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Demiral S, Lildharrie C, Lin E, Benveniste H, Volkow N. Blink-related arousal network surges are shaped by cortical vigilance states. RESEARCH SQUARE 2024:rs.3.rs-4271439. [PMID: 38766129 PMCID: PMC11100883 DOI: 10.21203/rs.3.rs-4271439/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
The vigilance state and the excitability of cortical networks impose wide-range effects on brain dynamics that arousal surges could promptly modify. We previously reported an association between spontaneous eye-blinks and BOLD activation in the brain arousal ascending network (AAN) and in thalamic nuclei based on 3T MR resting state brain images. Here we aimed to replicate our analyses using 7T MR images in a larger cohort of participants collected from the Human Connectome Project (HCP), which also contained simultaneous eye-tracking recordings, and to assess the interaction between the blink-associated arousal surges and the vigilance states. For this purpose, we compared blink associated BOLD activity under a vigilant versus a drowsy state, a classification made based on the pupillary data obtained during the fMRI scans. We conducted two main analyses: i) Cross-correlation analysis between the BOLD signal and blink events (eye blink time-series were convolved with the canonical and also with the temporal derivative of the Hemodynamic Response Function, HRF) within preselected regions of interests (ROIs) (i.e., brainstem AAN, thalamic and cerebellar nuclei) together with an exploratory voxel-wise analyses to assess the whole-brain, and ii) blink-event analysis of the BOLD signals to reveal the signal changes onset to the blinks in the preselected ROIs. Consistent with our prior findings on 3T MRI, we showed significant positive cross correlations between BOLD peaks in brainstem and thalamic nuclei that preceded or were overlapping with blink moments and that sharply decreased post-blink. Whole brain analysis revealed blink-related activation that was strongest in cerebellum, insula, lateral geniculate nucleus (LGN) and visual cortex. Drowsiness impacted HRF BOLD (enhancing it), time-to-peak (delaying it) and post-blink BOLD activity (accentuating decreases). Responses in the drowsy state could be related to the differences in the excitability of cortical, subcortical and cerebellar tissue, such that cerebellar and thalamic regions involved in visual attention processing were more responsive for the vigilant state, but AAN ROIs, as well as cerebellar and thalamic ROIs connected to pre-motor, frontal, temporal and DMN regions were less responsive. Such qualitative and quantitative differences in the blink related BOLD signal changes could reflect delayed cortical processing and the ineffectiveness of arousal surges during states of drowsiness. Future studies that manipulate arousal are needed to corroborate a mechanistic interaction of arousal surges with vigilance states and cortical excitability.
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Affiliation(s)
- Sukru Demiral
- National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health
| | - Christina Lildharrie
- National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health
| | - Esther Lin
- National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health
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Fan JM, Kudo K, Verma P, Ranasinghe KG, Morise H, Findlay AM, Vossel K, Kirsch HE, Raj A, Krystal AD, Nagarajan SS. Cortical Synchrony and Information Flow during Transition from Wakefulness to Light Non-Rapid Eye Movement Sleep. J Neurosci 2023; 43:8157-8171. [PMID: 37788939 PMCID: PMC10697405 DOI: 10.1523/jneurosci.0197-23.2023] [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: 02/01/2023] [Revised: 07/07/2023] [Accepted: 08/06/2023] [Indexed: 10/05/2023] Open
Abstract
Sleep is a highly stereotyped phenomenon, requiring robust spatiotemporal coordination of neural activity. Understanding how the brain coordinates neural activity with sleep onset can provide insights into the physiological functions subserved by sleep and the pathologic phenomena associated with sleep onset. We quantified whole-brain network changes in synchrony and information flow during the transition from wakefulness to light non-rapid eye movement (NREM) sleep, using MEG imaging in a convenient sample of 14 healthy human participants (11 female; mean 63.4 years [SD 11.8 years]). We furthermore performed computational modeling to infer excitatory and inhibitory properties of local neural activity. The transition from wakefulness to light NREM was identified to be encoded in spatially and temporally specific patterns of long-range synchrony. Within the delta band, there was a global increase in connectivity from wakefulness to light NREM, which was highest in frontoparietal regions. Within the theta band, there was an increase in connectivity in fronto-parieto-occipital regions and a decrease in temporal regions from wakefulness to Stage 1 sleep. Patterns of information flow revealed that mesial frontal regions receive hierarchically organized inputs from broad cortical regions upon sleep onset, including direct inflow from occipital regions and indirect inflow via parieto-temporal regions within the delta frequency band. Finally, biophysical neural mass modeling demonstrated changes in the anterior-to-posterior distribution of cortical excitation-to-inhibition with increased excitation-to-inhibition model parameters in anterior regions in light NREM compared with wakefulness. Together, these findings uncover whole-brain corticocortical structure and the orchestration of local and long-range, frequency-specific cortical interactions in the sleep-wake transition.SIGNIFICANCE STATEMENT Our work uncovers spatiotemporal cortical structure of neural synchrony and information flow upon the transition from wakefulness to light non-rapid eye movement sleep. Mesial frontal regions were identified to receive hierarchically organized inputs from broad cortical regions, including both direct inputs from occipital regions and indirect inputs via the parieto-temporal regions within the delta frequency range. Biophysical neural mass modeling revealed a spatially heterogeneous, anterior-posterior distribution of cortical excitation-to-inhibition. Our findings shed light on the orchestration of local and long-range cortical neural structure that is fundamental to sleep onset, and support an emerging view of cortically driven regulation of sleep homeostasis.
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Affiliation(s)
- Joline M Fan
- Department of Neurology, University of California-San Francisco, San Francisco, California 94143
| | - Kiwamu Kudo
- Department of Radiology and Biomedical Imaging, University of California-San Francisco, San Francisco, California 94143
- Medical Imaging Center, Ricoh Company, Ltd., Kanazawa, Japan 243-0460
| | - Parul Verma
- Department of Radiology and Biomedical Imaging, University of California-San Francisco, San Francisco, California 94143
| | - Kamalini G Ranasinghe
- Department of Neurology, University of California-San Francisco, San Francisco, California 94143
| | - Hirofumi Morise
- Department of Radiology and Biomedical Imaging, University of California-San Francisco, San Francisco, California 94143
- Medical Imaging Center, Ricoh Company, Ltd., Kanazawa, Japan 243-0460
| | - Anne M Findlay
- Department of Radiology and Biomedical Imaging, University of California-San Francisco, San Francisco, California 94143
| | - Keith Vossel
- Department of Neurology, University of California-San Francisco, San Francisco, California 94143
- Mary S. Easton Center for Alzheimer's Disease Research, Department of Neurology, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, California 90095
| | - Heidi E Kirsch
- Department of Neurology, University of California-San Francisco, San Francisco, California 94143
- Department of Radiology and Biomedical Imaging, University of California-San Francisco, San Francisco, California 94143
| | - Ashish Raj
- Department of Radiology and Biomedical Imaging, University of California-San Francisco, San Francisco, California 94143
| | - Andrew D Krystal
- Department of Psychiatry, University of California-San Francisco, San Francisco, California 94143
| | - Srikantan S Nagarajan
- Department of Radiology and Biomedical Imaging, University of California-San Francisco, San Francisco, California 94143
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Cardone P, Bodart O, Kirsch M, Sanfilippo J, Virgillito A, Martial C, Simon J, Wannez S, Sanders RD, Laureys S, Massimini M, Vandewalle G, Bonhomme V, Gosseries O. Depth of sedation with dexmedetomidine increases transcranial magnetic stimulation-evoked potential amplitude non-linearly. Br J Anaesth 2023; 131:715-725. [PMID: 37596183 DOI: 10.1016/j.bja.2023.05.030] [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: 06/24/2021] [Revised: 05/09/2023] [Accepted: 05/30/2023] [Indexed: 08/20/2023] Open
Abstract
BACKGROUND Cortical excitability is higher in unconsciousness than in wakefulness, but it is unclear how this relates to anaesthesia. We investigated cortical excitability in response to dexmedetomidine, the effects of which are not fully known. METHODS We recorded transcranial magnetic stimulation (TMS) and EEG in frontal and parietal cortex of 20 healthy subjects undergoing dexmedetomidine sedation in four conditions (baseline, light sedation, deep sedation, recovery). We used the first component (0-30 ms) of the TMS-evoked potential (TEP) to measure cortical excitability (amplitude), slope, and positive and negative peak latencies (collectively, TEP indices). We used generalised linear mixed models to test the effect of condition, brain region, and responsiveness on TEP indices. RESULTS Compared with baseline, amplitude in the frontal cortex increased by 6.52 μV (P<0.001) in light sedation, 4.55 μV (P=0.003) in deep sedation, and 5.03 μV (P<0.001) in recovery. Amplitude did not change in the parietal cortex. Compared with baseline, slope increased in all conditions (P<0.02) in the frontal but not parietal cortex. The frontal cortex showed 5.73 μV higher amplitude (P<0.001), 0.63 μV ms-1 higher slope (P<0.001), and 2.2 ms shorter negative peak latency (P=0.001) than parietal areas. Interactions between dexmedetomidine and region had effects over amplitude (P=0.004) and slope (P=0.009), with both being higher in light sedation, deep sedation, and recovery compared with baseline. CONCLUSIONS Transcranial magnetic stimulation-evoked potential amplitude changes non-linearly as a function of depth of sedation by dexmedetomidine, with a region-specific paradoxical increase. Future research should investigate other anaesthetics to elucidate the link between cortical excitability and depth of sedation.
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Affiliation(s)
- Paolo Cardone
- Coma Science Group, GIGA-Consciousness, University of Liège, Liège, Belgium; Centre du Cerveau, University of Liège, Liège, Belgium
| | - Olivier Bodart
- Coma Science Group, GIGA-Consciousness, University of Liège, Liège, Belgium; Centre du Cerveau, University of Liège, Liège, Belgium; Department of Neurology, University of Liège, Liège, Belgium
| | - Murielle Kirsch
- Anesthesia and Perioperative Neuroscience Laboratory, GIGA-Consciousness, University of Liège, Liège, Belgium; Department of Anaesthesia and Intensive Care Medicine, University of Liège, Liège, Belgium
| | - Julien Sanfilippo
- Anesthesia and Perioperative Neuroscience Laboratory, GIGA-Consciousness, University of Liège, Liège, Belgium
| | | | - Charlotte Martial
- Coma Science Group, GIGA-Consciousness, University of Liège, Liège, Belgium; Centre du Cerveau, University of Liège, Liège, Belgium
| | - Jessica Simon
- Psychology and Neuroscience of Cognition, University of Liège, Liège, Belgium
| | - Sarah Wannez
- Coma Science Group, GIGA-Consciousness, University of Liège, Liège, Belgium
| | - Robert D Sanders
- Specialty of Anaesthetics, University of Sydney, Camperdown, Australia; Department of Anaesthetics & Institute of Academic Surgery, Royal Prince Alfred Hospital, Camperdown, Australia
| | - Steven Laureys
- Coma Science Group, GIGA-Consciousness, University of Liège, Liège, Belgium; Centre du Cerveau, University of Liège, Liège, Belgium; Joint International Research Unit on Consciousness, CERVO Brain Research Centre, CIUSS, University Laval, Québec City, QC, Canada
| | - Marcello Massimini
- Department of Biomedical and Clinical Sciences "L. Sacco", Università degli Studi di Milano, Milan, Italy; IRCCS Fondazione Don Gnocchi, Milan, Italy
| | - Gilles Vandewalle
- Sleep and Chronobiology Lab, GIGA-Cyclotron Research Centre-In Vivo Imaging, University of Liège, Liège, Belgium
| | - Vincent Bonhomme
- Anesthesia and Perioperative Neuroscience Laboratory, GIGA-Consciousness, University of Liège, Liège, Belgium; Department of Anaesthesia and Intensive Care Medicine, University of Liège, Liège, Belgium; University Department of Anaesthesia and Intensive Care Medicine, Centre Hospitalier Régional de la Citadelle (CHR Citadelle), Liège, Belgium.
| | - Olivia Gosseries
- Coma Science Group, GIGA-Consciousness, University of Liège, Liège, Belgium; Centre du Cerveau, University of Liège, Liège, Belgium.
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Wang J, Chau SWH, Lam SP, Liu Y, Zhang J, Chan NY, Cheung MMS, Yu MWM, Tsang JCT, Chan JWY, Huang B, Li SX, Mok V, Wing YK. Prevalence and correlates of REM sleep behaviour disorder in patients with major depressive disorder: a two-phase study. J Neurol Neurosurg Psychiatry 2022; 93:1010-1017. [PMID: 34764151 DOI: 10.1136/jnnp-2021-327460] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Accepted: 10/13/2021] [Indexed: 11/04/2022]
Abstract
OBJECTIVE To investigate the prevalence and clinical correlates of video polysomnography (vPSG)-confirmed rapid eye movement sleep behaviour disorder (RBD) in patients with major depressive disorder (MDD). METHODS This is a clinic-based two-phase epidemiological study. In phase 1, patients with MDD were screened by a validated questionnaire, RBD Questionnaire-Hong Kong (RBDQ-HK). In phase 2, a subsample of both the screen-positive (RBDQ-HK >20) and screen-negative patients with MDD underwent further clinical and sleep assessment (vPSG) to confirm the diagnosis of RBD (MDD+RBD). Poststratification weighting method was used to estimate the prevalence of MDD+RBD. The total likelihood ratio and the probability of prodromal Parkinson's disease (PD) were calculated from prodromal markers and risk factors, as per the Movement Disorder Society research criteria. RESULTS A total of 455 patients with MDD were screened (median age (IQR)=52.66 (15.35) years, 77.58% woman, 43.74% positive). Eighty-one patients underwent vPSG and 12 of them were confirmed MDD+RBD. The prevalence of MDD+RBD was estimated to be 8.77% (95% CI: 4.33% to 16.93%), with possibly male predominance. MDD+RBD were associated with colour vision and olfaction deficit and a higher probability for prodromal PD. CONCLUSIONS Almost 9% of patients with MDD in the psychiatric outpatient clinic has vPSG-confirmed RBD. Comorbid MDD+RBD may represent a subtype of MDD with underlying α-synucleinopathy neurodegeneration. Systematic screening of RBD symptoms and necessity of vPSG confirmation should be highlighted for capturing this MDD subtype with a view to enhance personalised treatment and future neuroprotection to prevent neurodegeneration.
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Affiliation(s)
- Jing Wang
- Department of Psychiatry, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China.,Li Chiu Kong Family Sleep Assessment Unit, Department of Psychiatry, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Steven W H Chau
- Department of Psychiatry, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China.,Li Chiu Kong Family Sleep Assessment Unit, Department of Psychiatry, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Siu Ping Lam
- Department of Psychiatry, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China.,Li Chiu Kong Family Sleep Assessment Unit, Department of Psychiatry, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Yaping Liu
- Department of Psychiatry, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China.,Li Chiu Kong Family Sleep Assessment Unit, Department of Psychiatry, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Jihui Zhang
- Department of Psychiatry, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China.,Li Chiu Kong Family Sleep Assessment Unit, Department of Psychiatry, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China.,Guangdong Mental Health Center, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Science, Guangzhou, Guangdong, China
| | - Ngan Yin Chan
- Department of Psychiatry, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China.,Li Chiu Kong Family Sleep Assessment Unit, Department of Psychiatry, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Maxine M S Cheung
- Department of Psychiatry, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China.,Li Chiu Kong Family Sleep Assessment Unit, Department of Psychiatry, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Mandy Wai Man Yu
- Department of Psychiatry, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China.,Li Chiu Kong Family Sleep Assessment Unit, Department of Psychiatry, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Jessie C T Tsang
- Department of Psychiatry, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China.,Li Chiu Kong Family Sleep Assessment Unit, Department of Psychiatry, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Joey W Y Chan
- Department of Psychiatry, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China.,Li Chiu Kong Family Sleep Assessment Unit, Department of Psychiatry, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Bei Huang
- Department of Psychiatry, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China.,Li Chiu Kong Family Sleep Assessment Unit, Department of Psychiatry, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Shirley X Li
- Department of Psychology, The University of Hong Kong, Hong Kong SAR, China.,The State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong SAR, China
| | - Vincent Mok
- Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Yun Kwok Wing
- Department of Psychiatry, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China .,Li Chiu Kong Family Sleep Assessment Unit, Department of Psychiatry, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
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TMS-EEG responses across the lifespan: Measurement, methods for characterisation and identified responses. J Neurosci Methods 2022; 366:109430. [PMID: 34856320 DOI: 10.1016/j.jneumeth.2021.109430] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Revised: 11/02/2021] [Accepted: 11/25/2021] [Indexed: 01/29/2023]
Abstract
The combination of transcranial magnetic stimulation (TMS) and electroencephalography (EEG) allows probing of the neurophysiology of any neocortical brain area in vivo with millisecond accuracy. TMS-EEG is particularly unique compared with other available neurophysiological methods, as it can measure the state and dynamics of excitatory and inhibitory systems separately. Because of these capabilities, TMS-EEG responses are sensitive to the brain state, and the responses are influenced by brain maturation and ageing, making TMS-EEG a suitable method to study age-specific pathophysiology. In this review, we outline the TMS-EEG measurement procedure, the existing methods used for characterising TMS-EEG responses and the challenges associated with identifying the responses. We also summarise the findings thus far on how TMS-EEG responses change across the lifespan and the TMS-EEG features that separate typical and atypical brain maturation and ageing. Finally, we give an overview of the gaps in current knowledge to provide directions for future studies.
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Chia CH, Tang XW, Cao Y, Cao HT, Zhang W, Wu JF, Zhu YL, Chen Y, Lin Y, Wu Y, Zhang Z, Yuan TF, Hu RP. Cortical excitability signatures for the degree of sleepiness in human. eLife 2021; 10:65099. [PMID: 34313218 PMCID: PMC8373378 DOI: 10.7554/elife.65099] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2020] [Accepted: 07/26/2021] [Indexed: 11/13/2022] Open
Abstract
Sleep is essential in maintaining physiological homeostasis in the brain. While the underlying mechanism is not fully understood, a 'synaptic homeostasis' theory has been proposed that synapses continue to strengthen during awake and undergo downscaling during sleep. This theory predicts that brain excitability increases with sleepiness. Here, we collected transcranial magnetic stimulation measurements in 38 subjects in a 34 hr program and decoded the relationship between cortical excitability and self-report sleepiness using advanced statistical methods. By utilizing a combination of partial least squares regression and mixed-effect models, we identified a robust pattern of excitability changes, which can quantitatively predict the degree of sleepiness. Moreover, we found that synaptic strengthen occurred in both excitatory and inhibitory connections after sleep deprivation. In sum, our study provides supportive evidence for the synaptic homeostasis theory in human sleep and clarifies the process of synaptic strength modulation during sleepiness.
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Affiliation(s)
- Chin-Hsuan Chia
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Xin-Wei Tang
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Yue Cao
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Hua-Teng Cao
- Institute of Neuroscience, State Key Laboratory of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China.,Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai, China
| | - Wei Zhang
- Institute of Brain Science, Fudan University, Shanghai, China
| | - Jun-Fa Wu
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Yu-Lian Zhu
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Ying Chen
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Yi Lin
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Yi Wu
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Zhe Zhang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China.,Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai, China
| | - Ti-Fei Yuan
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental HealthCenter, Shanghai Jiaotong University School of Medicine, Shanghai, China.,Co-innovation Center of Neuroregeneration, Nantong University, Nantong, China.,Translational Research Institute of Brain and Brain-Like Intelligence, Shanghai Fourth People's Hospital Affiliated to Tongji University School of Medicine, Shanghai, China
| | - Rui-Ping Hu
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China
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