index, and lower global efficiency compared with LIG. Different nodal betweennesses and degrees between groups were mainly identified in the precuneus, sensorimotor cortex, and subcortical nuclei, among which the gray matter volume of the left precentral gyrus and left thalamus were positively correlated with the symptomatic improvement rates. Moreover, HIG had enhanced interregional connections within the somatomotor network and between the somatomotor network and default-mode network relative to LIG. We concluded that the high and low DBS responders have notable differences in large-scale network architectures. Our study sheds light on the structural network underpinnings of varying DBS responses in MS patients.
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Affiliation(s)
- Bin Liu
- Medical School of Chinese PLA, Beijing, 100853, China; Department of Neurosurgery, The First Medical Center of Chinese PLA General Hospital, Beijing, 100853, China
| | - Zhiqi Mao
- Department of Neurosurgery, The First Medical Center of Chinese PLA General Hospital, Beijing, 100853, China
| | - Xinyuan Yan
- Department of Psychiatry, University of Minnesota Medical School, Minneapolis, MN, USA
| | - Hang Yang
- Chinese Institute for Brain Research, Beijing, 102206, China
| | - Junpeng Xu
- Medical School of Chinese PLA, Beijing, 100853, China; Department of Neurosurgery, The First Medical Center of Chinese PLA General Hospital, Beijing, 100853, China
| | - Zhebin Feng
- Medical School of Chinese PLA, Beijing, 100853, China; Department of Neurosurgery, The First Medical Center of Chinese PLA General Hospital, Beijing, 100853, China
| | - Yanyang Zhang
- Department of Neurosurgery, The First Medical Center of Chinese PLA General Hospital, Beijing, 100853, China.
| | - Xinguang Yu
- Department of Neurosurgery, The First Medical Center of Chinese PLA General Hospital, Beijing, 100853, China.
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Beylergil SB, Noecker AM, Kilbane C, McIntyre CC, Shaikh AG. Does Vestibular Motion Perception Correlate with Axonal Pathways Stimulated by Subthalamic Deep Brain Stimulation in Parkinson's Disease? CEREBELLUM (LONDON, ENGLAND) 2024; 23:554-569. [PMID: 37308757 DOI: 10.1007/s12311-023-01576-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 06/01/2023] [Indexed: 06/14/2023]
Abstract
Perception of our linear motion - heading - is critical for postural control, gait, and locomotion, and it is impaired in Parkinson's disease (PD). Deep brain stimulation (DBS) has variable effects on vestibular heading perception, depending on the location of the electrodes within the subthalamic nucleus (STN). Here, we aimed to find the anatomical correlates of heading perception in PD. Fourteen PD participants with bilateral STN DBS performed a two-alternative forced-choice discrimination task where a motion platform delivered translational forward movements with a heading angle varying between 0 and 30° to the left or to the right with respect to the straight-ahead direction. Using psychometric curves, we derived the heading discrimination threshold angle of each patient from the response data. We created patient-specific DBS models and calculated the percentages of stimulated axonal pathways that are anatomically adjacent to the STN and known to play a major role in vestibular information processing. We performed correlation analyses to investigate the extent of these white matter tracts' involvement in heading perception. Significant positive correlations were identified between improved heading discrimination for rightward heading and the percentage of activated streamlines of the contralateral hyperdirect, pallido-subthalamic, and subthalamo-pallidal pathways. The hyperdirect pathways are thought to provide top-down control over STN connections to the cerebellum. In addition, STN may also antidromically activate collaterals of hyperdirect pathway that projects to the precerebellar pontine nuclei. In select cases, there was strong activation of the cerebello-thalamic projections, but it was not consistently present in all participants. Large volumetric overlap between the volume of tissue activation and the STN in the left hemisphere positively impacted rightward heading perception. Altogether, the results suggest heavy involvement of basal ganglia cerebellar network in STN-induced modulation of vestibular heading perception in PD.
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Affiliation(s)
- Sinem Balta Beylergil
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA
- National VA Parkinson Consortium Center, Neurology Service, Daroff-Dell'Osso Ocular Motility and Vestibular Laboratory, Louis Stokes Cleveland VA Medical Center, Cleveland, OH, USA
| | - Angela M Noecker
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA
| | - Camilla Kilbane
- Department of Neurology, Case Western Reserve University, 11100 Euclid Avenue, Cleveland, OH, 44110, USA
- Movement Disorders Center, Neurological Institute, University Hospitals, Cleveland, OH, USA
| | - Cameron C McIntyre
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA
| | - Aasef G Shaikh
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA.
- National VA Parkinson Consortium Center, Neurology Service, Daroff-Dell'Osso Ocular Motility and Vestibular Laboratory, Louis Stokes Cleveland VA Medical Center, Cleveland, OH, USA.
- Department of Neurology, Case Western Reserve University, 11100 Euclid Avenue, Cleveland, OH, 44110, USA.
- Movement Disorders Center, Neurological Institute, University Hospitals, Cleveland, OH, USA.
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Chen Y, Zhu G, Yuan T, Ma R, Zhang X, Meng F, Yang A, Du T, Zhang J. Subthalamic nucleus deep brain stimulation alleviates oxidative stress via mitophagy in Parkinson's disease. NPJ Parkinsons Dis 2024; 10:52. [PMID: 38448431 PMCID: PMC10917786 DOI: 10.1038/s41531-024-00668-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Accepted: 02/23/2024] [Indexed: 03/08/2024] Open
Abstract
Subthalamic nucleus deep brain stimulation (STN-DBS) has the potential to delay Parkinson's disease (PD) progression. Whether oxidative stress participates in the neuroprotective effects of DBS and related signaling pathways remains unknown. To address this, we applied STN-DBS to mice and monkey models of PD and collected brain tissue to evaluate mitophagy, oxidative stress, and related pathway. To confirm findings in animal experiments, a cohort of PD patients was recruited and oxidative stress was evaluated in cerebrospinal fluid. When PD mice received STN stimulation, the mTOR pathway was suppressed, accompanied by elevated LC3 II expression, increased mitophagosomes, and a decrease in p62 expression. The increase in mitophagy and balance of mitochondrial fission/fusion dynamics in the substantia nigra caused a marked enhancement of the antioxidant enzymes superoxide dismutase and glutathione levels. Subsequently, fewer mitochondrial apoptogenic factors were released to the cytoplasm, which resulted in a suppression of caspase activation and reservation of dopaminergic neurons. While interfaced with an mTOR activator, oxidative stress was no longer regulated by STN-DBS, with no neuroprotective effect. Similar results to those found in the rodent experiments were obtained in monkeys treated with chronic STN stimulation. Moreover, antioxidant enzymes in PD patients were increased after the operation, however, there was no relation between changes in antioxidant enzymes and motor impairment. Collectively, our study found that STN-DBS was able to increase mitophagy via an mTOR-dependent pathway, and oxidative stress was suppressed due to removal of damaged mitochondria, which was attributed to the dopaminergic neuroprotection of STN-DBS in PD.
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Affiliation(s)
- Yingchuan Chen
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, 100070, Beijing, China
- Beijing Key Laboratory of Neurostimulation, 100070, Beijing, China
| | - Guanyu Zhu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, 100070, Beijing, China
- Beijing Key Laboratory of Neurostimulation, 100070, Beijing, China
| | - Tianshuo Yuan
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, 100070, Beijing, China
- Beijing Key Laboratory of Neurostimulation, 100070, Beijing, China
| | - Ruoyu Ma
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, 100070, Beijing, China
- Beijing Key Laboratory of Neurostimulation, 100070, Beijing, China
| | - Xin Zhang
- Beijing Key Laboratory of Neurostimulation, 100070, Beijing, China
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, 100070, Beijing, China
| | - Fangang Meng
- Beijing Key Laboratory of Neurostimulation, 100070, Beijing, China
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, 100070, Beijing, China
| | - Anchao Yang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, 100070, Beijing, China
- Beijing Key Laboratory of Neurostimulation, 100070, Beijing, China
| | - Tingting Du
- Beijing Key Laboratory of Neurostimulation, 100070, Beijing, China.
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, 100070, Beijing, China.
| | - Jianguo Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, 100070, Beijing, China.
- Beijing Key Laboratory of Neurostimulation, 100070, Beijing, China.
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, 100070, Beijing, China.
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Deuter D, Mederer T, Kohl Z, Forras P, Rosengarth K, Schlabeck M, Röhrl D, Wendl C, Fellner C, Schmidt NO, Schlaier J. Amelioration of Parkinsonian tremor evoked by DBS: which role play cerebello-(sub)thalamic fiber tracts? J Neurol 2024; 271:1451-1461. [PMID: 38032372 PMCID: PMC10896868 DOI: 10.1007/s00415-023-12095-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Revised: 11/01/2023] [Accepted: 11/02/2023] [Indexed: 12/01/2023]
Abstract
BACKGROUND Current pathophysiological models of Parkinson's disease (PD) assume a malfunctioning network being adjusted by the DBS signal. As various authors showed a main involvement of the cerebellum within this network, cerebello-cerebral fiber tracts are gaining special interest regarding the mediation of DBS effects. OBJECTIVES The crossing and non-decussating fibers of the dentato-rubro-thalamic tract (c-DRTT/nd-DRTT) and the subthalamo-ponto-cerebellar tract (SPCT) are thought to build up an integrated network enabling a bidimensional communication between the cerebellum and the basal ganglia. The aim of this study was to investigate the influence of these tracts on clinical control of Parkinsonian tremor evoked by DBS. METHODS We analyzed 120 electrode contacts from a cohort of 14 patients with tremor-dominant or equivalence-type PD having received bilateral STN-DBS. Probabilistic tractography was performed to depict the c-DRTT, nd-DRTT, and SPCT. Distance maps were calculated for the tracts and correlated to clinical tremor control for each electrode pole. RESULTS A significant difference between "effective" and "less-effective" contacts was only found for the c-DRTT (p = 0.039), but not for the SPCT, nor the nd-DRTT. In logistic and linear regressions, significant results were also found for the c-DRTT only (pmodel logistic = 0.035, ptract logistic = 0,044; plinear = 0.027). CONCLUSIONS We found a significant correlation between the distance of the DBS electrode pole to the c-DRTT and the clinical efficacy regarding tremor reduction. The c-DRTT might therefore play a major role in the mechanisms of alleviation of Parkinsonian tremor and could eventually serve as a possible DBS target for tremor-dominant PD in future.
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Affiliation(s)
- Daniel Deuter
- Department of Neurosurgery, University Hospital Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany.
- Center for Deep Brain Stimulation, University Hospital Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany.
| | - Tobias Mederer
- Department of Neurosurgery, University Hospital Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany
- Center for Deep Brain Stimulation, University Hospital Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany
| | - Zacharias Kohl
- Center for Deep Brain Stimulation, University Hospital Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany
- Department of Neurology, University Hospital Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany
- Department of Neurology, Regensburg Medbo District Hospital, Universitätsstraße 84, 93053, Regensburg, Germany
| | - Patricia Forras
- Center for Deep Brain Stimulation, University Hospital Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany
- Department of Neurology, University Hospital Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany
- Department of Neurology, Regensburg Medbo District Hospital, Universitätsstraße 84, 93053, Regensburg, Germany
| | - Katharina Rosengarth
- Department of Neurosurgery, University Hospital Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany
| | - Mona Schlabeck
- Center for Deep Brain Stimulation, University Hospital Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany
- Department of Anesthesiology, University Hospital Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany
| | - Daniela Röhrl
- Center for Deep Brain Stimulation, University Hospital Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany
- Department of Anesthesiology, University Hospital Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany
| | - Christina Wendl
- Center for Deep Brain Stimulation, University Hospital Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany
- Department of Radiology, University Hospital Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany
- Department of Radiology, Regensburg Medbo District Hospital, Universitätsstraße 84, 93053, Regensburg, Germany
| | - Claudia Fellner
- Department of Radiology, University Hospital Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany
| | - Nils-Ole Schmidt
- Department of Neurosurgery, University Hospital Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany
| | - Jürgen Schlaier
- Department of Neurosurgery, University Hospital Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany
- Center for Deep Brain Stimulation, University Hospital Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany
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Tao Q, Chao H, Fang D, Dou D. Progress in neurorehabilitation research and the support by the National Natural Science Foundation of China from 2010 to 2022. Neural Regen Res 2024; 19:226-232. [PMID: 37488871 PMCID: PMC10479845 DOI: 10.4103/1673-5374.375342] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Revised: 03/27/2023] [Accepted: 04/14/2023] [Indexed: 07/26/2023] Open
Abstract
The National Natural Science Foundation of China is one of the major funding agencies for neurorehabilitation research in China. This study reviews the frontier directions and achievements in the field of neurorehabilitation in China and worldwide. We used data from the Web of Science Core Collection (WoSCC) database to analyze the publications and data provided by the National Natural Science Foundation of China to analyze funding information. In addition, the prospects for neurorehabilitation research in China are discussed. From 2010 to 2022, a total of 74,220 publications in neurorehabilitation were identified, with there being an overall upward tendency. During this period, the National Natural Science Foundation of China has funded 476 research projects with a total funding of 192.38 million RMB to support neurorehabilitation research in China. With the support of the National Natural Science Foundation of China, China has made some achievements in neurorehabilitation research. Research related to neurorehabilitation is believed to be making steady and significant progress in China.
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Affiliation(s)
- Qian Tao
- School of Medicine, Jinan University, Guangzhou, Guangdong Province, China
- School of Health and Life Science, University of Health and Rehabilitation Sciences, Qingdao, Shandong Province, China
- Department of Health Sciences, National Natural Science Foundation of China, Beijing, China
| | - Honglu Chao
- Department of Health Sciences, National Natural Science Foundation of China, Beijing, China
- Department of Neurosurgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu Province, China
| | - Dong Fang
- Department of Health Sciences, National Natural Science Foundation of China, Beijing, China
| | - Dou Dou
- Department of Health Sciences, National Natural Science Foundation of China, Beijing, China
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El Ouadih Y, Marques A, Pereira B, Luisoni M, Claise B, Coste J, Sontheimer A, Chaix R, Debilly B, Derost P, Morand D, Durif F, Lemaire JJ. Deep brain stimulation of the subthalamic nucleus in severe Parkinson's disease: relationships between dual-contact topographic setting and 1-year worsening of speech and gait. Acta Neurochir (Wien) 2023; 165:3927-3941. [PMID: 37889334 DOI: 10.1007/s00701-023-05843-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Accepted: 06/24/2023] [Indexed: 10/28/2023]
Abstract
BACKGROUND Subthalamic nucleus (STN) deep brain stimulation (DBS) alleviates severe motor fluctuations and dyskinesia in Parkinson's disease, but may result in speech and gait disorders. Among the suspected or demonstrated causes of these adverse effects, we focused on the topography of contact balance (CB; individual, right and left relative dual positions), a scantly studied topic, analyzing the relationships between symmetric or non-symmetric settings, and the worsening of these signs. METHOD An observational monocentric study was conducted on a series of 92 patients after ethical approval. CB was specified by longitudinal and transversal positions and relation to the STN (CB sub-aspects) and totalized at the patient level (patient CB). CB was deemed symmetric when the two contacts were at the same locations relative to the STN. CB was deemed asymmetric when at least one sub-aspect differed in the patient CB. Baseline and 1-year characteristics were routinely collected: (i) general, namely, Unified Parkinson's Disease Rating Scores (UPDRS), II, III motor and IV, daily levodopa equivalent doses, and Parkinson's Disease Questionnaire of Quality of Life (PDQ39) scores; (ii) specific, namely scores for speech (II-5 and III-18) and axial signs (II-14, III-28, III-29, and III-30). Only significant correlations were considered (p < 0.05). RESULTS Baseline characteristics were comparable (symmetric versus asymmetric). CB settings were related to deteriorations of speech and axial signs: communication PDQ39 and UPDRS speech and gait scores worsened exclusively with symmetric settings; the most influential CB sub-aspect was symmetric longitudinal position. CONCLUSION Our findings suggest that avoiding symmetric CB settings, whether by electrode positioning or shaping of electric fields, could reduce worsening of speech and gait.
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Affiliation(s)
- Youssef El Ouadih
- Université Clermont Auvergne, Clermont Auvergne INP, CHU Clermont-Ferrand, CNRS, Institut Pascal, 63000, Clermont-Ferrand, France
- Service de Neurochirurgie, CHU Clermont-Ferrand, 63000, Clermont-Ferrand, France
| | - Ana Marques
- Université Clermont Auvergne, Clermont Auvergne INP, CHU Clermont-Ferrand, CNRS, Institut Pascal, 63000, Clermont-Ferrand, France
- Service de Neurologie, CHU Clermont-Ferrand, 63000, Clermont-Ferrand, France
| | - Bruno Pereira
- Direction de La Recherche Clinique Et de L'Innovation, CHU Clermont-Ferrand, 63000, Clermont-Ferrand, France
| | - Maxime Luisoni
- Université Clermont Auvergne, Clermont Auvergne INP, CHU Clermont-Ferrand, CNRS, Institut Pascal, 63000, Clermont-Ferrand, France
| | - Béatrice Claise
- Service de Radiologie, Unité de Neuroradiologie, CHU Clermont-Ferrand, 63000, Clermont-Ferrand, France
| | - Jérôme Coste
- Université Clermont Auvergne, Clermont Auvergne INP, CHU Clermont-Ferrand, CNRS, Institut Pascal, 63000, Clermont-Ferrand, France
- Service de Neurochirurgie, CHU Clermont-Ferrand, 63000, Clermont-Ferrand, France
| | - Anna Sontheimer
- Université Clermont Auvergne, Clermont Auvergne INP, CHU Clermont-Ferrand, CNRS, Institut Pascal, 63000, Clermont-Ferrand, France
- Service de Neurochirurgie, CHU Clermont-Ferrand, 63000, Clermont-Ferrand, France
| | - Rémi Chaix
- Université Clermont Auvergne, Clermont Auvergne INP, CHU Clermont-Ferrand, CNRS, Institut Pascal, 63000, Clermont-Ferrand, France
- Service de Neurochirurgie, CHU Clermont-Ferrand, 63000, Clermont-Ferrand, France
| | - Bérangère Debilly
- Service de Neurologie, CHU Clermont-Ferrand, 63000, Clermont-Ferrand, France
| | - Philippe Derost
- Service de Neurologie, CHU Clermont-Ferrand, 63000, Clermont-Ferrand, France
| | - Dominique Morand
- Direction de La Recherche Clinique Et de L'Innovation, CHU Clermont-Ferrand, 63000, Clermont-Ferrand, France
| | - Franck Durif
- Université Clermont Auvergne, Clermont Auvergne INP, CHU Clermont-Ferrand, CNRS, Institut Pascal, 63000, Clermont-Ferrand, France
- Service de Neurologie, CHU Clermont-Ferrand, 63000, Clermont-Ferrand, France
| | - Jean-Jacques Lemaire
- Université Clermont Auvergne, Clermont Auvergne INP, CHU Clermont-Ferrand, CNRS, Institut Pascal, 63000, Clermont-Ferrand, France.
- Service de Neurochirurgie, CHU Clermont-Ferrand, 63000, Clermont-Ferrand, France.
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9
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Zhou S, Gao Y, Li R, Wang H, Zhang M, Guo Y, Cui W, Brown KG, Han C, Shi L, Liu H, Zhang J, Li Y, Meng F. Neurosurgical robots in China: State of the art and future prospect. iScience 2023; 26:107983. [PMID: 37867956 PMCID: PMC10589856 DOI: 10.1016/j.isci.2023.107983] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2023] Open
Abstract
Neurosurgical robots have developed for decades and can effectively assist surgeons to carry out a variety of surgical operations, such as biopsy, stereo-electroencephalography (SEEG), deep brain stimulation (DBS), and so forth. In recent years, neurosurgical robots in China have developed rapidly. This article will focus on several key skills in neurosurgical robots, such as medical imaging systems, automatic manipulator, lesion localization techniques, multimodal image fusion technology, registration method, and vascular imaging technology; introduce the clinical application of neurosurgical robots in China, and look forward to the potential improvement points in the future based on our experience and research in the field.
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Affiliation(s)
- Siyu Zhou
- Beijing Neurosurgical Institute, Capital Medical University, Beijing 100070, China
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
- Beijing Key Laboratory of Neurostimulation, Beijing 100070, China
| | - Yuan Gao
- Beijing Neurosurgical Institute, Capital Medical University, Beijing 100070, China
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
- Beijing Key Laboratory of Neurostimulation, Beijing 100070, China
| | - Renpeng Li
- Beijing Neurosurgical Institute, Capital Medical University, Beijing 100070, China
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
- Beijing Key Laboratory of Neurostimulation, Beijing 100070, China
| | - Huizhi Wang
- Beijing Neurosurgical Institute, Capital Medical University, Beijing 100070, China
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
- Beijing Key Laboratory of Neurostimulation, Beijing 100070, China
| | - Moxuan Zhang
- Beijing Neurosurgical Institute, Capital Medical University, Beijing 100070, China
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
- Beijing Key Laboratory of Neurostimulation, Beijing 100070, China
| | - Yuzhu Guo
- School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China
| | - Weigang Cui
- School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China
| | - Kayla Giovanna Brown
- Beijing Neurosurgical Institute, Capital Medical University, Beijing 100070, China
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
- Beijing Key Laboratory of Neurostimulation, Beijing 100070, China
| | - Chunlei Han
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
- Beijing Key Laboratory of Neurostimulation, Beijing 100070, China
| | - Lin Shi
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
- Beijing Key Laboratory of Neurostimulation, Beijing 100070, China
| | - Huanguang Liu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
- Beijing Key Laboratory of Neurostimulation, Beijing 100070, China
| | - Jianguo Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
- Beijing Key Laboratory of Neurostimulation, Beijing 100070, China
| | - Yang Li
- School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China
| | - Fangang Meng
- Beijing Neurosurgical Institute, Capital Medical University, Beijing 100070, China
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
- Beijing Key Laboratory of Neurostimulation, Beijing 100070, China
- Chinese Institute for Brain Research, Beijing 102206, China
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10
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Xu C, Qi L, Wang X, Schaper FLWVJ, Wu D, Yu T, Yan X, Jin G, Wang Q, Wang X, Huang X, Wang Y, Chen Y, Liu J, Wang Y, Horn A, Fisher RS, Ren L. Functional connectomic profile correlates with effective anterior thalamic stimulation for refractory epilepsy. Brain Stimul 2023; 16:1302-1309. [PMID: 37633491 DOI: 10.1016/j.brs.2023.08.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 08/19/2023] [Accepted: 08/21/2023] [Indexed: 08/28/2023] Open
Abstract
BACKGROUND Deep brain stimulation of the anterior nucleus of the thalamus (ANT-DBS) is an effective treatment for refractory epilepsy; however, seizure outcome varies among individuals. Identifying a reliable noninvasive biomarker to predict good responders would be helpful. OBJECTIVES To test whether the functional connectivity between the ANT-DBS sites and the seizure foci correlates with effective seizure control in refractory epilepsy. METHODS We performed a proof-of-concept pilot study of patients with focal refractory epilepsy receiving ANT-DBS. Using normative human connectome data derived from 1000 healthy participants, we investigated whether intrinsic functional connectivity between the seizure foci and the DBS site was associated with seizure outcome. We repeated this analysis controlling for the extent of seizure foci, distance between the seizure foci and DBS site, and using functional connectivity of the ANT instead of the DBS site to test the contribution of variance in DBS sites. RESULTS Eighteen patients with two or more seizure foci were included. Greater functional connectivity between the seizure foci and the DBS site correlated with more favorable outcome. The degree of functional connectivity accounted for significant variance in clinical outcomes (DBS site: |r| = 0.773, p < 0.001 vs ANT-atlas: |r| = 0.715, p = 0.001), which remained significant when controlling for the extent of the seizure foci (|r| = 0.773, p < 0.001) and the distance between the seizure foci and DBS site (|r| = 0.777, p < 0.001). Significant correlations were independent of variance in the DBS sites (|r| = 0.148, p = 0.57). CONCLUSION These findings suggest that functional connectomic profile is a potential reliable non-invasive biomarker to predict ANT-DBS outcomes. Accordingly, the identification of ANT responders could decrease the surgical risk for patients who may not benefit and optimize the cost-effective allocation of health care resources.
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Affiliation(s)
- Cuiping Xu
- National Center for Neurological Disorders, Beijing, China; Department of Functional Neurosurgery, Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Clinical Center for Epilepsy, Capital Medical University, Beijing, China
| | - Lei Qi
- National Center for Neurological Disorders, Beijing, China; Department of Neurology, Xuanwu Hospital, Clinical Center for Epilepsy, Capital Medical University, Beijing, China
| | - Xueyuan Wang
- National Center for Neurological Disorders, Beijing, China; Department of Functional Neurosurgery, Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Clinical Center for Epilepsy, Capital Medical University, Beijing, China
| | - Frédéric L W V J Schaper
- Center for Brain Circuit Therapeutics, Departments of Neurology, Psychiatry, and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, United States
| | - Di Wu
- National Center for Neurological Disorders, Beijing, China; Department of Neurology, Xuanwu Hospital, Clinical Center for Epilepsy, Capital Medical University, Beijing, China
| | - Tao Yu
- National Center for Neurological Disorders, Beijing, China; Department of Functional Neurosurgery, Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Clinical Center for Epilepsy, Capital Medical University, Beijing, China
| | - Xiaoming Yan
- National Center for Neurological Disorders, Beijing, China; Department of Functional Neurosurgery, Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Clinical Center for Epilepsy, Capital Medical University, Beijing, China
| | - Guangyuan Jin
- National Center for Neurological Disorders, Beijing, China; Department of Neurology, Xuanwu Hospital, Clinical Center for Epilepsy, Capital Medical University, Beijing, China
| | - Qiao Wang
- National Center for Neurological Disorders, Beijing, China; Department of Neurology, Xuanwu Hospital, Clinical Center for Epilepsy, Capital Medical University, Beijing, China
| | - Xiaopeng Wang
- National Center for Neurological Disorders, Beijing, China; Department of Neurology, Xuanwu Hospital, Clinical Center for Epilepsy, Capital Medical University, Beijing, China
| | - Xinqi Huang
- National Center for Neurological Disorders, Beijing, China; Department of Neurology, Xuanwu Hospital, Clinical Center for Epilepsy, Capital Medical University, Beijing, China
| | - Yuke Wang
- National Center for Neurological Disorders, Beijing, China; Department of Neurology, Xuanwu Hospital, Clinical Center for Epilepsy, Capital Medical University, Beijing, China
| | - Yuanhong Chen
- National Center for Neurological Disorders, Beijing, China; Department of Neurology, Xuanwu Hospital, Clinical Center for Epilepsy, Capital Medical University, Beijing, China
| | - Jinghui Liu
- National Center for Neurological Disorders, Beijing, China; Department of Neurology, Xuanwu Hospital, Clinical Center for Epilepsy, Capital Medical University, Beijing, China
| | - Yuping Wang
- National Center for Neurological Disorders, Beijing, China; Department of Neurology, Xuanwu Hospital, Clinical Center for Epilepsy, Capital Medical University, Beijing, China
| | - Andreas Horn
- Center for Brain Circuit Therapeutics, Departments of Neurology, Psychiatry, and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, United States; Department of Neurology, Charité-Universitätsmedizin Berlin, Berlin, Germany; MGH Neurosurgery & Center for Neurotechnology and Neurorecovery (CNTR) at MGH Neurology, Massachusetts General Hospital, Harvard Medical School, United States
| | - Robert S Fisher
- Department of Neurology and Neurological Sciences and Neurosurgery by Courtesy, Stanford University School of Medicine, Palo Alto, CA, USA
| | - Liankun Ren
- National Center for Neurological Disorders, Beijing, China; Department of Neurology, Xuanwu Hospital, Clinical Center for Epilepsy, Capital Medical University, Beijing, China; Chinese Institute for Brain Research, Beijing, China.
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11
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Peng X, Baker-Vogel B, Sarhan M, Short EB, Zhu W, Liu H, Kautz S, Badran BW. Left or right ear? A neuroimaging study using combined taVNS/fMRI to understand the interaction between ear stimulation target and lesion location in chronic stroke. Brain Stimul 2023; 16:1144-1153. [PMID: 37517466 DOI: 10.1016/j.brs.2023.07.050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2023] [Revised: 06/29/2023] [Accepted: 07/23/2023] [Indexed: 08/01/2023] Open
Abstract
BACKGROUND Implanted vagus nerve stimulation (VNS) and transcutaneous auricular VNS (taVNS) have been primarily administered clinically to the unilateral-left vagus nerve. This left-only convention has proved clinically beneficial in brain disorders. However, in stroke survivors, the presence of a lesion in the brain may complicate VNS-mediated signaling, and it is important to understand the laterality effects of VNS in stroke survivors to optimize the intervention. OBJECTIVE To understand whether taVNS delivered to different ear targets relative to the lesion (ipsilesional vs contralesional vs bilateral vs sham) impacts blood oxygenation level dependent (BOLD) signal propagation in stroke survivors. METHODS We enrolled 20 adults with a prior history of stroke. Each participant underwent a single visit, during which taVNS was delivered concurrently during functional magnetic resonance imaging (fMRI) acquisition. Each participant received three discrete active stimulation conditions (ipsilesional, contralesional, bilateral) and one sham condition in a randomized order. Stimulation-related BOLD signal changes in the active conditions were compared to sham conditions to understand the interaction taVNS and laterality effects. RESULTS All active taVNS conditions deactivated the contralesional default mode network related regions compared to sham, however only ipsilesional taVNS enhanced the activations in the ipsilesional visuomotor and secondary visual cortex. Furthermore, we reveal an interaction in task activations between taVNS and cortical visuomotor areas, where ipsilesional taVNS significantly increased ipsilesional visuomotor activity and decreased contralesional visuomotor activity compared to sham. CONCLUSION Laterality of taVNS relative to the lesion is a critical factor in optimizing taVNS in a stroke population, with ipsilesional stimulation providing largest direct brain activation and should be explored further when designing taVNS studies in neurorehabilitation.
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Affiliation(s)
- Xiaolong Peng
- Department of Psychiatry and Behavioral Sciences, Neuro-X Lab, Medical University of South Carolina, Charleston, SC, USA; Deparment of Neuroscience, Medical University of South Carolina, Charleston, SC, USA
| | - Brenna Baker-Vogel
- Department of Psychiatry and Behavioral Sciences, Neuro-X Lab, Medical University of South Carolina, Charleston, SC, USA; Deparment of Neuroscience, Medical University of South Carolina, Charleston, SC, USA
| | - Mutaz Sarhan
- Department of Psychiatry and Behavioral Sciences, Neuro-X Lab, Medical University of South Carolina, Charleston, SC, USA; Deparment of Neuroscience, Medical University of South Carolina, Charleston, SC, USA
| | - Edward B Short
- Department of Psychiatry and Behavioral Sciences, Neuro-X Lab, Medical University of South Carolina, Charleston, SC, USA; Deparment of Neuroscience, Medical University of South Carolina, Charleston, SC, USA
| | - Wenzhen Zhu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Hesheng Liu
- Deparment of Neuroscience, Medical University of South Carolina, Charleston, SC, USA; Changping Laboratory, Beijing, China
| | - Steven Kautz
- Department of Health Sciences and Research, Medical University of South Carolina, Charleston, SC, USA
| | - Bashar W Badran
- Department of Psychiatry and Behavioral Sciences, Neuro-X Lab, Medical University of South Carolina, Charleston, SC, USA; Deparment of Neuroscience, Medical University of South Carolina, Charleston, SC, USA.
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12
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Eraifej J, Cabral J, Fernandes HM, Kahan J, He S, Mancini L, Thornton J, White M, Yousry T, Zrinzo L, Akram H, Limousin P, Foltynie T, Aziz TZ, Deco G, Kringelbach M, Green AL. Modulation of limbic resting-state networks by subthalamic nucleus deep brain stimulation. Netw Neurosci 2023; 7:478-495. [PMID: 37397890 PMCID: PMC10312264 DOI: 10.1162/netn_a_00297] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Accepted: 11/29/2022] [Indexed: 09/03/2023] Open
Abstract
Beyond the established effects of subthalamic nucleus deep brain stimulation (STN-DBS) in reducing motor symptoms in Parkinson's disease, recent evidence has highlighted the effect on non-motor symptoms. However, the impact of STN-DBS on disseminated networks remains unclear. This study aimed to perform a quantitative evaluation of network-specific modulation induced by STN-DBS using Leading Eigenvector Dynamics Analysis (LEiDA). We calculated the occupancy of resting-state networks (RSNs) in functional MRI data from 10 patients with Parkinson's disease implanted with STN-DBS and statistically compared between ON and OFF conditions. STN-DBS was found to specifically modulate the occupancy of networks overlapping with limbic RSNs. STN-DBS significantly increased the occupancy of an orbitofrontal limbic subsystem with respect to both DBS OFF (p = 0.0057) and 49 age-matched healthy controls (p = 0.0033). Occupancy of a diffuse limbic RSN was increased with STN-DBS OFF when compared with healthy controls (p = 0.021), but not when STN-DBS was ON, which indicates rebalancing of this network. These results highlight the modulatory effect of STN-DBS on components of the limbic system, particularly within the orbitofrontal cortex, a structure associated with reward processing. These results reinforce the value of quantitative biomarkers of RSN activity in evaluating the disseminated impact of brain stimulation techniques and the personalization of therapeutic strategies.
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Affiliation(s)
- John Eraifej
- Oxford Functional Neurosurgery Group, Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom
| | - Joana Cabral
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Oxford, United Kingdom
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Henrique M. Fernandes
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Joshua Kahan
- Sobell Department for Motor Neurosciences and Movement Disorders, UCL Institute of Neurology, London, United Kingdom
| | - Shenghong He
- MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Laura Mancini
- Neuroradiological Academic Unit, Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, University College London, London, United Kingdom
- Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, United Kingdom
| | - John Thornton
- Neuroradiological Academic Unit, Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, University College London, London, United Kingdom
- Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, United Kingdom
| | - Mark White
- Neuroradiological Academic Unit, Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, University College London, London, United Kingdom
- Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, United Kingdom
| | - Tarek Yousry
- Neuroradiological Academic Unit, Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, University College London, London, United Kingdom
- Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, United Kingdom
| | - Ludvic Zrinzo
- Sobell Department for Motor Neurosciences and Movement Disorders, UCL Institute of Neurology, London, United Kingdom
| | - Harith Akram
- Sobell Department for Motor Neurosciences and Movement Disorders, UCL Institute of Neurology, London, United Kingdom
| | - Patricia Limousin
- Sobell Department for Motor Neurosciences and Movement Disorders, UCL Institute of Neurology, London, United Kingdom
| | - Tom Foltynie
- Sobell Department for Motor Neurosciences and Movement Disorders, UCL Institute of Neurology, London, United Kingdom
| | - Tipu Z. Aziz
- Oxford Functional Neurosurgery Group, Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Universitat Pompeu Fabra, Barcelona, Spain
- Institució Catalana de la Recerca i Estudis Avançats, Barcelona, Spain
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Morten Kringelbach
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Oxford, United Kingdom
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Alexander L. Green
- Oxford Functional Neurosurgery Group, Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom
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13
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Upton S, Brown AA, Golzy M, Garland EL, Froeliger B. Right inferior frontal gyrus theta-burst stimulation reduces smoking behaviors and strengthens fronto-striatal-limbic resting-state functional connectivity: a randomized crossover trial. Front Psychiatry 2023; 14:1166912. [PMID: 37457779 PMCID: PMC10338839 DOI: 10.3389/fpsyt.2023.1166912] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Accepted: 05/22/2023] [Indexed: 07/18/2023] Open
Abstract
Introduction Functional and anatomical irregularities in the right inferior frontal gyrus (rIFG), a ventrolateral prefrontal region that mediates top-down inhibitory control over prepotent behavioral responding, are implicated in the ongoing maintenance of nicotine dependence (ND). However, there is little research on the effects of neuromodulation of the rIFG on smoking behavior, inhibitory control, and resting-state functional connectivity (rsFC) among individuals with ND. Methods In this double-blind, crossover, theta-burst stimulation (TBS) study, adults with ND (N = 31; female: n = 15) completed a baseline session and were then randomized to two counterbalanced sessions of functionally neuronavigated TBS to the rIFG: continuous TBS (cTBS) on 1 day and intermittent TBS (iTBS) on another. Differences in cigarette cravings, smoking, and fronto-striatal-limbic rsFC were assessed. Results Relative to baseline, cTBS significantly reduced appetitive and withdrawal cravings immediately after treatment. The effects of cTBS on withdrawal craving persisted for 24 h, as well as produced a reduction in smoking. Furthermore, cTBS significantly strengthened rsFC between the rIFG pars opercularis and subcallosal cingulate (fronto-striatal circuit), and between the rIFG pars opercularis and the right posterior parahippocampal gyrus (fronto-limbic circuit). At post-24 h, cTBS-induced increase in fronto-striatal rsFC was significantly associated with less appetitive craving, while the increase in fronto-limbic rsFC was significantly associated with less withdrawal craving and smoking. Discussion These findings warrant further investigation into the potential value of rIFG cTBS to attenuate smoking behavior among individuals with ND.
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Affiliation(s)
- Spencer Upton
- Department of Psychological Sciences, University of Missouri, Columbia, MO, United States
| | - Alexander A. Brown
- Department of Psychological Sciences, University of Missouri, Columbia, MO, United States
- Department of Psychiatry, School of Medicine, University of Missouri, Columbia, MO, United States
- Cognitive Neuroscience Systems Core Facility, University of Missouri, Columbia, MO, United States
| | - Mojgan Golzy
- Biostatistics Unit, Department of Family and Community Medicine, School of Medicine, University of Missouri, Columbia, MO, United States
| | - Eric L. Garland
- Center on Mindfulness and Integrative Health Intervention Development, College of Social Work, University of Utah, Salt Lake City, UT, United States
| | - Brett Froeliger
- Department of Psychological Sciences, University of Missouri, Columbia, MO, United States
- Department of Psychiatry, School of Medicine, University of Missouri, Columbia, MO, United States
- Cognitive Neuroscience Systems Core Facility, University of Missouri, Columbia, MO, United States
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14
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Santos AN, Kherif F, Melie-Garcia L, Lutti A, Chiappini A, Rauschenbach L, Dinger TF, Riess C, El Rahal A, Darkwah Oppong M, Sure U, Dammann P, Draganski B. Parkinson's disease may disrupt overlapping subthalamic nucleus and pallidal motor networks. Neuroimage Clin 2023; 38:103432. [PMID: 37210889 PMCID: PMC10213095 DOI: 10.1016/j.nicl.2023.103432] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Revised: 04/13/2023] [Accepted: 05/07/2023] [Indexed: 05/23/2023]
Abstract
There is an ongoing debate about differential clinical outcome and associated adverse effects of deep brain stimulation (DBS) in Parkinson's disease (PD) targeting the subthalamic nucleus (STN) or the globus pallidus pars interna (GPi). Given that functional connectivity profiles suggest beneficial DBS effects within a common network, the empirical evidence about the underlying anatomical circuitry is still scarce. Therefore, we investigate the STN and GPi-associated structural covariance brain patterns in PD patients and healthy controls. We estimate GPi's and STN's whole-brain structural covariance from magnetic resonance imaging (MRI) in a normative mid- to old-age community-dwelling cohort (n = 1184) across maps of grey matter volume, magnetization transfer (MT) saturation, longitudinal relaxation rate (R1), effective transversal relaxation rate (R2*) and effective proton density (PD*). We compare these with the structural covariance estimates in patients with idiopathic PD (n = 32) followed by validation using a reduced size controls' cohort (n = 32). In the normative data set, we observed overlapping spatially distributed cortical and subcortical covariance patterns across maps confined to basal ganglia, thalamus, motor, and premotor cortical areas. Only the subcortical and midline motor cortical areas were confirmed in the reduced size cohort. These findings contrasted with the absence of structural covariance with cortical areas in the PD cohort. We interpret with caution the differential covariance maps of overlapping STN and GPi networks in patients with PD and healthy controls as correlates of motor network disruption. Our study provides face validity to the proposed extension of the currently existing structural covariance methods based on morphometry features to multiparameter MRI sensitive to brain tissue microstructure.
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Affiliation(s)
- Alejandro N Santos
- Laboratory of Research in Neuroimaging (LREN) -Department of Clinical Neuroscience, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland; Department of Neurosurgery, University Hospital Essen, Essen, Germany; Center for Translational Neuroscience and Behavioral Science (C-TNBS), University of Duisburg, Essen, Germany
| | - Ferath Kherif
- Laboratory of Research in Neuroimaging (LREN) -Department of Clinical Neuroscience, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Lester Melie-Garcia
- Laboratory of Research in Neuroimaging (LREN) -Department of Clinical Neuroscience, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Antoine Lutti
- Laboratory of Research in Neuroimaging (LREN) -Department of Clinical Neuroscience, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Alessio Chiappini
- Department of Neurosurgery, University Hospital Basel, Basel, Switzerland
| | - Laurèl Rauschenbach
- Department of Neurosurgery, University Hospital Essen, Essen, Germany; Center for Translational Neuroscience and Behavioral Science (C-TNBS), University of Duisburg, Essen, Germany
| | - Thiemo F Dinger
- Department of Neurosurgery, University Hospital Essen, Essen, Germany; Center for Translational Neuroscience and Behavioral Science (C-TNBS), University of Duisburg, Essen, Germany
| | - Christoph Riess
- Department of Neurosurgery, University Hospital Essen, Essen, Germany; Center for Translational Neuroscience and Behavioral Science (C-TNBS), University of Duisburg, Essen, Germany
| | - Amir El Rahal
- Department of Neurosurgery, University Hospital Freiburg, Freiburg im Breisgau, Germany
| | - Marvin Darkwah Oppong
- Department of Neurosurgery, University Hospital Essen, Essen, Germany; Center for Translational Neuroscience and Behavioral Science (C-TNBS), University of Duisburg, Essen, Germany
| | - Ulrich Sure
- Department of Neurosurgery, University Hospital Essen, Essen, Germany; Center for Translational Neuroscience and Behavioral Science (C-TNBS), University of Duisburg, Essen, Germany
| | - Philipp Dammann
- Department of Neurosurgery, University Hospital Essen, Essen, Germany; Center for Translational Neuroscience and Behavioral Science (C-TNBS), University of Duisburg, Essen, Germany
| | - Bogdan Draganski
- Laboratory of Research in Neuroimaging (LREN) -Department of Clinical Neuroscience, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland; Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
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15
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Lamoš M, Bočková M, Goldemundová S, Baláž M, Chrastina J, Rektor I. The effect of deep brain stimulation in Parkinson's disease reflected in EEG microstates. NPJ Parkinsons Dis 2023; 9:63. [PMID: 37069159 PMCID: PMC10110608 DOI: 10.1038/s41531-023-00508-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2022] [Accepted: 04/03/2023] [Indexed: 04/19/2023] Open
Abstract
Mechanisms of deep brain stimulation (DBS) on cortical networks were explored mainly by fMRI. Advanced analysis of high-density EEG is a source of additional information and may provide clinically useful biomarkers. The presented study evaluates EEG microstates in Parkinson's disease and the effect of DBS of the subthalamic nucleus (STN). The association between revealed spatiotemporal dynamics of brain networks and changes in oscillatory activity and clinical examination were assessed. Thirty-seven patients with Parkinson's disease treated by STN-DBS underwent two sessions (OFF and ON stimulation conditions) of resting-state EEG. EEG microstates were analyzed in patient recordings and in a matched healthy control dataset. Microstate parameters were then compared across groups and were correlated with clinical and neuropsychological scores. Of the five revealed microstates, two differed between Parkinson's disease patients and healthy controls. Another microstate differed between ON and OFF stimulation conditions in the patient group and restored parameters in the ON stimulation state toward to healthy values. The mean beta power of that microstate was the highest in patients during the OFF stimulation condition and the lowest in healthy controls; sources were localized mainly in the supplementary motor area. Changes in microstate parameters correlated with UPDRS and neuropsychological scores. Disease specific alterations in the spatiotemporal dynamics of large-scale brain networks can be described by EEG microstates. The approach can reveal changes reflecting the effect of DBS on PD motor symptoms as well as changes probably related to non-motor symptoms not influenced by DBS.
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Grants
- NU21-04-00445 Agentura Pro Zdravotnický Výzkum České Republiky (Czech Health Research Council)
- NU21-04-00445 Agentura Pro Zdravotnický Výzkum České Republiky (Czech Health Research Council)
- NU21-04-00445 Agentura Pro Zdravotnický Výzkum České Republiky (Czech Health Research Council)
- NU21-04-00445 Agentura Pro Zdravotnický Výzkum České Republiky (Czech Health Research Council)
- NU21-04-00445 Agentura Pro Zdravotnický Výzkum České Republiky (Czech Health Research Council)
- NU21-04-00445 Agentura Pro Zdravotnický Výzkum České Republiky (Czech Health Research Council)
- LM2018129 Ministerstvo Školství, Mládeže a Tělovýchovy (Ministry of Education, Youth and Sports)
- LM2018129 Ministerstvo Školství, Mládeže a Tělovýchovy (Ministry of Education, Youth and Sports)
- LM2018129 Ministerstvo Školství, Mládeže a Tělovýchovy (Ministry of Education, Youth and Sports)
- LM2018129 Ministerstvo Školství, Mládeže a Tělovýchovy (Ministry of Education, Youth and Sports)
- LM2018129 Ministerstvo Školství, Mládeže a Tělovýchovy (Ministry of Education, Youth and Sports)
- LM2018129 Ministerstvo Školství, Mládeže a Tělovýchovy (Ministry of Education, Youth and Sports)
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Affiliation(s)
- Martin Lamoš
- Brain and Mind Research Program, Central European Institute of Technology, Masaryk University, Brno, Czech Republic
| | - Martina Bočková
- Brain and Mind Research Program, Central European Institute of Technology, Masaryk University, Brno, Czech Republic
- Movement Disorders Center, First Department of Neurology, Masaryk University School of Medicine, St. Anne's Hospital, Brno, Czech Republic
| | - Sabina Goldemundová
- Brain and Mind Research Program, Central European Institute of Technology, Masaryk University, Brno, Czech Republic
| | - Marek Baláž
- Brain and Mind Research Program, Central European Institute of Technology, Masaryk University, Brno, Czech Republic
- Movement Disorders Center, First Department of Neurology, Masaryk University School of Medicine, St. Anne's Hospital, Brno, Czech Republic
| | - Jan Chrastina
- Brain and Mind Research Program, Central European Institute of Technology, Masaryk University, Brno, Czech Republic
- Department of Neurosurgery, Masaryk University School of Medicine, St. Anne's Hospital, Brno, Czech Republic
| | - Ivan Rektor
- Brain and Mind Research Program, Central European Institute of Technology, Masaryk University, Brno, Czech Republic.
- Movement Disorders Center, First Department of Neurology, Masaryk University School of Medicine, St. Anne's Hospital, Brno, Czech Republic.
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16
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Lead-DBS v3.0: Mapping deep brain stimulation effects to local anatomy and global networks. Neuroimage 2023; 268:119862. [PMID: 36610682 PMCID: PMC10144063 DOI: 10.1016/j.neuroimage.2023.119862] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Revised: 12/22/2022] [Accepted: 01/03/2023] [Indexed: 01/07/2023] Open
Abstract
Following its introduction in 2014 and with support of a broad international community, the open-source toolbox Lead-DBS has evolved into a comprehensive neuroimaging platform dedicated to localizing, reconstructing, and visualizing electrodes implanted in the human brain, in the context of deep brain stimulation (DBS) and epilepsy monitoring. Expanding clinical indications for DBS, increasing availability of related research tools, and a growing community of clinician-scientist researchers, however, have led to an ongoing need to maintain, update, and standardize the codebase of Lead-DBS. Major development efforts of the platform in recent years have now yielded an end-to-end solution for DBS-based neuroimaging analysis allowing comprehensive image preprocessing, lead localization, stimulation volume modeling, and statistical analysis within a single tool. The aim of the present manuscript is to introduce fundamental additions to the Lead-DBS pipeline including a deformation warpfield editor and novel algorithms for electrode localization. Furthermore, we introduce a total of three comprehensive tools to map DBS effects to local, tract- and brain network-levels. These updates are demonstrated using a single patient example (for subject-level analysis), as well as a retrospective cohort of 51 Parkinson's disease patients who underwent DBS of the subthalamic nucleus (for group-level analysis). Their applicability is further demonstrated by comparing the various methodological choices and the amount of explained variance in clinical outcomes across analysis streams. Finally, based on an increasing need to standardize folder and file naming specifications across research groups in neuroscience, we introduce the brain imaging data structure (BIDS) derivative standard for Lead-DBS. Thus, this multi-institutional collaborative effort represents an important stage in the evolution of a comprehensive, open-source pipeline for DBS imaging and connectomics.
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17
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Wong JK, Mayberg HS, Wang DD, Richardson RM, Halpern CH, Krinke L, Arlotti M, Rossi L, Priori A, Marceglia S, Gilron R, Cavanagh JF, Judy JW, Miocinovic S, Devergnas AD, Sillitoe RV, Cernera S, Oehrn CR, Gunduz A, Goodman WK, Petersen EA, Bronte-Stewart H, Raike RS, Malekmohammadi M, Greene D, Heiden P, Tan H, Volkmann J, Voon V, Li L, Sah P, Coyne T, Silburn PA, Kubu CS, Wexler A, Chandler J, Provenza NR, Heilbronner SR, Luciano MS, Rozell CJ, Fox MD, de Hemptinne C, Henderson JM, Sheth SA, Okun MS. Proceedings of the 10th annual deep brain stimulation think tank: Advances in cutting edge technologies, artificial intelligence, neuromodulation, neuroethics, interventional psychiatry, and women in neuromodulation. Front Hum Neurosci 2023; 16:1084782. [PMID: 36819295 PMCID: PMC9933515 DOI: 10.3389/fnhum.2022.1084782] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Accepted: 12/12/2022] [Indexed: 02/05/2023] Open
Abstract
The deep brain stimulation (DBS) Think Tank X was held on August 17-19, 2022 in Orlando FL. The session organizers and moderators were all women with the theme women in neuromodulation. Dr. Helen Mayberg from Mt. Sinai, NY was the keynote speaker. She discussed milestones and her experiences in developing depression DBS. The DBS Think Tank was founded in 2012 and provides an open platform where clinicians, engineers and researchers (from industry and academia) can freely discuss current and emerging DBS technologies as well as the logistical and ethical issues facing the field. The consensus among the DBS Think Tank X speakers was that DBS has continued to expand in scope however several indications have reached the "trough of disillusionment." DBS for depression was considered as "re-emerging" and approaching a slope of enlightenment. DBS for depression will soon re-enter clinical trials. The group estimated that globally more than 244,000 DBS devices have been implanted for neurological and neuropsychiatric disorders. This year's meeting was focused on advances in the following areas: neuromodulation in Europe, Asia, and Australia; cutting-edge technologies, closed loop DBS, DBS tele-health, neuroethics, lesion therapy, interventional psychiatry, and adaptive DBS.
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Affiliation(s)
- Joshua K. Wong
- Department of Neurology, Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, United States
| | - Helen S. Mayberg
- Department of Neurology, Neurosurgery, Psychiatry, and Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Doris D. Wang
- Department of Neurological Surgery, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States
| | - R. Mark Richardson
- Department of Neurosurgery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - Casey H. Halpern
- Richards Medical Research Laboratories, Department of Neurosurgery, Perelman School of Medicine, Pennsylvania Hospital, University of Pennsylvania, Philadelphia, PA, United States
| | - Lothar Krinke
- Newronika, Goose Creek, SC, United States
- Department of Neuroscience, West Virginia University, Morgantown, WV, United States
| | | | | | | | | | | | - James F. Cavanagh
- Department of Psychology, University of New Mexico, Albuquerque, NM, United States
| | - Jack W. Judy
- Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL, United States
| | - Svjetlana Miocinovic
- Department of Neurology, School of Medicine, Emory University, Atlanta, GA, United States
| | - Annaelle D. Devergnas
- Department of Neurology, School of Medicine, Emory University, Atlanta, GA, United States
| | - Roy V. Sillitoe
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, United States
| | - Stephanie Cernera
- Department of Neurological Surgery, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States
| | - Carina R. Oehrn
- Department of Neurological Surgery, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States
| | - Aysegul Gunduz
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL, United States
| | - Wayne K. Goodman
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, United States
| | - Erika A. Petersen
- Department of Neurosurgery, University of Arkansas for Medical Sciences, Little Rock, AR, United States
| | - Helen Bronte-Stewart
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
| | - Robert S. Raike
- Restorative Therapies Group Implantables, Research, and Core Technology, Medtronic Inc., Minneapolis, MN, United States
| | | | - David Greene
- NeuroPace, Inc., Mountain View, CA, United States
| | - Petra Heiden
- Department of Stereotactic and Functional Neurosurgery, Faculty of Medicine, University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Huiling Tan
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Jens Volkmann
- Department of Neurology, University of Würzburg, Würzburg, Germany
| | - Valerie Voon
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | - Luming Li
- National Engineering Research Center of Neuromodulation, School of Aerospace Engineering, Tsinghua University, Beijing, China
| | - Pankaj Sah
- Queensland Brain Institute, University of Queensland, St Lucia, QLD, Australia
| | - Terry Coyne
- Queensland Brain Institute, University of Queensland, St Lucia, QLD, Australia
| | - Peter A. Silburn
- Queensland Brain Institute, University of Queensland, St Lucia, QLD, Australia
| | - Cynthia S. Kubu
- Department of Neurology, Cleveland Clinic, Cleveland, OH, United States
| | - Anna Wexler
- Department of Medical Ethics and Health Policy, University of Pennsylvania, Philadelphia, PA, United States
| | - Jennifer Chandler
- Centre for Health Law, Policy, and Ethics, Faculty of Law, University of Ottawa, Ottawa, ON, Canada
| | - Nicole R. Provenza
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, United States
| | - Sarah R. Heilbronner
- Department of Neuroscience, University of Minnesota, Minneapolis, MN, United States
| | - Marta San Luciano
- Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States
| | - Christopher J. Rozell
- School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, United States
| | - Michael D. Fox
- Center for Brain Circuit Therapeutics, Department of Neurology, Psychiatry, Radiology, and Neurosurgery, Brigham and Women’s Hospital, Boston, MA, United States
| | - Coralie de Hemptinne
- Department of Neurology, Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, United States
| | - Jaimie M. Henderson
- Department of Neurosurgery, Stanford University, Stanford, CA, United States
| | - Sameer A. Sheth
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, United States
| | - Michael S. Okun
- Department of Neurology, Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, United States
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18
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Zhang D, Fu Q, Xue C, Xiao C, Sun Y, Liu W, Hu X. Characterization of Hemodynamic Alteration in Parkinson's Disease and Effect on Resting-State Connectivity. Neuroscience 2023:S0306-4522(23)00006-4. [PMID: 36642395 DOI: 10.1016/j.neuroscience.2023.01.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Revised: 12/30/2022] [Accepted: 01/03/2023] [Indexed: 01/14/2023]
Abstract
Functional magnetic resonance imaging (fMRI) is a convolution of latent neural activity and the hemodynamic response function (HRF). According to prior studies, the neurodegenerative process in idiopathic Parkinson's Disease (PD) interacts significantly with neuromuscular abnormalities. Although these underlying neuromuscular changes might influence the temporal characteristics of HRF and fMRI signals, relatively few studies have explored this possibility. We hypothesized that such alterations would engender changes in estimated functional connectivity (FC) in fMRI space compared to latent neural space. To test these theories, we calculated voxel-level HRFs by deconvolving resting-state fMRI data from PD patients (n = 61) and healthy controls (HC) (n = 47). Significant group differences in HRF (P < 0.05, Gaussian random field-corrected) were observed in several regions previously associated with PD. Subsequently, we focused on putamen-seed-based FC differences between the PD and HC groups using fMRI and latent neural signals. The results suggested that neglecting HRF variability may cultivate false-positive and false-negative FC group differences. Furthermore, HRF was related to dopamine receptor type 2 (DRD2) gene expression (P < 0.001, t = -7.06, false discover rate-corrected). Taken together, these findings reveal HRF variation and its possible underlying molecular mechanism in PD, and suggest that deconvolution could reduce the impact of HRF variation on FC group differences.
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Affiliation(s)
- Da Zhang
- Department of Radiology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Qianyi Fu
- International Laboratory for Children's Medical Imaging Research, School of Biological Sciences and Medical Engineering, Southeast University, Nanjing, Jiangsu, China
| | - Chen Xue
- Department of Radiology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Chaoyong Xiao
- Department of Radiology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China; Institute of Brain Functional Imaging, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Yu Sun
- International Laboratory for Children's Medical Imaging Research, School of Biological Sciences and Medical Engineering, Southeast University, Nanjing, Jiangsu, China; Research Centre for University of Birmingham and Southeast University, Southeast University, Nanjing, Jiangsu, China
| | - Weiguo Liu
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China.
| | - Xiao Hu
- Department of Radiology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China; Institute of Brain Functional Imaging, Nanjing Medical University, Nanjing, Jiangsu, China.
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19
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Lai Y, He N, Wei H, Deng L, Zhou H, Li J, Kaiser M, Zhang C, Li D, Sun B. Value of functional connectivity in outcome prediction for pallidal stimulation in Parkinson disease. J Neurosurg 2023; 138:27-37. [PMID: 35523258 DOI: 10.3171/2022.3.jns212732] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Accepted: 03/21/2022] [Indexed: 01/04/2023]
Abstract
OBJECTIVE Functional connectivity shows the ability to predict the outcome of subthalamic nucleus deep brain stimulation (DBS) in Parkinson disease (PD). However, evidence supporting its value in predicting the outcome of globus pallidus internus (GPi) DBS remains scarce. In this study the authors investigated patient-specific functional connectivity related to GPi DBS outcome in PD and established connectivity models for outcome prediction. METHODS The authors reviewed the outcomes of 21 patients with PD who received bilateral GPi DBS and presurgical functional MRI at the Ruijin Hospital. The connectivity profiles within cortical areas identified as relevant to DBS outcome in the literature were calculated using the intersection of the volume of tissue activated (VTA) and the local structures as the seeds. Combined with the leave-one-out cross-validation strategy, models of the optimal connectivity profile were constructed to predict outcome. RESULTS Connectivity between the pallidal areas and primary motor area, supplementary motor area (SMA), and premotor cortex was identified through the literature as related to GPi DBS outcome. The similarity between the connectivity profile within the primary motor area, SMA, pre-SMA, and premotor cortex seeding from the VTA-GPi intersection from an out-of-sample patient and the constructed in-sample optimal connectivity profile predicts GPi DBS outcome (R = 0.58, p = 0.006). The predictions on average deviated by 13.1% ± 11.3% from actual improvements. On the contrary, connectivity profiles seeding from the GPi (R = -0.12, p = 0.603), the VTA (R = 0.23, p = 0.308), the VTA outside the GPi (R = 0.12, p = 0.617), or other local structures were found not to be predictive. CONCLUSIONS The results showed that patient-specific functional connectivity seeding from the VTA-GPi intersection could help in GPi DBS outcome prediction. Reproducibility remains to be determined across centers in larger cohorts stratified by PD motor subtype.
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Affiliation(s)
- Yijie Lai
- 1Department of Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Naying He
- 2Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Hongjiang Wei
- 3Department of Biomedical Engineering, Institute for Medical Imaging Technology, Shanghai Jiao Tong University, Shanghai, China
| | - Lifu Deng
- 4Center for Cognitive Neuroscience, Duke University, Durham, North Carolina
| | - Haiyan Zhou
- 5Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jun Li
- 6School of Information Science and Technology, Shanghai Technical University, Shanghai, China
| | - Marcus Kaiser
- 7School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom; and
| | - Chencheng Zhang
- 1Department of Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- 8Shanghai Research Center for Brain Science and Brain-Inspired Intelligence, Shanghai, China
| | - Dianyou Li
- 1Department of Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Bomin Sun
- 1Department of Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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20
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Jiang Y, Yuan TS, Chen YC, Guo P, Lian TH, Liu YY, Liu W, Bai YT, Zhang Q, Zhang W, Zhang JG. Deep brain stimulation of the nucleus basalis of Meynert modulates hippocampal-frontoparietal networks in patients with advanced Alzheimer's disease. Transl Neurodegener 2022; 11:51. [PMID: 36471370 PMCID: PMC9721033 DOI: 10.1186/s40035-022-00327-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Accepted: 11/17/2022] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Deep brain stimulation (DBS) of the nucleus basalis of Meynert (NBM) has shown potential for the treatment of mild-to-moderate Alzheimer's disease (AD). However, there is little evidence of whether NBM-DBS can improve cognitive functioning in patients with advanced AD. In addition, the mechanisms underlying the modulation of brain networks remain unclear. This study was aimed to assess the cognitive function and the resting-state connectivity following NBM-DBS in patients with advanced AD. METHODS Eight patients with advanced AD underwent bilateral NBM-DBS and were followed up for 12 months. Clinical outcomes were assessed by neuropsychological examinations using the Mini-Mental State Examination (MMSE) and Alzheimer's Disease Assessment Scale. Resting-state functional magnetic resonance imaging and positron emission tomography data were also collected. RESULTS The cognitive functioning of AD patients did not change from baseline to the 12-month follow-up. Interestingly, the MMSE score indicated clinical efficacy at 1 month of follow-up. At this time point, the connectivity between the hippocampal network and frontoparietal network tended to increase in the DBS-on state compared to the DBS-off state. Additionally, the increased functional connectivity between the parahippocampal gyrus (PHG) and the parietal cortex was associated with cognitive improvement. Further dynamic functional network analysis showed that NBM-DBS increased the proportion of the PHG-related connections, which was related to improved cognitive performance. CONCLUSION The results indicated that NBM-DBS improves short-term cognitive performance in patients with advanced AD, which may be related to the modulation of multi-network connectivity patterns, and the hippocampus plays an important role within these networks. TRIAL REGISTRATION ChiCTR, ChiCTR1900022324. Registered 5 April 2019-Prospective registration. https://www.chictr.org.cn/showproj.aspx?proj=37712.
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Affiliation(s)
- Yin Jiang
- grid.24696.3f0000 0004 0369 153XDepartment of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, 100070 China
| | - Tian-Shuo Yuan
- grid.24696.3f0000 0004 0369 153XDepartment of Functional Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070 China
| | - Ying-Chuan Chen
- grid.24696.3f0000 0004 0369 153XDepartment of Functional Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070 China
| | - Peng Guo
- grid.24696.3f0000 0004 0369 153XCenter for Cognitive Neurology, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070 China
| | - Teng-Hong Lian
- grid.24696.3f0000 0004 0369 153XCenter for Cognitive Neurology, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070 China
| | - Yu-Ye Liu
- grid.24696.3f0000 0004 0369 153XDepartment of Functional Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070 China
| | - Wei Liu
- grid.24696.3f0000 0004 0369 153XDepartment of Functional Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070 China
| | - Yu-Tong Bai
- grid.24696.3f0000 0004 0369 153XDepartment of Functional Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070 China
| | - Quan Zhang
- grid.24696.3f0000 0004 0369 153XDepartment of Functional Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070 China
| | - Wei Zhang
- grid.24696.3f0000 0004 0369 153XCenter for Cognitive Neurology, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070 China
| | - Jian-Guo Zhang
- grid.24696.3f0000 0004 0369 153XDepartment of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, 100070 China ,grid.24696.3f0000 0004 0369 153XDepartment of Functional Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070 China ,grid.413259.80000 0004 0632 3337Beijing Key Laboratory of Neurostimulation, Beijing, 100070 China
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21
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Sui Y, Yu H, Zhang C, Chen Y, Jiang C, Li L. Deep brain-machine interfaces: sensing and modulating the human deep brain. Natl Sci Rev 2022; 9:nwac212. [PMID: 36644311 PMCID: PMC9834907 DOI: 10.1093/nsr/nwac212] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Revised: 10/02/2022] [Accepted: 10/04/2022] [Indexed: 01/18/2023] Open
Abstract
Different from conventional brain-machine interfaces that focus more on decoding the cerebral cortex, deep brain-machine interfaces enable interactions between external machines and deep brain structures. They sense and modulate deep brain neural activities, aiming at function restoration, device control and therapeutic improvements. In this article, we provide an overview of multiple deep brain recording and stimulation techniques that can serve as deep brain-machine interfaces. We highlight two widely used interface technologies, namely deep brain stimulation and stereotactic electroencephalography, for technical trends, clinical applications and brain connectivity research. We discuss the potential to develop closed-loop deep brain-machine interfaces and achieve more effective and applicable systems for the treatment of neurological and psychiatric disorders.
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Affiliation(s)
- Yanan Sui
- National Engineering Research Center of Neuromodulation, Tsinghua University, Beijing 100084, China
| | - Huiling Yu
- National Engineering Research Center of Neuromodulation, Tsinghua University, Beijing 100084, China
| | - Chen Zhang
- National Engineering Research Center of Neuromodulation, Tsinghua University, Beijing 100084, China
| | - Yue Chen
- National Engineering Research Center of Neuromodulation, Tsinghua University, Beijing 100084, China
| | - Changqing Jiang
- National Engineering Research Center of Neuromodulation, Tsinghua University, Beijing 100084, China
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22
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Yan H, Ren L, Yu T. Deep brain stimulation of the subthalamic nucleus for epilepsy. Acta Neurol Scand 2022; 146:798-804. [PMID: 36134756 DOI: 10.1111/ane.13707] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Accepted: 09/04/2022] [Indexed: 12/16/2022]
Abstract
Deep brain stimulation of the subthalamic nucleus (STN-DBS) is a promising palliative option for patients with refractory epilepsy. However, crucial questions remain unanswered: Which patients are the optimal candidates? How, where, and when to stimulate the STN? And what is the mechanism of STN-DBS action on epilepsy? Thus, we reviewed the clinical evidence on the antiepileptic effects of STN-DBS and its possible mechanisms on drug-resistant epilepsy, its safety, and the factors influencing stimulation outcomes. This information may guide clinical decision-making. In addition, based on the current knowledge on the effect of STN-DBS on epilepsy, we suggest research that needs to be carried out in the future.
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Affiliation(s)
- Hao Yan
- Department of Functional Neurosurgery, Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Liankun Ren
- Department of Neurology, Comprehensive Epilepsy Center of Beijing, Beijing Key Laboratory of Neuromodulation, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Tao Yu
- Department of Functional Neurosurgery, Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
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23
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解 虎, 张 建. [Neuromodulation: Past, Present, and Future]. SICHUAN DA XUE XUE BAO. YI XUE BAN = JOURNAL OF SICHUAN UNIVERSITY. MEDICAL SCIENCE EDITION 2022; 53:559-563. [PMID: 35871723 PMCID: PMC10409452 DOI: 10.12182/20220760101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Indexed: 06/15/2023]
Abstract
Neuromodulation technology is one of the medical fields currently experiencing the most rapid development, witnessing a surge in the types of modulation techniques and a constant expansion of indications. Consequently, hundreds of thousands of patients with functional neurological disorders have benefited from the advancements in the field all over the world. Nevertheless, some challenges remain, for exmaple, the lack of a thorough understanding of the mechanism of neuromodulation, the long-standing controversy over the optimal targets of neuromodulation, the lack of reliable efficacy predictors, and the cumbersome and inefficient mode of postoperative programming. We anticipate that these issues will be resolved with the continued advancement in medical technology and the gradual revelation of the neural network mechanism of brain disorders. More individualized, precise, and intelligent neuromodulation technology will be the main direction of development in the future. Herein, we reviewed and commented on the evolution of neuromodulation technology, the current status of its applications, and its prospective development.
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Affiliation(s)
- 虎涛 解
- 首都医科大学附属北京天坛医院 神经外科 (北京 100070)Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - 建国 张
- 首都医科大学附属北京天坛医院 神经外科 (北京 100070)Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
- 北京市神经外科研究所 (北京 100070)Beijing Institute of Neurosurgery, Beijing 100070, China
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24
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Jørgensen LM, Baandrup AO, Mandeville J, Glud AN, Sørensen JCH, Weikop P, Jespersen B, Hansen AE, Thomsen C, Knudsen GM. An fMRI-compatible system for targeted electrical stimulation. J Neurosci Methods 2022; 378:109659. [PMID: 35772608 DOI: 10.1016/j.jneumeth.2022.109659] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Revised: 06/19/2022] [Accepted: 06/24/2022] [Indexed: 10/17/2022]
Abstract
BACKGROUND Neuromodulation is a rapidly expanding therapeutic option considered within neuropsychiatry, pain and rehabilitation therapy. Combining electrostimulation with feedback from fMRI can provide information about the mechanisms underlying the therapeutic effects, but so far, such studies have been hampered by the lack of technology to conduct safe and accurate experiments. Here we present a system for fMRI compatible electrical stimulation, and the first proof-of-concept neuroimaging data with deep brain stimulation (DBS) in pigs obtained with the device. NEW METHOD The system consists of two modules, placed in the control and scanner room, connected by optical fiber. The system also connects to the MRI scanner to timely initiate the stimulation sequence at start of scan. We evaluated the system in four pigs with DBS in the subthalamic nucleus (STN) while we acquired BOLD responses in the STN and neocortex. RESULTS We found that the system delivered robust electrical stimuli to the implanted electrode in sync with the preprogrammed fMRI sequence. All pigs displayed a DBS-STN induced neocortical BOLD response, but none in the STN. COMPARISONS WITH EXISTING METHOD The system solves three major problems related to electric stimuli and fMRI examinations, namely preventing distortion of the fMRI signal, enabling communication that synchronize the experimental conditions, and surmounting the safety hazards caused by interference with the MRI scanner. CONCLUSIONS The fMRI compatible electrical stimulator circumvents previous problems related to electroceuticals and fMRI. The system allows flexible modifications for fMRI designs and stimulation parameters, and can be customized to electroceutical applications beyond DBS.
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Affiliation(s)
- Louise Møller Jørgensen
- Neurobiology Research Unit, Department of Neurology, Copenhagen University Hospital - Rigshospitalet, Inge Lehmannsvej 6-8, 2100 Copenhagen, Denmark; Copenhagen Spine Research Unit, Center for Rheumatology and Spine Diseases, Copenhagen University Hospital - Rigshospitalet, Valdemar Hansens Vej 13-17, 2600 Glostrup, Denmark; Department of Clinical Medicine, University of Copenhagen, Blegdamsvej 2, 2200 Copenhagen, Denmark.
| | - Anders Ohlhues Baandrup
- Research Center for Advanced Imaging, Copenhagen University Hospital - Roskilde, Sygehusvej 6, 4000 Roskilde, Denmark
| | - Joseph Mandeville
- The Martinos Center, Harvard University, Massachusetts General Hospital, 149 13(th) street, Boston, MA 02129, USA
| | - Andreas Nørgaard Glud
- Department of Neurosurgery, CENSE-group, Aarhus University Hospital - Skejby, Palle Juul-Jensens Boulevard 165, 8200 Aarhus N, Denmark
| | - Jens Christian Hedemann Sørensen
- Department of Neurosurgery, CENSE-group, Aarhus University Hospital - Skejby, Palle Juul-Jensens Boulevard 165, 8200 Aarhus N, Denmark
| | - Pia Weikop
- Center for Basic and Translational Neuroscience, Nedergaard Laboratory, Division of Glial Disease and Therapeutics, University of Copenhagen, Blegdamsvej 3, 2200 Copenhagen N, Denmark
| | - Bo Jespersen
- Department of Neurosurgery, Copenhagen University Hospital - Rigshospitalet, Blegdamsvej 9, Copenhagen, Denmark
| | - Adam Espe Hansen
- Department of Clinical Medicine, University of Copenhagen, Blegdamsvej 2, 2200 Copenhagen, Denmark; Department of Radiology, Copenhagen University Hospital - Rigshospitalet, Blegdamsvej 9, Copenhagen, Denmark; Department of Clinical Physiology, Nuclear Medicine & PET, Copenhagen University Hospital - Rigshospitalet, Blegdamsvej 9, Copenhagen, Denmark
| | - Carsten Thomsen
- Department of Clinical Medicine, University of Copenhagen, Blegdamsvej 2, 2200 Copenhagen, Denmark; Research Center for Advanced Imaging, Copenhagen University Hospital - Roskilde, Sygehusvej 6, 4000 Roskilde, Denmark
| | - Gitte Moos Knudsen
- Neurobiology Research Unit, Department of Neurology, Copenhagen University Hospital - Rigshospitalet, Inge Lehmannsvej 6-8, 2100 Copenhagen, Denmark; Department of Clinical Medicine, University of Copenhagen, Blegdamsvej 2, 2200 Copenhagen, Denmark
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Loh A, Gwun D, Chow CT, Boutet A, Tasserie J, Germann J, Santyr B, Elias G, Yamamoto K, Sarica C, Vetkas A, Zemmar A, Madhavan R, Fasano A, Lozano AM. Probing responses to deep brain stimulation with functional magnetic resonance imaging. Brain Stimul 2022; 15:683-694. [PMID: 35447378 DOI: 10.1016/j.brs.2022.03.009] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Revised: 03/24/2022] [Accepted: 03/30/2022] [Indexed: 01/29/2023] Open
Abstract
BACKGROUND Deep brain stimulation (DBS) is an established treatment for certain movement disorders and has additionally shown promise for various psychiatric, cognitive, and seizure disorders. However, the mechanisms through which stimulation exerts therapeutic effects are incompletely understood. A technique that may help to address this knowledge gap is functional magnetic resonance imaging (fMRI). This is a non-invasive imaging tool which permits the observation of DBS effects in vivo. OBJECTIVE The objective of this review was to provide a comprehensive overview of studies in which fMRI during active DBS was performed, including studied disorders, stimulated brain regions, experimental designs, and the insights gleaned from stimulation-evoked fMRI responses. METHODS We conducted a systematic review of published human studies in which fMRI was performed during active stimulation in DBS patients. The search was conducted using PubMED and MEDLINE. RESULTS The rate of fMRI DBS studies is increasing over time, with 37 studies identified overall. The median number of DBS patients per study was 10 (range = 1-67, interquartile range = 11). Studies examined fMRI responses in various disease cohorts, including Parkinson's disease (24 studies), essential tremor (3 studies), epilepsy (3 studies), obsessive-compulsive disorder (2 studies), pain (2 studies), Tourette syndrome (1 study), major depressive disorder, anorexia, and bipolar disorder (1 study), and dementia with Lewy bodies (1 study). The most commonly stimulated brain region was the subthalamic nucleus (24 studies). Studies showed that DBS modulates large-scale brain networks, and that stimulation-evoked fMRI responses are related to the site of stimulation, stimulation parameters, patient characteristics, and therapeutic outcomes. Finally, a number of studies proposed fMRI-based biomarkers for DBS treatment, highlighting ways in which fMRI could be used to confirm circuit engagement and refine DBS therapy. CONCLUSION A review of the literature reflects an exciting and expanding field, showing that the combination of DBS and fMRI represents a uniquely powerful tool for simultaneously manipulating and observing neural circuitry. Future work should focus on relatively understudied disease cohorts and stimulated regions, while focusing on the prospective validation of putative fMRI-based biomarkers.
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Affiliation(s)
- Aaron Loh
- Division of Neurosurgery, Toronto Western Hospital, University of Toronto, Canada
| | - David Gwun
- Division of Neurosurgery, Toronto Western Hospital, University of Toronto, Canada
| | - Clement T Chow
- Division of Neurosurgery, Toronto Western Hospital, University of Toronto, Canada
| | - Alexandre Boutet
- Division of Neurosurgery, Toronto Western Hospital, University of Toronto, Canada; Joint Department of Medical Imaging, University of Toronto, Toronto, Canada
| | - Jordy Tasserie
- Division of Neurosurgery, Toronto Western Hospital, University of Toronto, Canada
| | - Jürgen Germann
- Division of Neurosurgery, Toronto Western Hospital, University of Toronto, Canada
| | - Brendan Santyr
- Division of Neurosurgery, Toronto Western Hospital, University of Toronto, Canada
| | - Gavin Elias
- Division of Neurosurgery, Toronto Western Hospital, University of Toronto, Canada
| | - Kazuaki Yamamoto
- Division of Neurosurgery, Toronto Western Hospital, University of Toronto, Canada
| | - Can Sarica
- Division of Neurosurgery, Toronto Western Hospital, University of Toronto, Canada
| | - Artur Vetkas
- Division of Neurosurgery, Toronto Western Hospital, University of Toronto, Canada; Department of Neurosurgery, Tartu University Hospital, University of Tartu, Tartu, Estonia
| | - Ajmal Zemmar
- Department of Neurosurgery, Henan University School of Medicine, Zhengzhou, China; Department of Neurosurgery, University of Louisville, Louisville, KY, United States
| | | | - Alfonso Fasano
- Edmond J. Safra Program in Parkinson's Disease and Morton and Gloria Shulman Movement Disorders Clinic, Toronto Western Hospital and Division of Neurology, UHN, Division of Neurology, University of Toronto, Toronto, Ontario, Canada; Center for Advancing Neurotechnological Innovation to Application (CRANIA), Toronto, Ontario, Canada
| | - Andres M Lozano
- Division of Neurosurgery, Toronto Western Hospital, University of Toronto, Canada; Krembil Research Institute, Toronto, Ontario, Canada.
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Miao J, Tantawi M, Koa V, Zhang AB, Zhang V, Sharan A, Wu C, Matias CM. Use of Functional MRI in Deep Brain Stimulation in Parkinson's Diseases: A Systematic Review. Front Neurol 2022; 13:849918. [PMID: 35401406 PMCID: PMC8984293 DOI: 10.3389/fneur.2022.849918] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Accepted: 02/21/2022] [Indexed: 11/21/2022] Open
Abstract
Deep brain stimulation (DBS) has been used to modulate aberrant circuits associated with Parkinson's disease (PD) for decades and has shown robust therapeutic benefits. However, the mechanism of action of DBS remains incompletely understood. With technological advances, there is an emerging use of functional magnetic resonance imaging (fMRI) after DBS implantation to explore the effects of stimulation on brain networks in PD. This systematic review was designed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to summarize peer-reviewed articles published within the past 10 years in which fMRI was employed on patients with PD-DBS. Search in PubMed database provided 353 references, and screenings resulted in a total of 19 studies for qualitative synthesis regarding study designs (fMRI scan timepoints and paradigm), methodology, and PD subtypes. This review concluded that fMRI may be used in patients with PD-DBS after proper safety test; resting-state and block-based fMRI designs have been employed to explore the effects of DBS on brain networks and the mechanism of action of the DBS, respectively. With further validation of safety use of fMRI and advances in imaging techniques, fMRI may play an increasingly important role in better understanding of the mechanism of stimulation as well as in improving clinical care to provide subject-specific neuromodulation treatments.
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Affiliation(s)
- Jingya Miao
- Department of Neurosurgery, Thomas Jefferson University, Philadelphia, PA, United States
- Jefferson Integrated Magnetic Resonance Imaging Center, Department of Radiology, Thomas Jefferson University, Philadelphia, PA, United States
| | - Mohamed Tantawi
- Department of Neurosurgery, Thomas Jefferson University, Philadelphia, PA, United States
- Jefferson Integrated Magnetic Resonance Imaging Center, Department of Radiology, Thomas Jefferson University, Philadelphia, PA, United States
| | - Victoria Koa
- Department of Neurosurgery, Thomas Jefferson University, Philadelphia, PA, United States
| | - Ashley B. Zhang
- Department of Neurosurgery, Thomas Jefferson University, Philadelphia, PA, United States
| | - Veronica Zhang
- Jefferson Integrated Magnetic Resonance Imaging Center, Department of Radiology, Thomas Jefferson University, Philadelphia, PA, United States
| | - Ashwini Sharan
- Department of Neurosurgery, Thomas Jefferson University, Philadelphia, PA, United States
| | - Chengyuan Wu
- Department of Neurosurgery, Thomas Jefferson University, Philadelphia, PA, United States
- Jefferson Integrated Magnetic Resonance Imaging Center, Department of Radiology, Thomas Jefferson University, Philadelphia, PA, United States
| | - Caio M. Matias
- Department of Neurosurgery, Thomas Jefferson University, Philadelphia, PA, United States
- Jefferson Integrated Magnetic Resonance Imaging Center, Department of Radiology, Thomas Jefferson University, Philadelphia, PA, United States
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27
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Bai Y, Diao Y, Gan L, Zhuo Z, Yin Z, Hu T, Cheng D, Xie H, Wu D, Fan H, Zhang Q, Duan Y, Meng F, Liu Y, Jiang Y, Zhang J. Deep Brain Stimulation Modulates Multiple Abnormal Resting-State Network Connectivity in Patients With Parkinson’s Disease. Front Aging Neurosci 2022; 14:794987. [PMID: 35386115 PMCID: PMC8978802 DOI: 10.3389/fnagi.2022.794987] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Accepted: 02/08/2022] [Indexed: 12/12/2022] Open
Abstract
Background Deep brain stimulation (DBS) improves motor and non-motor symptoms in patients with Parkinson’s disease (PD). Researchers mainly investigated the motor networks to reveal DBS mechanisms, with few studies extending to other networks. This study aimed to investigate multi-network modulation patterns using DBS in patients with PD. Methods Twenty-four patients with PD underwent 1.5 T functional MRI (fMRI) scans in both DBS-on and DBS-off states, with twenty-seven age-matched healthy controls (HCs). Default mode, sensorimotor, salience, and left and right frontoparietal networks were identified by using the independent component analysis. Power spectra and functional connectivity of these networks were calculated. In addition, multiregional connectivity was established from 15 selected regions extracted from the abovementioned networks. Comparisons were made among groups. Finally, correlation analyses were performed between the connectivity changes and symptom improvements. Results Compared with HCs, PD-off showed abnormal power spectra and functional connectivity both within and among these networks. Some of the abovementioned abnormalities could be corrected by DBS, including increasing the power spectra in the sensorimotor network and modulating the parts of the ipsilateral functional connectivity in different regions centered in the frontoparietal network. Moreover, the DBS-induced functional connectivity changes were correlated with motor and depression improvements in patients with PD. Conclusion DBS modulated the abnormalities in multi-networks. The functional connectivity alterations were associated with motor and psychiatric improvements in PD. This study lays the foundation for large-scale brain network research on multi-network DBS modulation.
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Affiliation(s)
- Yutong Bai
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yu Diao
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Lu Gan
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Zhizheng Zhuo
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Zixiao Yin
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Tianqi Hu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Dan Cheng
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Hutao Xie
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Delong Wu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Houyou Fan
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Quan Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yunyun Duan
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Fangang Meng
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yaou Liu
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- *Correspondence: Yaou Liu,
| | - Yin Jiang
- Department of Neurosurgery, Beijing Neurosurgical Institute, Beijing, China
- Yin Jiang,
| | - Jianguo Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Department of Neurosurgery, Beijing Neurosurgical Institute, Beijing, China
- Beijing Key Laboratory of Neurostimulation, Beijing, China
- Jianguo Zhang,
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28
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Elias GJB, Germann J, Boutet A, Loh A, Li B, Pancholi A, Beyn ME, Naheed A, Bennett N, Pinto J, Bhat V, Giacobbe P, Woodside DB, Kennedy SH, Lozano AM. 3 T MRI of rapid brain activity changes driven by subcallosal cingulate deep brain stimulation. Brain 2021; 145:2214-2226. [PMID: 34919630 DOI: 10.1093/brain/awab447] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Revised: 11/08/2021] [Accepted: 11/18/2021] [Indexed: 11/14/2022] Open
Abstract
Deep brain stimulation targeting the subcallosal cingulate area (SCC-DBS), a hub with multiple axonal projections, has shown therapeutic potential for treatment-resistant mood disorders. While SCC-DBS drives long-term metabolic changes in corticolimbic circuits, the brain areas that are directly modulated by electrical stimulation of this region are not known. We used 3.0 Tesla functional MRI to map the topography of acute brain changes produced by stimulation in an initial cohort of twelve patients with fully implanted SCC-DBS devices. Four additional SCC-DBS patients were also scanned and employed as a validation cohort. Participants underwent resting state scans (n=78 acquisitions overall) during i) inactive DBS; ii) clinically optimal active DBS; iii) suboptimal active DBS. All scans were acquired within a single MRI session, each separated by a 5-minute washout period. Analysis of the amplitude of low frequency fluctuations (ALFF) in each sequence indicated that clinically optimal SCC-DBS reduced spontaneous brain activity in several areas, including bilateral dorsal anterior cingulate cortex (dACC), posterior cingulate cortex (PCC), precuneus, and left inferior parietal lobule (pBonferroni<0.0001). Stimulation-induced dACC signal reduction correlated with immediate within-session mood fluctuations, was greater at optimal versus suboptimal settings, and related to local cingulum bundle engagement. Moreover, linear modelling showed that immediate changes in dACC, PCC, and precuneus activity could predict individual long-term antidepressant improvement. A model derived from the primary cohort that incorporated ALFF changes in these three areas (along with pre-operative symptom severity) explained 55% of the variance in clinical improvement in that cohort. The same model also explained 93% of the variance in the out-of-sample validation cohort. Additionally all three brain areas exhibited significant changes in functional connectivity between active and inactive DBS states (pBonferroni<0.01). These results provide insight into the network-level mechanisms of SCC-DBS and point towards potential acute biomarkers of clinical response that could help to optimize and personalize this therapy.
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Affiliation(s)
- Gavin J B Elias
- Division of Neurosurgery, Department of Surgery, University Health Network and University of Toronto, Toronto, Canada.,Krembil Research Institute, University of Toronto, Toronto, Canada
| | - Jürgen Germann
- Division of Neurosurgery, Department of Surgery, University Health Network and University of Toronto, Toronto, Canada.,Krembil Research Institute, University of Toronto, Toronto, Canada
| | - Alexandre Boutet
- Division of Neurosurgery, Department of Surgery, University Health Network and University of Toronto, Toronto, Canada.,Krembil Research Institute, University of Toronto, Toronto, Canada.,Joint Department of Medical Imaging, University of Toronto, Toronto, Canada
| | - Aaron Loh
- Division of Neurosurgery, Department of Surgery, University Health Network and University of Toronto, Toronto, Canada.,Krembil Research Institute, University of Toronto, Toronto, Canada
| | - Bryan Li
- Joint Department of Medical Imaging, University of Toronto, Toronto, Canada
| | - Aditya Pancholi
- Division of Neurosurgery, Department of Surgery, University Health Network and University of Toronto, Toronto, Canada
| | - Michelle E Beyn
- Division of Neurosurgery, Department of Surgery, University Health Network and University of Toronto, Toronto, Canada
| | - Asma Naheed
- Joint Department of Medical Imaging, University of Toronto, Toronto, Canada
| | - Nicole Bennett
- Joint Department of Medical Imaging, University of Toronto, Toronto, Canada
| | - Jessica Pinto
- Joint Department of Medical Imaging, University of Toronto, Toronto, Canada
| | - Venkat Bhat
- Department of Psychiatry, University Health Network and University of Toronto, Toronto, Canada
| | - Peter Giacobbe
- Department of Psychiatry, Sunnybrook Health Sciences Centre and University of Toronto, Toronto, Canada
| | - D Blake Woodside
- Department of Psychiatry, University Health Network and University of Toronto, Toronto, Canada
| | - Sidney H Kennedy
- Krembil Research Institute, University of Toronto, Toronto, Canada.,Department of Psychiatry, University Health Network and University of Toronto, Toronto, Canada
| | - Andres M Lozano
- Division of Neurosurgery, Department of Surgery, University Health Network and University of Toronto, Toronto, Canada.,Krembil Research Institute, University of Toronto, Toronto, Canada
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Zhang Y, Le S, Li H, Ji B, Wang MH, Tao J, Liang JQ, Zhang XY, Kang XY. MRI magnetic compatible electrical neural interface: From materials to application. Biosens Bioelectron 2021; 194:113592. [PMID: 34507098 DOI: 10.1016/j.bios.2021.113592] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2021] [Accepted: 08/24/2021] [Indexed: 01/07/2023]
Abstract
Neural electrical interfaces are important tools for local neural stimulation and recording, which potentially have wide application in the diagnosis and treatment of neural diseases, as well as in the transmission of neural activity for brain-computer interface (BCI) systems. At the same time, magnetic resonance imaging (MRI) is one of the effective and non-invasive techniques for recording whole-brain signals, providing details of brain structures and also activation pattern maps. Simultaneous recording of extracellular neural signals and MRI combines two expressions of the same neural activity and is believed to be of great importance for the understanding of brain function. However, this combination makes requests on the magnetic and electronic performance of neural interface devices. MRI-compatibility refers here to a technological approach to simultaneous MRI and electrode recording or stimulation without artifacts in imaging. Trade-offs between materials magnetic susceptibility selection and electrical function should be considered. Herein, prominent trends in selecting materials of suitable magnetic properties are analyzed and material design, function and application of neural interfaces are outlined together with the remaining challenge to fabricate MRI-compatible neural interface.
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Affiliation(s)
- Yuan Zhang
- Laboratory for Neural Interface and Brain Computer Interface, Institute of AI and Robotics, Academy for Engineering and Technology, FUDAN University, 220 Handan Rd., Yangpu District, Shanghai, 200433, China; Ji Hua Laboratory, 28 Island Ring South Rd., Foshan City, 528200, China; Engineering Research Center of AI & Robotics, Ministry of Education, Shanghai Engineering Research Center of AI & Robotics, MOE Frontiers Center for Brain Science, Shanghai 200433, China; Research Center for Intelligent Sensing, Zhejiang Lab, Hangzhou, 311100, China; Yiwu Research Institute of Fudan University, Chengbei Road, Yiwu City, 322000, Zhejiang, China
| | - Song Le
- Laboratory for Neural Interface and Brain Computer Interface, Institute of AI and Robotics, Academy for Engineering and Technology, FUDAN University, 220 Handan Rd., Yangpu District, Shanghai, 200433, China; Ji Hua Laboratory, 28 Island Ring South Rd., Foshan City, 528200, China; Engineering Research Center of AI & Robotics, Ministry of Education, Shanghai Engineering Research Center of AI & Robotics, MOE Frontiers Center for Brain Science, Shanghai 200433, China; Research Center for Intelligent Sensing, Zhejiang Lab, Hangzhou, 311100, China; Yiwu Research Institute of Fudan University, Chengbei Road, Yiwu City, 322000, Zhejiang, China
| | - Hui Li
- Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 1068 Xueyuan Avenue, Shenzhen University Town, Shenzhen, 518055, China
| | - Bowen Ji
- Unmanned System Research Institute; Ministry of Education Key Laboratory of Micro/Nano Systems for Aerospace, School of Mechanical Engineering, Northwestern Polytechnical University, Xi'an, 710072, China
| | - Ming-Hao Wang
- The MOE Engineering Research Center of Smart Microsensors and Microsystems, School of Electronics & Information, Hangzhou Dianzi University, Hangzhou, 310018, China
| | - Jin Tao
- State Key Laboratory of Applied Optics, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, Jilin, 130033, China
| | - Jing-Qiu Liang
- State Key Laboratory of Applied Optics, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, Jilin, 130033, China
| | - Xiao-Yong Zhang
- Institute of Science and Technology for Brain-inspired Intelligence, FUDAN University, Shanghai, 200433, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai 200433, China
| | - Xiao-Yang Kang
- Laboratory for Neural Interface and Brain Computer Interface, Institute of AI and Robotics, Academy for Engineering and Technology, FUDAN University, 220 Handan Rd., Yangpu District, Shanghai, 200433, China; Ji Hua Laboratory, 28 Island Ring South Rd., Foshan City, 528200, China; Engineering Research Center of AI & Robotics, Ministry of Education, Shanghai Engineering Research Center of AI & Robotics, MOE Frontiers Center for Brain Science, Shanghai 200433, China; Research Center for Intelligent Sensing, Zhejiang Lab, Hangzhou, 311100, China; Yiwu Research Institute of Fudan University, Chengbei Road, Yiwu City, 322000, Zhejiang, China.
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Baldermann JC, Schüller T, Kohl S, Voon V, Li N, Hollunder B, Figee M, Haber SN, Sheth SA, Mosley PE, Huys D, Johnson KA, Butson C, Ackermans L, Bouwens van der Vlis T, Leentjens AFG, Barbe M, Visser-Vandewalle V, Kuhn J, Horn A. Connectomic Deep Brain Stimulation for Obsessive-Compulsive Disorder. Biol Psychiatry 2021; 90:678-688. [PMID: 34482949 DOI: 10.1016/j.biopsych.2021.07.010] [Citation(s) in RCA: 49] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Revised: 06/29/2021] [Accepted: 07/01/2021] [Indexed: 01/17/2023]
Abstract
Obsessive-compulsive disorder is among the most disabling psychiatric disorders. Although deep brain stimulation is considered an effective treatment, its use in clinical practice is not fully established. This is, at least in part, due to ambiguity about the best suited target and insufficient knowledge about underlying mechanisms. Recent advances suggest that changes in broader brain networks are responsible for improvement of obsessions and compulsions, rather than local impact at the stimulation site. These findings were fueled by innovative methodological approaches using brain connectivity analyses in combination with neuromodulatory interventions. Such a connectomic approach for neuromodulation constitutes an integrative account that aims to characterize optimal target networks. In this critical review, we integrate findings from connectomic studies and deep brain stimulation interventions to characterize a neural network presumably effective in reducing obsessions and compulsions. To this end, we scrutinize methodologies and seemingly conflicting findings with the aim to merge observations to identify common and diverse pathways for treating obsessive-compulsive disorder. Ultimately, we propose a unified network that-when modulated by means of cortical or subcortical interventions-alleviates obsessive-compulsive symptoms.
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Affiliation(s)
- Juan Carlos Baldermann
- Department of Neurology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany; Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.
| | - Thomas Schüller
- Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Sina Kohl
- Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Valerie Voon
- Department of Psychiatry, Cambridge University, Cambridge, United Kingdom
| | - Ningfei Li
- Department of Neurology, Movement Disorders and Neuromodulation Section, Charité - University Medicine Berlin, Berlin, Germany
| | - Barbara Hollunder
- Department of Neurology, Movement Disorders and Neuromodulation Section, Charité - University Medicine Berlin, Berlin, Germany; Einstein Center for Neurosciences, Charité - University Medicine Berlin, Berlin, Germany; Faculty of Philosophy, Humboldt University of Berlin, Berlin School of Mind and Brain, Berlin, Germany
| | - Martijn Figee
- Department of Psychiatry, Mount Sinai Hospital, New York, New York
| | - Suzanne N Haber
- Department of Pharmacology and Physiology, University of Rochester School of Medicine, Rochester, New York; Basic Neuroscience Division, Harvard Medical School, McLean Hospital, Belmont, Massachusetts
| | - Sameer A Sheth
- Department of Neurosurgery, Baylor College of Medicine, Houston, Texas
| | - Philip E Mosley
- Systems Neuroscience Group, QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia; Queensland Brain Institute, University of Queensland, St Lucia, Queensland, Australia
| | - Daniel Huys
- Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Kara A Johnson
- Department of Neurology, Norman Fixel Institute for Neurological Diseases, University of Florida, Gainesville, Florida
| | - Christopher Butson
- Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, Utah; Department of Biomedical Engineering, University of Utah, Salt Lake City, Utah
| | - Linda Ackermans
- School of Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands
| | | | - Albert F G Leentjens
- School of Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands
| | - Michael Barbe
- Department of Neurology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Veerle Visser-Vandewalle
- Department of Stereotactic and Functional Neurosurgery, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Jens Kuhn
- Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany; Department of Psychiatry, Psychotherapy and Psychosomatic, Johanniter Hospital Oberhausen, Oberhausen, Germany
| | - Andreas Horn
- Department of Neurology, Movement Disorders and Neuromodulation Section, Charité - University Medicine Berlin, Berlin, Germany
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31
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Li Z, Liu C, Wang Q, Liang K, Han C, Qiao H, Zhang J, Meng F. Abnormal Functional Brain Network in Parkinson's Disease and the Effect of Acute Deep Brain Stimulation. Front Neurol 2021; 12:715455. [PMID: 34721258 PMCID: PMC8551554 DOI: 10.3389/fneur.2021.715455] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Accepted: 08/26/2021] [Indexed: 01/21/2023] Open
Abstract
Objective: The objective of this study was to use functional connectivity and graphic indicators to investigate the abnormal brain network topological characteristics caused by Parkinson's disease (PD) and the effect of acute deep brain stimulation (DBS) on those characteristics in patients with PD. Methods: We recorded high-density EEG (256 channels) data from 21 healthy controls (HC) and 20 patients with PD who were in the DBS-OFF state and DBS-ON state during the resting state with eyes closed. A high-density EEG source connectivity method was used to identify functional brain networks. Power spectral density (PSD) analysis was compared between the groups. Functional connectivity was calculated for 68 brain regions in the theta (4-8 Hz), alpha (8-13 Hz), beta1 (13-20 Hz), and beta2 (20-30 Hz) frequency bands. Network estimates were measured at both the global (network topology) and local (inter-regional connection) levels. Results: Compared with HC, PSD was significantly increased in the theta (p = 0.003) frequency band and was decreased in the beta1 (p = 0.009) and beta2 (p = 0.04) frequency bands in patients with PD. However, there were no differences in any frequency bands between patients with PD with DBS-OFF and DBS-ON. The clustering coefficient and local efficiency of patients with PD showed a significant decrease in the alpha, beta1, and beta2 frequency bands (p < 0.001). In addition, edgewise statistics showed a significant difference between the HC and patients with PD in all analyzed frequency bands (p < 0.005). However, there were no significant differences between the DBS-OFF state and DBS-ON state in the brain network, except for the functional connectivity in the beta2 frequency band (p < 0.05). Conclusion: Compared with HC, patients with PD showed the following characteristics: slowed EEG background activity, decreased clustering coefficient and local efficiency of the brain network, as well as both increased and decreased functional connectivity between different brain areas. Acute DBS induces a local response of the brain network in patients with PD, mainly showing decreased functional connectivity in a few brain regions in the beta2 frequency band.
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Affiliation(s)
- Zhibao Li
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Chong Liu
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Qiao Wang
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Kun Liang
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Chunlei Han
- Department of Functional Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Neurostimulation, Beijing, China
| | - Hui Qiao
- Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Jianguo Zhang
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.,Department of Functional Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Neurostimulation, Beijing, China
| | - Fangang Meng
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.,Department of Functional Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Neurostimulation, Beijing, China.,Chinese Institute for Brain Research, Beijing (CIBR), Beijing, China
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32
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Sun H, He Y, Cao H. Functional magnetic resonance imaging research in China. CNS Neurosci Ther 2021; 27:1259-1267. [PMID: 34492160 PMCID: PMC8504522 DOI: 10.1111/cns.13725] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Revised: 08/18/2021] [Accepted: 08/20/2021] [Indexed: 01/11/2023] Open
Abstract
Functional magnetic resonance imaging (fMRI) non-invasively measures the activity of the human brain and provides a unique technological tool for investigating aspects of the human brain including cognition, development, and disorders. As one of the main funding agencies for basic research in China, the National Natural Scientific Foundation of China (NSFC) has initiated various research programs during the last two decades that are related to fMRI research. In this review, we collected and analyzed the metadata of the projects and published studies in research fields using fMRI that were funded by the NSFC. We observed a trend of increasing funding amounts from the NSFC for fMRI research, typically from the General Program and Key Program. Leading research institutes from economically developed municipalities and provinces received the most support and formed close collaboration relationships. Finally, we reviewed several representative achievements from research institutions in china, involving data analysis methods, brain connectomes, and computational platforms in addition to their applications in brain disorders.
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Affiliation(s)
- Hongzan Sun
- Department of RadiologyShengjing Hospital of China Medical UniversityShenyangChina
| | - Yong He
- State Key Laboratory of Cognitive Neuroscience and LearningBeijing Normal UniversityBeijingChina
- Beijing Key Laboratory of Brain Imaging and ConnectomicsBeijing Normal UniversityBeijingChina
- IDG/McGovern Institute for Brain ResearchBeijing Normal UniversityBeijingChina
- Chinese Institute for Brain ResearchBeijingChina
| | - Heqi Cao
- Department of Health SciencesNational Natural Science Foundation of ChinaBeijingChina
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33
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Bijsterbosch JD, Valk SL, Wang D, Glasser MF. Recent developments in representations of the connectome. Neuroimage 2021; 243:118533. [PMID: 34469814 PMCID: PMC8842504 DOI: 10.1016/j.neuroimage.2021.118533] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Revised: 07/16/2021] [Accepted: 08/28/2021] [Indexed: 02/03/2023] Open
Abstract
Research into the human connectome (i.e., all connections in the human brain) with the use of resting state functional MRI has rapidly increased in popularity in recent years, especially with the growing availability of large-scale neuroimaging datasets. The goal of this review article is to describe innovations in functional connectome representations that have come about in the past 8 years, since the 2013 NeuroImage special issue on 'Mapping the Connectome'. In the period, research has shifted from group-level brain parcellations towards the characterization of the individualized connectome and of relationships between individual connectomic differences and behavioral/clinical variation. Achieving subject-specific accuracy in parcel boundaries while retaining cross-subject correspondence is challenging, and a variety of different approaches are being developed to meet this challenge, including improved alignment, improved noise reduction, and robust group-to-subject mapping approaches. Beyond the interest in the individualized connectome, new representations of the data are being studied to complement the traditional parcellated connectome representation (i.e., pairwise connections between distinct brain regions), such as methods that capture overlapping and smoothly varying patterns of connectivity ('gradients'). These different connectome representations offer complimentary insights into the inherent functional organization of the brain, but challenges for functional connectome research remain. Interpretability will be improved by future research towards gaining insights into the neural mechanisms underlying connectome observations obtained from functional MRI. Validation studies comparing different connectome representations are also needed to build consensus and confidence to proceed with clinical trials that may produce meaningful clinical translation of connectome insights.
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Affiliation(s)
- Janine D Bijsterbosch
- Department of Radiology, Washington University School of Medicine, Saint Louis, MO, 63110, USA.
| | - Sofie L Valk
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; INM-7, Forschungszentrum Jülich, Jülich, Germany
| | - Danhong Wang
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | - Matthew F Glasser
- Department of Radiology, Washington University School of Medicine, Saint Louis, MO, 63110, USA; Department of Neuroscience, Washington University School of Medicine, Saint Louis, Missouri, 63110, USA
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34
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Zhang C, Lai Y, Li J, He N, Liu Y, Li Y, Li H, Wei H, Yan F, Horn A, Li D, Sun B. Subthalamic and Pallidal Stimulations in Patients with Parkinson's Disease: Common and Dissociable Connections. Ann Neurol 2021; 90:670-682. [PMID: 34390280 PMCID: PMC9292442 DOI: 10.1002/ana.26199] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Revised: 08/10/2021] [Accepted: 08/12/2021] [Indexed: 12/25/2022]
Abstract
OBJECTIVE The subthalamic nucleus (STN) and internal globus pallidus (GPi) are the most effective targets in deep brain stimulation (DBS) for Parkinson's disease (PD). However, the common and specific effects on brain connectivity of stimulating the 2 nuclei remain unclear. METHODS Patients with PD receiving STN-DBS (n = 27, 6 women, mean age 64.8 years) or GPi-DBS (n = 28, 13 women, mean age 64.6 years) were recruited for resting-state functional magnetic resonance imaging to assess the effects of STN-DBS and GPi-DBS on brain functional dynamics. RESULTS The functional connectivity both between the somatosensory-motor cortices and thalamus, and between the somatosensory-motor cortices and cerebellum decreased in the DBS-on state compared with the off state (p < 0.05). The changes in thalamocortical connectivity correlated with DBS-induced motor improvement (p < 0.05) and were negatively correlated with the normalized intersection volume of tissues activated at both DBS targets (p < 0.05). STN-DBS modulated functional connectivity among a wider range of brain areas than GPi-DBS (p = 0.009). Notably, only STN-DBS affected connectivity between the postcentral gyrus and cerebellar vermis (p < 0.001) and between the somatomotor and visual networks (p < 0.001). INTERPRETATION Our findings highlight common alterations in the motor pathway and its relationship with the motor improvement induced by both STN- and GPi-DBS. The effects on cortico-cerebellar and somatomotor-visual functional connectivity differed between groups, suggesting differentiated neural modulation of the 2 target sites. Our results provide mechanistic insight and yield the potential to refine target selection strategies for focal brain stimulation in PD. ANN NEUROL 2021.
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Affiliation(s)
- Chencheng Zhang
- Department of Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.,Center for Functional Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.,Shanghai Research Center for Brain Science and Brain-Inspired Intelligence, Shanghai, China.,Department of Anatomy and Physiology, Collaborative Innovation Centre for Brain Science, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yijie Lai
- Department of Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.,Center for Functional Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jun Li
- Department of Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.,Center for Functional Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.,School of Information Science and Technology, Shanghai Tech University, Shanghai, China
| | - Naying He
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yu Liu
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yan Li
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Hongyang Li
- Department of Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.,Center for Functional Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Hongjiang Wei
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.,Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai, China
| | - Fuhua Yan
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Andreas Horn
- Department of Neurology, Movement Disorders and Neuromodulation Section, Charité - University Medicine Berlin, Berlin, Germany
| | - Dianyou Li
- Department of Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.,Center for Functional Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Bomin Sun
- Department of Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.,Center for Functional Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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35
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Tiefe Hirnstimulation: Das ganze Gehirn im Blick. FORTSCHRITTE DER NEUROLOGIE-PSYCHIATRIE 2021. [DOI: 10.1055/a-1353-1575] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
Die neuromodulatorischen Effekte der tiefen Hirnstimulation (DBS) auf
große Gehirnnetzwerke sind noch weitgehend unklar. Bislang fehlten
Techniken für die Darstellung der DBS-induzierten Aktivität
über das gesamte Gehirn hinweg. In China ermöglichte jetzt
ein neuer Stimulator, der mit der 3-Tesla-Magnetresonanztomographie (3T-MRT)
kompatibel ist, eine solche Untersuchung.
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36
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Li Z, Ren G, Liu C, Wang Q, Liang K, Han C, Qiao H, Zhang J, Wang Q, Meng F. Dysfunctional Brain Dynamics of Parkinson's Disease and the Effect of Acute Deep Brain Stimulation. Front Neurosci 2021; 15:697909. [PMID: 34354564 PMCID: PMC8331088 DOI: 10.3389/fnins.2021.697909] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2021] [Accepted: 06/09/2021] [Indexed: 12/25/2022] Open
Abstract
Background: Parkinson's disease (PD) is the second most common neurodegenerative disorder after Alzheimer's disease, and deep brain stimulation (DBS) can effectively alleviate PD symptoms. Although previous studies have detected network features of PD and DBS, few studies have considered their dynamic characteristics. Objective: We tested two hypotheses. (1) Reduced brain dynamics, as evidenced by slowed microstate dynamic change, is a characteristic of PD and is related to the movement disorders of patients with PD. (2) Therapeutic acute DBS can partially reverse slow brain dynamics in PD to healthy levels. Methods: We used electroencephalography (EEG) microstate analysis based on high density (256-channel) EEG to detect the effects of PD and DBS on brain dynamic changes on a sub-second timescale. We compared 21 healthy controls (HCs) with 20 patients with PD who were in either DBS-OFF or DBS-ON states. Assessment of movement disorder using the Unified Parkinson's Disease Rating Scale III was correlated with microstate parameters. Results: Compared with HCs, patients with PD displayed a longer mean microstate duration with reduced occurrence per second, which were significantly associated with movement disorders. In patients with PD, some parameters of microstate analysis were restored toward healthy levels after DBS. Conclusions: Resting-state EEG microstate analysis is an important tool for investigating brain dynamic changes in PD and DBS. PD can slow down brain dynamic change, and therapeutic acute DBS can partially reverse this change toward a healthy level.
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Affiliation(s)
- Zhibao Li
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Guoping Ren
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Chong Liu
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Qiao Wang
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Kun Liang
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Chunlei Han
- Department of Functional Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Neurostimulation, Beijing Neurosurgical Institute, Beijing, China
| | - Hui Qiao
- Neuroelectrophysiology Room, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Jianguo Zhang
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.,Department of Functional Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Neurostimulation, Beijing Neurosurgical Institute, Beijing, China
| | - Qun Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Fangang Meng
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.,Department of Functional Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Neurostimulation, Beijing Neurosurgical Institute, Beijing, China.,Chinese Institute for Brain Research Beijing (CIBR), Beijing, China
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37
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Arbuthnott GW. An Introspective Approach: A Lifetime of Parkinson's Disease Research and Not Much to Show for it Yet? Cells 2021; 10:cells10030513. [PMID: 33670933 PMCID: PMC7997292 DOI: 10.3390/cells10030513] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Revised: 02/23/2021] [Accepted: 02/23/2021] [Indexed: 11/16/2022] Open
Abstract
I feel part of a massive effort to understand what is wrong with motor systems in the brain relating to Parkinson’s disease. Today, the symptoms of the disease can be modified slightly, but dopamine neurons still die; the disease progression continues inexorably. Maybe the next research phase will bring the power of modern genetics to bear on halting, or better, preventing cell death. The arrival of accessible human neuron assemblies in organoids perhaps will provide a better access to the processes underlying neuronal demise.
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Affiliation(s)
- Gordon W Arbuthnott
- Brain Mechanisms for Behaviour Unit, Okinawa Institute of Science and Technology, Graduate University, Onna-son, Okinawa 904-0495, Japan
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38
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Measuring Subthalamic Nucleus Volume of Parkinson's Patients and Evaluating Its Relationship with Clinical Scales at Pre- and Postdeep Brain Stimulation Treatment: A Magnetic Resonance Imaging Study. BIOMED RESEARCH INTERNATIONAL 2021; 2021:6646416. [PMID: 33708991 PMCID: PMC7932794 DOI: 10.1155/2021/6646416] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/11/2020] [Revised: 02/09/2021] [Accepted: 02/19/2021] [Indexed: 11/17/2022]
Abstract
This study investigated potential imaging biomarkers for predicting the efficacy of deep brain stimulation (DBS) of the subthalamic nucleus (STN) in patients with Parkinson's disease (PD). A total of 59 PD patients and 50 healthy control subjects underwent high-resolution 3-dimensional T1-weighted brain magnetic resonance imaging. Bilateral STN volumes were compared between the 2 groups, and a correlation analysis was performed to assess the relationship between bilateral STN volumes or intracranial volume (ICV) and pre- or postoperative clinical scale scores. The results showed that the left STN volume differed significantly between PD patients and controls. In patients, the left STN volume was negatively correlated with pre- and postoperative quality of life scores and positively correlated with Mini-mental State Examination (MMSE) and Montreal Cognitive Assessment scores; ICV was also positively correlated with the MMSE score. These findings indicate that changes in the left STN volume are a useful biomarker for evaluating the clinical outcome of PD patients following DBS.
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39
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Sui Y, Tian Y, Ko WKD, Wang Z, Jia F, Horn A, De Ridder D, Choi KS, Bari AA, Wang S, Hamani C, Baker KB, Machado AG, Aziz TZ, Fonoff ET, Kühn AA, Bergman H, Sanger T, Liu H, Haber SN, Li L. Deep Brain Stimulation Initiative: Toward Innovative Technology, New Disease Indications, and Approaches to Current and Future Clinical Challenges in Neuromodulation Therapy. Front Neurol 2021; 11:597451. [PMID: 33584498 PMCID: PMC7876228 DOI: 10.3389/fneur.2020.597451] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2020] [Accepted: 11/23/2020] [Indexed: 01/17/2023] Open
Abstract
Deep brain stimulation (DBS) is one of the most important clinical therapies for neurological disorders. DBS also has great potential to become a great tool for clinical neuroscience research. Recently, the National Engineering Laboratory for Neuromodulation at Tsinghua University held an international Deep Brain Stimulation Initiative workshop to discuss the cutting-edge technological achievements and clinical applications of DBS. We specifically addressed new clinical approaches and challenges in DBS for movement disorders (Parkinson's disease and dystonia), clinical application toward neurorehabilitation for stroke, and the progress and challenges toward DBS for neuropsychiatric disorders. This review highlighted key developments in (1) neuroimaging, with advancements in 3-Tesla magnetic resonance imaging DBS compatibility for exploration of brain network mechanisms; (2) novel DBS recording capabilities for uncovering disease pathophysiology; and (3) overcoming global healthcare burdens with online-based DBS programming technology for connecting patient communities. The successful event marks a milestone for global collaborative opportunities in clinical development of neuromodulation to treat major neurological disorders.
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Affiliation(s)
- Yanan Sui
- National Engineering Laboratory for Neuromodulation, Tsinghua University, Beijing, China
| | - Ye Tian
- National Engineering Laboratory for Neuromodulation, Tsinghua University, Beijing, China
| | - Wai Kin Daniel Ko
- National Engineering Laboratory for Neuromodulation, Tsinghua University, Beijing, China
| | - Zhiyan Wang
- National Engineering Laboratory for Neuromodulation, Tsinghua University, Beijing, China
| | - Fumin Jia
- National Engineering Laboratory for Neuromodulation, Tsinghua University, Beijing, China
| | - Andreas Horn
- Charité, Department of Neurology, Movement Disorders and Neuromodulation Unit, University Medicine Berlin, Berlin, Germany
| | - Dirk De Ridder
- Section of Neurosurgery, Department of Surgical Sciences, Dunedin School of Medicine, University of Otago, Dunedin, New Zealand
| | - Ki Sueng Choi
- Department of Psychiatry and Behavioural Science, Emory University, Atlanta, GA, United States.,Department of Radiology, Mount Sinai School of Medicine, New York, NY, United States.,Department of Neurosurgery, Mount Sinai School of Medicine, New York, NY, United States
| | - Ausaf A Bari
- Department of Neurosurgery, University of California, Los Angeles, Los Angeles, CA, United States
| | - Shouyan Wang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Clement Hamani
- Harquail Centre for Neuromodulation, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Kenneth B Baker
- Department of Neurosciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, United States.,Neurological Institute, Cleveland Clinic, Cleveland, OH, United States
| | - Andre G Machado
- Department of Neurosciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, United States.,Neurological Institute, Cleveland Clinic, Cleveland, OH, United States
| | - Tipu Z Aziz
- Department of Neurosurgery, John Radcliffe Hospital, Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom
| | - Erich Talamoni Fonoff
- Department of Neurology, University of São Paulo Medical School, São Paulo, Brazil.,Hospital Sírio-Libanês and Hospital Albert Einstein, São Paulo, Brazil
| | - Andrea A Kühn
- Charité, Department of Neurology, Movement Disorders and Neuromodulation Unit, University Medicine Berlin, Berlin, Germany
| | - Hagai Bergman
- Department of Medical Neurobiology (Physiology), Institute of Medical Research-Israel-Canada (IMRIC), Faculty of Medicine, Jerusalem, Israel.,The Edmond and Lily Safra Center for Brain Research (ELSC), The Hebrew University and Department of Neurosurgery, Hadassah Medical Center, Hebrew University, Jerusalem, Israel
| | - Terence Sanger
- University of Southern California, Children's Hospital Los Angeles, Los Angeles, CA, United States
| | - Hesheng Liu
- Department of Neuroscience, College of Medicine, Medical University of South Carolina, Charleston, SC, United States
| | - Suzanne N Haber
- Department of Pharmacology and Physiology, University of Rochester School of Medicine & Dentistry, Rochester, NY, United States.,McLean Hospital and Harvard Medical School, Belmont, MA, United States
| | - Luming Li
- National Engineering Laboratory for Neuromodulation, Tsinghua University, Beijing, China
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