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Chen J, Fan Y, Wei W, Wang L, Wang X, Fan F, Jia Z, Li M, Wang J, Zou Q, Chen B, Lv Y. Repetitive transcranial magnetic stimulation modulates cortical-subcortical connectivity in sensorimotor network. Eur J Neurosci 2021; 55:227-243. [PMID: 34905661 DOI: 10.1111/ejn.15571] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2021] [Revised: 12/09/2021] [Accepted: 12/09/2021] [Indexed: 11/30/2022]
Abstract
Repetitive transcranial magnetic stimulation (rTMS) holds the ability to modulate the connectivity within the stimulated network. However, whether and how the rTMS targeted over the primary motor cortex (M1) could affect the connectivity within the sensorimotor network (SMN) is not fully elucidated. Hence, in this study, we investigated the after-effects of rTMS over left M1 at different frequencies on connectivity within SMN. Forty-five healthy participants were recruited and randomly divided into three groups according to rTMS frequencies (high-frequency [HF], 3 Hz; low-frequency [LF], 1 Hz; and SHAM). Participants received 1-Hz, 3-Hz or sham stimulation and underwent two functional magnetic resonance imaging (fMRI) scanning sessions before and after rTMS intervention. Using resting-state functional connectivity (FC) approach, we found that high- and low-frequency rTMS had opposing effects on FC within the SMN, especially for connectivity with subcortical regions (i.e., putamen, thalamus and cerebellum). Specifically, the reductions in connectivity between cortical and subcortical regions within cortico-basal ganglia thalamo-cortical circuits and the cognitive loop of cerebellum, and increased connectivity between cortical and subdivisions within the sensorimotor loop of cerebellum were observed after high-frequency rTMS intervention, whereas the thalamus and cognitive cerebellum subdivisions exhibited increased connectivity, and sensorimotor cerebellum subdivisions showed decreased connectivity with stimulated target after low-frequency stimulation. Collectively, these findings demonstrated the alterations of connectivity within SMN after rTMS intervention at different frequencies and may help to understand the mechanisms of rTMS treatment for movement disorders associated with deficits in subcortical regions such as Parkinson's disease, Huntington's disease and Tourette's syndrome.
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Affiliation(s)
- Jing Chen
- Center for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, China.,Institute of Psychological Science, Hangzhou Normal University, Hangzhou, China.,Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou, China
| | - Yanzi Fan
- Center for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, China.,Institute of Psychological Science, Hangzhou Normal University, Hangzhou, China.,Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou, China
| | - Wei Wei
- Center for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, China.,Institute of Psychological Science, Hangzhou Normal University, Hangzhou, China.,Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou, China
| | - Luoyu Wang
- Center for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, China.,Institute of Psychological Science, Hangzhou Normal University, Hangzhou, China.,Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou, China
| | - Xiaoyu Wang
- Department of Psychology, Technische Universität Dresden, Dresden, Germany
| | - Fengmei Fan
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, China
| | - Zejuan Jia
- Shijiazhuang Hospital of Traditional Chinese Medicine, Shijiazhuang, China
| | - Mengting Li
- School of Teacher Education, Zhejiang Normal University, Jinhua, China
| | - Jinhui Wang
- Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou, China
| | - Qihong Zou
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
| | - Bing Chen
- School of Education, Hangzhou Normal University, Hangzhou, China
| | - Yating Lv
- Center for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, China.,Institute of Psychological Science, Hangzhou Normal University, Hangzhou, China.,Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou, China
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Gatto RG, Weissmann C. Diffusion Tensor Imaging in Preclinical and Human Studies of Huntington's Disease: What Have we Learned so Far? Curr Med Imaging 2020; 15:521-542. [PMID: 32008561 DOI: 10.2174/1573405614666181115113400] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2018] [Revised: 10/23/2018] [Accepted: 10/26/2018] [Indexed: 12/13/2022]
Abstract
BACKGROUND Huntington's Disease is an irreversible neurodegenerative disease characterized by the progressive deterioration of specific brain nerve cells. The current evaluation of cellular and physiological events in patients with HD relies on the development of transgenic animal models. To explore such events in vivo, diffusion tensor imaging has been developed to examine the early macro and microstructural changes in brain tissue. However, the gap in diffusion tensor imaging findings between animal models and clinical studies and the lack of microstructural confirmation by histological methods has questioned the validity of this method. OBJECTIVE This review explores white and grey matter ultrastructural changes associated to diffusion tensor imaging, as well as similarities and differences between preclinical and clinical Huntington's Disease studies. METHODS A comprehensive review of the literature using online-resources was performed (Pub- Med search). RESULTS Similar changes in fractional anisotropy as well as axial, radial and mean diffusivities were observed in white matter tracts across clinical and animal studies. However, comparative diffusion alterations in different grey matter structures were inconsistent between clinical and animal studies. CONCLUSION Diffusion tensor imaging can be related to specific structural anomalies in specific cellular populations. However, some differences between animal and clinical studies could derive from the contrasting neuroanatomy or connectivity across species. Such differences should be considered before generalizing preclinical results into the clinical practice. Moreover, current limitations of this technique to accurately represent complex multicellular events at the single micro scale are real. Future work applying complex diffusion models should be considered.
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Affiliation(s)
- Rodolfo Gabriel Gatto
- Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, 60607, United States
| | - Carina Weissmann
- Insituto de Fisiología Biologia Molecular y Neurociencias-IFIBYNE-CONICET, University of Buenos Aires, Buenos Aires, Argentina
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Hu Y, Ji G, Li G, Manza P, Zhang W, Wang J, Lv G, He Y, Zhang Z, Yuan K, von Deneen KM, Chen A, Cui G, Wang H, Wiers CE, Volkow ND, Nie Y, Zhang Y, Wang GJ. Brain Connectivity, and Hormonal and Behavioral Correlates of Sustained Weight Loss in Obese Patients after Laparoscopic Sleeve Gastrectomy. Cereb Cortex 2020; 31:1284-1295. [PMID: 33037819 DOI: 10.1093/cercor/bhaa294] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Revised: 09/01/2020] [Accepted: 09/01/2020] [Indexed: 12/12/2022] Open
Abstract
The biological mediators that support cognitive-control and long-term weight-loss after laparoscopic sleeve gastrectomy (LSG) remain unclear. We measured peripheral appetitive hormones and brain functional-connectivity (FC) using magnetic-resonance-imaging with food cue-reactivity task in 25 obese participants at pre, 1 month, and 6 month after LSG, and compared with 30 normal weight controls. We also used diffusion-tensor-imaging to explore whether LSG increases brain structural-connectivity (SC) of regions involved in food cue-reactivity. LSG significantly decreased BMI, craving for high-calorie food cues, ghrelin, insulin, and leptin levels, and increased self-reported cognitive-control of eating behavior. LSG increased FC between the right dorsolateral prefrontal cortex (DLPFC) and the pregenual anterior cingulate cortex (pgACC) and increased SC between DLPFC and ACC at 1 month and 6 month after LSG. Reduction in BMI correlated negatively with increased FC of right DLPFC-pgACC at 1 month and with increased SC of DLPFC-ACC at 1 month and 6 month after LSG. Reduction in craving for high-calorie food cues correlated negatively with increased FC of DLPFC-pgACC at 6 month after LSG. Additionally, SC of DLPFC-ACC mediated the relationship between lower ghrelin levels and greater cognitive control. These findings provide evidence that LSG improved functional and structural connectivity in prefrontal regions, which contribute to enhanced cognitive-control and sustained weight-loss following surgery.
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Affiliation(s)
- Yang Hu
- Center for Brain Imaging, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, China
| | - Gang Ji
- State Key Laboratory of Cancer Biology, National Clinical Research Center for Digestive Diseases and Xijing Hospital of Digestive Diseases, Fourth Military Medical University, Xi'an, Shaanxi 710032, China
| | - Guanya Li
- Center for Brain Imaging, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, China
| | - Peter Manza
- Laboratory of Neuroimaging, National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD 20892, USA
| | - Wenchao Zhang
- Center for Brain Imaging, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, China
| | - Jia Wang
- Center for Brain Imaging, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, China
| | - Ganggang Lv
- Center for Brain Imaging, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, China
| | - Yang He
- Center for Brain Imaging, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, China
| | - Zhida Zhang
- Center for Brain Imaging, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, China
| | - Kai Yuan
- Center for Brain Imaging, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, China
| | - Karen M von Deneen
- Center for Brain Imaging, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, China
| | - Antao Chen
- Department of Psychology, Southwest University, Chongqing 400715, China
| | - Guangbin Cui
- Department of Radiology, Tangdu Hospital, The Fourth Military Medical University, Xi'an, Shaanxi 710038, China
| | - Huaning Wang
- Department of Psychiatry, Xijing Hospital, The Fourth Military Medical University, Xi'an, Shaanxi 710032, China
| | - Corinde E Wiers
- Laboratory of Neuroimaging, National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD 20892, USA
| | - Nora D Volkow
- Laboratory of Neuroimaging, National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD 20892, USA
| | - Yongzhan Nie
- State Key Laboratory of Cancer Biology, National Clinical Research Center for Digestive Diseases and Xijing Hospital of Digestive Diseases, Fourth Military Medical University, Xi'an, Shaanxi 710032, China
| | - Yi Zhang
- Center for Brain Imaging, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, China
| | - Gene-Jack Wang
- Laboratory of Neuroimaging, National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD 20892, USA
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