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Tsuchiyagaito A, Misaki M, Cochran G, Philip NS, Paulus MP, Guinjoan SM. Thalamo-cortical circuits associated with trait- and state-repetitive negative thinking in major depressive disorder. J Psychiatr Res 2023; 168:184-192. [PMID: 37913745 PMCID: PMC10872862 DOI: 10.1016/j.jpsychires.2023.10.058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 08/10/2023] [Accepted: 10/25/2023] [Indexed: 11/03/2023]
Abstract
BACKGROUND Repetitive negative thinking (RNT), often referred to as rumination in the mood disorders literature, is a symptom dimension associated with poor prognosis and suicide in major depressive disorder (MDD). Given the transdiagnostic nature of RNT, this study aimed to evaluate the hypothesis that neurobiological substrates of RNT in MDD may share the brain mechanisms underlying obsessions, particularly those involving cortico-striatal-thalamic-cortical (CSTC) circuits. METHODS Thirty-nine individuals with MDD underwent RNT induction during fMRI. Trait-RNT was measured by the Ruminative Response Scale (RRS) and state-RNT was measured by a visual analogue scale. We employed a connectome-wide association analysis examining the association between RNT intensity with striatal and thalamic connectivity. RESULTS A greater RRS score was associated with hyperconnectivity of the right mediodorsal thalamus with prefrontal cortex, including lateral orbitofrontal cortex, along with Wernicke's area and posterior default mode network nodes (t = 4.66-6.70). A greater state-RNT score was associated with hyperconnectivity of the right laterodorsal thalamus with bilateral primary sensory and motor cortices, supplementary motor area, and Broca's area (t = 4.51-6.57). Unexpectedly, there were no significant findings related to the striatum. CONCLUSIONS The present results suggest RNT in MDD is subserved by abnormal connectivity between right thalamic nuclei and cortical regions involved in both visceral and higher order cognitive processing. Emerging deep-brain neuromodulation methods may be useful to establish causal relationships between dysfunction of right thalamic-cortical circuits and RNT in MDD.
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Affiliation(s)
- Aki Tsuchiyagaito
- Laureate Institute for Brain Research, Tulsa, OK, USA; Oxley College of Health Sciences, The University of Tulsa, Tulsa, OK, USA; Research Center for Child Mental Development, Chiba University, Chiba, Japan.
| | - Masaya Misaki
- Laureate Institute for Brain Research, Tulsa, OK, USA; Oxley College of Health Sciences, The University of Tulsa, Tulsa, OK, USA
| | - Gabe Cochran
- Laureate Institute for Brain Research, Tulsa, OK, USA
| | - Noah S Philip
- Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, Providence, RI, USA; Center for Neurorestoration and Neurotechnology, VA Providence Healthcare System, Providence, RI, USA
| | | | - Salvador M Guinjoan
- Laureate Institute for Brain Research, Tulsa, OK, USA; Department of Psychiatry, Oklahoma University Health Sciences Center at Tulsa, Tulsa, OK, USA; Laureate Psychiatric Hospital and Clinic, Tulsa, OK, USA
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Lu F, Cui Q, Zou Y, Guo Y, Luo W, Yu Y, Gao J, Cai X, Fu L, Yuan S, Huang J, Zhang Y, Xie J, Sheng W, Tang Q, Gao Q, He Z, Chen H. Effects of rTMS Intervention on Functional Neuroimaging Activities in Adolescents with Major Depressive Disorder Measured Using Resting-State fMRI. Bioengineering (Basel) 2023; 10:1374. [PMID: 38135965 PMCID: PMC10740826 DOI: 10.3390/bioengineering10121374] [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: 08/25/2023] [Revised: 11/10/2023] [Accepted: 11/22/2023] [Indexed: 12/24/2023] Open
Abstract
Repetitive transcranial magnetic stimulation (rTMS) to the left dorsolateral prefrontal cortex (L-DLPFC) is commonly used for the clinical treatment of major depressive disorder (MDD). The neuroimaging biomarkers and mechanisms of rTMS are still not completely understood. This study aimed to explore the functional neuroimaging changes induced by rTMS in adolescents with MDD. A total of ten sessions of rTMS were administrated to the L-DLPFC in thirteen adolescents with MDD once a day for two weeks. All of them were scanned using resting-state functional magnetic resonance imaging at baseline and after rTMS treatment. The regional homogeneity (ReHo), amplitude of low-frequency fluctuation (ALFF), and the subgenual anterior cingulate cortex (sgACC)-based functional connectivity (FC) were computed as neuroimaging indicators. The correlation between changes in the sgACC-based FC and the improvement in depressive symptoms was also analyzed. After rTMS treatment, ReHo and ALFF were significantly increased in the L-DLPFC, the left medial prefrontal cortex, bilateral medial orbital frontal cortex, and the left ACC. ReHo and ALFF decreased mainly in the left middle occipital gyrus, the right middle cingulate cortex (MCC), bilateral calcarine, the left cuneus, and the left superior occipital gyrus. Furthermore, the FCs between the left sgACC and the L-DLPFC, the right IFGoper, the left MCC, the left precuneus, bilateral post-central gyrus, the left supplementary motor area, and the left superior marginal gyrus were enhanced after rTMS treatment. Moreover, the changes in the left sgACC-left MCC FC were associated with an improvement in depressive symptoms in early improvers. This study showed that rTMS treatment in adolescents with MDD causes changes in brain activities and sgACC-based FC, which may provide basic neural biomarkers for rTMS clinical trials.
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Affiliation(s)
- Fengmei Lu
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; (F.L.); (Y.Z.); (Y.G.); (W.L.); (Y.Y.); (X.C.); (L.F.); (S.Y.); (J.H.); (Y.Z.); (J.X.); (W.S.); (Q.T.)
| | - Qian Cui
- School of Public Affairs and Administration, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Yang Zou
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; (F.L.); (Y.Z.); (Y.G.); (W.L.); (Y.Y.); (X.C.); (L.F.); (S.Y.); (J.H.); (Y.Z.); (J.X.); (W.S.); (Q.T.)
| | - Yuanhong Guo
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; (F.L.); (Y.Z.); (Y.G.); (W.L.); (Y.Y.); (X.C.); (L.F.); (S.Y.); (J.H.); (Y.Z.); (J.X.); (W.S.); (Q.T.)
| | - Wei Luo
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; (F.L.); (Y.Z.); (Y.G.); (W.L.); (Y.Y.); (X.C.); (L.F.); (S.Y.); (J.H.); (Y.Z.); (J.X.); (W.S.); (Q.T.)
| | - Yue Yu
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; (F.L.); (Y.Z.); (Y.G.); (W.L.); (Y.Y.); (X.C.); (L.F.); (S.Y.); (J.H.); (Y.Z.); (J.X.); (W.S.); (Q.T.)
| | - Jingjing Gao
- School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China;
| | - Xiao Cai
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; (F.L.); (Y.Z.); (Y.G.); (W.L.); (Y.Y.); (X.C.); (L.F.); (S.Y.); (J.H.); (Y.Z.); (J.X.); (W.S.); (Q.T.)
| | - Linna Fu
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; (F.L.); (Y.Z.); (Y.G.); (W.L.); (Y.Y.); (X.C.); (L.F.); (S.Y.); (J.H.); (Y.Z.); (J.X.); (W.S.); (Q.T.)
| | - Shuai Yuan
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; (F.L.); (Y.Z.); (Y.G.); (W.L.); (Y.Y.); (X.C.); (L.F.); (S.Y.); (J.H.); (Y.Z.); (J.X.); (W.S.); (Q.T.)
| | - Juan Huang
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; (F.L.); (Y.Z.); (Y.G.); (W.L.); (Y.Y.); (X.C.); (L.F.); (S.Y.); (J.H.); (Y.Z.); (J.X.); (W.S.); (Q.T.)
| | - Yajun Zhang
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; (F.L.); (Y.Z.); (Y.G.); (W.L.); (Y.Y.); (X.C.); (L.F.); (S.Y.); (J.H.); (Y.Z.); (J.X.); (W.S.); (Q.T.)
| | - Jing Xie
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; (F.L.); (Y.Z.); (Y.G.); (W.L.); (Y.Y.); (X.C.); (L.F.); (S.Y.); (J.H.); (Y.Z.); (J.X.); (W.S.); (Q.T.)
| | - Wei Sheng
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; (F.L.); (Y.Z.); (Y.G.); (W.L.); (Y.Y.); (X.C.); (L.F.); (S.Y.); (J.H.); (Y.Z.); (J.X.); (W.S.); (Q.T.)
| | - Qin Tang
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; (F.L.); (Y.Z.); (Y.G.); (W.L.); (Y.Y.); (X.C.); (L.F.); (S.Y.); (J.H.); (Y.Z.); (J.X.); (W.S.); (Q.T.)
| | - Qing Gao
- School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Zongling He
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; (F.L.); (Y.Z.); (Y.G.); (W.L.); (Y.Y.); (X.C.); (L.F.); (S.Y.); (J.H.); (Y.Z.); (J.X.); (W.S.); (Q.T.)
| | - Huafu Chen
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; (F.L.); (Y.Z.); (Y.G.); (W.L.); (Y.Y.); (X.C.); (L.F.); (S.Y.); (J.H.); (Y.Z.); (J.X.); (W.S.); (Q.T.)
- MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu 611731, China
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Huang Y, Weng Y, Lan L, Zhu C, Shen T, Tang W, Lai HY. Insight in obsessive-compulsive disorder: conception, clinical characteristics, neuroimaging, and treatment. PSYCHORADIOLOGY 2023; 3:kkad025. [PMID: 38666121 PMCID: PMC10917385 DOI: 10.1093/psyrad/kkad025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 10/27/2023] [Accepted: 11/07/2023] [Indexed: 04/28/2024]
Abstract
Obsessive-compulsive disorder (OCD) is a chronic disabling disease with often unsatisfactory therapeutic outcomes. The fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) has broadened the diagnostic criteria for OCD, acknowledging that some OCD patients may lack insight into their symptoms. Previous studies have demonstrated that insight can impact therapeutic efficacy and prognosis, underscoring its importance in the treatment of mental disorders, including OCD. In recent years, there has been a growing interest in understanding the influence of insight on mental disorders, leading to advancements in related research. However, to the best of our knowledge, there is dearth of comprehensive reviews on the topic of insight in OCD. In this review article, we aim to fill this gap by providing a concise overview of the concept of insight and its multifaceted role in clinical characteristics, neuroimaging mechanisms, and treatment for OCD.
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Affiliation(s)
- Yueqi Huang
- Department of Psychiatry, Affiliated Mental Health Center and Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou 310007, China
| | - Yazhu Weng
- Fourth Clinical School of Zhejiang Chinese Medical University, Hangzhou 310053, China
| | - Lan Lan
- Department of Psychology and Behavior Science, Zhejiang University, Hangzhou 310058, China
| | - Cheng Zhu
- Department of Psychiatry, Affiliated Mental Health Center and Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou 310007, China
| | - Ting Shen
- Frontotemporal Degeneration Center, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia 19104, PA, USA
| | - Wenxin Tang
- Department of Psychiatry, Affiliated Mental Health Center and Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou 310007, China
| | - Hsin-Yi Lai
- Department of Psychiatry, Affiliated Mental Health Center and Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou 310007, China
- Department of Neurology of the Second Affiliated Hospital, Interdisciplinary Institute of Neuroscience and Technology, Key Laboratory of Medical Neurobiology of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou 310029, China
- MOE Frontier Science Center for Brain Science and Brain-Machine Integration, State Key Laboratory of Brain-machine Intelligence, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou 311121, China
- College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou 310027, China
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Zarghami TS. A new causal centrality measure reveals the prominent role of subcortical structures in the causal architecture of the extended default mode network. Brain Struct Funct 2023; 228:1917-1941. [PMID: 37658184 DOI: 10.1007/s00429-023-02697-w] [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: 04/16/2023] [Accepted: 08/09/2023] [Indexed: 09/03/2023]
Abstract
Network representation has been an incredibly useful concept for understanding the behavior of complex systems in social sciences, biology, neuroscience, and beyond. Network science is mathematically founded on graph theory, where nodal importance is gauged using measures of centrality. Notably, recent work suggests that the topological centrality of a node should not be over-interpreted as its dynamical or causal importance in the network. Hence, identifying the influential nodes in dynamic causal models (DCM) remains an open question. This paper introduces causal centrality for DCM, a dynamics-sensitive and causally-founded centrality measure based on the notion of intervention in graphical models. Operationally, this measure simplifies to an identifiable expression using Bayesian model reduction. As a proof of concept, the average DCM of the extended default mode network (eDMN) was computed in 74 healthy subjects. Next, causal centralities of different regions were computed for this causal graph, and compared against several graph-theoretical centralities. The results showed that the subcortical structures of the eDMN were more causally central than the cortical regions, even though the graph-theoretical centralities unanimously favored the latter. Importantly, model comparison revealed that only the pattern of causal centrality was causally relevant. These results are consistent with the crucial role of the subcortical structures in the neuromodulatory systems of the brain, and highlight their contribution to the organization of large-scale networks. Potential applications of causal centrality-to study causal models of other neurotypical and pathological functional networks-are discussed, and some future lines of research are outlined.
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Affiliation(s)
- Tahereh S Zarghami
- Bio-Electric Department, School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran.
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Yin Y, Wang F, Ma Y, Yang J, Li R, Li Y, Wang J, Liu H. Structural and functional changes in drug-naïve benign childhood epilepsy with centrotemporal spikes and their associated gene expression profiles. Cereb Cortex 2023; 33:5774-5782. [PMID: 36444721 PMCID: PMC10183734 DOI: 10.1093/cercor/bhac458] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Revised: 10/27/2022] [Accepted: 10/28/2022] [Indexed: 11/30/2022] Open
Abstract
Benign epilepsy with centrotemporal spikes (BECTS) is a common pediatric epilepsy syndrome that has been widely reported to show abnormal brain structure and function. However, the genetic mechanisms underlying structural and functional changes remain largely unknown. Based on the structural and resting-state functional magnetic resonance imaging data of 22 drug-naïve children with BECTS and 33 healthy controls, we conducted voxel-based morphology (VBM) and fractional amplitude of low-frequency fluctuation (fALFF) analyses to compare cortical morphology and spontaneous brain activity between the 2 groups. In combination with the Allen Human Brain Atlas, transcriptome-neuroimaging spatial correlation analyses were applied to explore gene expression profiles associated with gray matter volume (GMV) and fALFF changes in BECTS. VBM analysis demonstrated significantly increased GMV in the right brainstem and right middle cingulate gyrus in BECTS. Moreover, children with BECTS exhibited significantly increased fALFF in left temporal pole, while decreased fALFF in right thalamus and left precuneus. These brain structural and functional alterations were closely related to behavioral and cognitive deficits, and the fALFF-linked gene expression profiles were enriched in voltage-gated ion channel and synaptic activity as well as neuron projection. Our findings suggest that brain morphological and functional abnormalities in children with BECTS involve complex polygenic genetic mechanisms.
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Affiliation(s)
- Yu Yin
- Department of Radiology, Affiliated Hospital of Zunyi Medical University, Medical Imaging Center of Guizhou Province, Zunyi 563003, China
| | - Fuqin Wang
- Department of Radiology, Affiliated Hospital of Zunyi Medical University, Medical Imaging Center of Guizhou Province, Zunyi 563003, China
| | - Yingzi Ma
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming 650500, China
- Yunnan Key Laboratory of Primate Biomedical Research, Kunming 650500, Yunnan, China
| | - Jia Yang
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming 650500, China
- Yunnan Key Laboratory of Primate Biomedical Research, Kunming 650500, Yunnan, China
| | - Rui Li
- School of Electrical Engineering and Electronic Information, Xihua University, Chengdu 610039, China
| | - Yuanyuan Li
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 625014, China
| | - Jiaojian Wang
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming 650500, China
- Yunnan Key Laboratory of Primate Biomedical Research, Kunming 650500, Yunnan, China
| | - Heng Liu
- Department of Radiology, Affiliated Hospital of Zunyi Medical University, Medical Imaging Center of Guizhou Province, Zunyi 563003, China
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Lu C, Feng Y, Li H, Gao Z, Zhu X, Hu J. A preclinical study of deep brain stimulation in the ventral tegmental area for alleviating positive psychotic-like behaviors in mice. Front Hum Neurosci 2022; 16:945912. [PMID: 36034113 PMCID: PMC9399924 DOI: 10.3389/fnhum.2022.945912] [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: 05/17/2022] [Accepted: 06/14/2022] [Indexed: 11/13/2022] Open
Abstract
Deep brain stimulation (DBS) is a clinical intervention for the treatment of movement disorders. It has also been applied to the treatment of psychiatric disorders such as depression, anorexia nervosa, obsessive-compulsive disorder, and schizophrenia. Psychiatric disorders including schizophrenia, bipolar disorder, and major depression can lead to psychosis, which can cause patients to lose touch with reality. The ventral tegmental area (VTA), located near the midline of the midbrain, is an important region involved in psychosis. However, the clinical application of electrical stimulation of the VTA to treat psychotic diseases has been limited, and related mechanisms have not been thoroughly studied. In the present study, hyperlocomotion and stereotyped behaviors of the mice were employed to mimic and evaluate the positive-psychotic-like behaviors. We attempted to treat positive psychotic-like behaviors by electrically stimulating the VTA in mice and exploring the neural mechanisms behind behavioral effects. Local field potential recording and in vivo fiber photometry to observe the behavioral effects and changes in neural activities caused by DBS in the VTA of mice. Optogenetic techniques were used to verify the neural mechanisms underlying the behavioral effects induced by DBS. Our results showed that electrical stimulation of the VTA activates local gamma-aminobutyric acid (GABA) neurons, and dopamine (DA) neurons, reduces hyperlocomotion, and relieves stereotyped behaviors induced by MK-801 (dizocilpine) injection. The results of optogenetic manipulation showed that the activation of the VTA GABA neurons, but not DA neurons, is involved in the alleviation of hyperlocomotion and stereotyped behaviors. We visualized changes in the activity of specific types in specific brain areas induced by DBS, and explored the neural mechanism of DBS in alleviating positive psychotic-like behaviors. This preclinical study not only proposes new technical means of exploring the mechanism of DBS, but also provides experimental justification for the clinical treatment of psychotic diseases by electrical stimulation of the VTA.
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Affiliation(s)
- Chen Lu
- School of Life Science and Technology, Shanghai Tech University, Shanghai, China
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Yifan Feng
- School of Life Science and Technology, Shanghai Tech University, Shanghai, China
| | - Hongxia Li
- Department of Neurology and Institute of Neurology, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zilong Gao
- School of Life Sciences, Westlake University, Hangzhou, China
| | - Xiaona Zhu
- School of Life Science and Technology, Shanghai Tech University, Shanghai, China
| | - Ji Hu
- School of Life Science and Technology, Shanghai Tech University, Shanghai, China
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