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Zeng S, Ma L, Mao H, Shi Y, Xu M, Gao Q, Kaidong C, Li M, Ding Y, Ji Y, Hu X, Feng W, Fang X. Dynamic functional network connectivity in patients with a mismatch between white matter hyperintensity and cognitive function. Front Aging Neurosci 2024; 16:1418173. [PMID: 39086757 PMCID: PMC11288916 DOI: 10.3389/fnagi.2024.1418173] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2024] [Accepted: 07/03/2024] [Indexed: 08/02/2024] Open
Abstract
Objective White matter hyperintensity (WMH) in patients with cerebral small vessel disease (CSVD) is strongly associated with cognitive impairment. However, the severity of WMH does not coincide fully with cognitive impairment. This study aims to explore the differences in the dynamic functional network connectivity (dFNC) of WMH with cognitively matched and mismatched patients, to better understand the underlying mechanisms from a quantitative perspective. Methods The resting-state functional magnetic resonance imaging (rs-fMRI) and cognitive function scale assessment of the patients were acquired. Preprocessing of the rs-fMRI data was performed, and this was followed by dFNC analysis to obtain the dFNC metrics. Compared the dFNC and dFNC metrics within different states between mismatch and match group, we analyzed the correlation between dFNC metrics and cognitive function. Finally, to analyze the reasons for the differences between the mismatch and match groups, the CSVD imaging features of each patient were quantified with the assistance of the uAI Discover system. Results The 149 CSVD patients included 20 cases of "Type I mismatch," 51 cases of Type I match, 38 cases of "Type II mismatch," and 40 cases of "Type II match." Using dFNC analysis, we found that the fraction time (FT) and mean dwell time (MDT) of State 2 differed significantly between "Type I match" and "Type I mismatch"; the FT of States 1 and 4 differed significantly between "Type II match" and "Type II mismatch." Correlation analysis revealed that dFNC metrics in CSVD patients correlated with executive function and information processing speed among the various cognitive functions. Through quantitative analysis, we found that the number of perivascular spaces and bilateral medial temporal lobe atrophy (MTA) scores differed significantly between "Type I match" and "Type I mismatch," while the left MTA score differed between "Type II match" and "Type II mismatch." Conclusion Different mechanisms were implicated in these two types of mismatch: Type I affected higher-order networks, and may be related to the number of perivascular spaces and brain atrophy, whereas Type II affected the primary networks, and may be related to brain atrophy and the years of education.
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Affiliation(s)
- Siyuan Zeng
- Medical Imaging Center, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi Medical Center, Nanjing Medical University, Wuxi People’s Hospital, Wuxi, China
| | - Lin Ma
- Medical Imaging Center, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi Medical Center, Nanjing Medical University, Wuxi People’s Hospital, Wuxi, China
| | - Haixia Mao
- Medical Imaging Center, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi Medical Center, Nanjing Medical University, Wuxi People’s Hospital, Wuxi, China
| | - Yachen Shi
- Department of Neurology, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi Medical Center, Nanjing Medical University, Wuxi People’s Hospital, Wuxi, China
| | - Min Xu
- Medical Imaging Center, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi Medical Center, Nanjing Medical University, Wuxi People’s Hospital, Wuxi, China
| | - Qianqian Gao
- Medical Imaging Center, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi Medical Center, Nanjing Medical University, Wuxi People’s Hospital, Wuxi, China
| | - Chen Kaidong
- Medical Imaging Center, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi Medical Center, Nanjing Medical University, Wuxi People’s Hospital, Wuxi, China
| | - Mingyu Li
- Medical Imaging Center, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi Medical Center, Nanjing Medical University, Wuxi People’s Hospital, Wuxi, China
| | - Yuxiao Ding
- Medical Imaging Center, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi Medical Center, Nanjing Medical University, Wuxi People’s Hospital, Wuxi, China
| | - Yi Ji
- Medical Imaging Center, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi Medical Center, Nanjing Medical University, Wuxi People’s Hospital, Wuxi, China
| | - Xiaoyun Hu
- Medical Imaging Center, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi Medical Center, Nanjing Medical University, Wuxi People’s Hospital, Wuxi, China
| | - Wang Feng
- Department of Neurology, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi Medical Center, Nanjing Medical University, Wuxi People’s Hospital, Wuxi, China
| | - Xiangming Fang
- Medical Imaging Center, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi Medical Center, Nanjing Medical University, Wuxi People’s Hospital, Wuxi, China
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Mehta DD, Siddiqui S, Ward HB, Steele VR, Pearlson GD, George TP. Functional and structural effects of repetitive transcranial magnetic stimulation (rTMS) for the treatment of auditory verbal hallucinations in schizophrenia: A systematic review. Schizophr Res 2024; 267:86-98. [PMID: 38531161 DOI: 10.1016/j.schres.2024.03.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Revised: 02/26/2024] [Accepted: 03/15/2024] [Indexed: 03/28/2024]
Abstract
BACKGROUND Auditory verbal hallucinations (AVH) are a disabling symptom for people with schizophrenia (SCZ), and do not always respond to antipsychotics. Repetitive transcranial magnetic stimulation (rTMS) has shown efficacy for medication-refractory AVH, though the underlying neural mechanisms by which rTMS produces these effects remain unclear. This systematic review evaluated the structural and functional impact of rTMS for AVH in SCZ, and its association with clinical outcomes. METHODS A systematic search was conducted in Medline, PsychINFO, and PubMed using terms for four key concepts: AVH, SCZ, rTMS, neuroimaging. Using PRISMA guidelines, 18 studies were identified that collected neuroimaging data of an rTMS intervention for AVH in SCZ. Risk of bias assessments was conducted. RESULTS Low frequency (<5 Hz) rTMS targeting left hemispheric language processing regions may normalize brain abnormalities in AVH patients at structural, functional, electrophysiological, and topological levels, with concurrent symptom improvement. Amelioration of aberrant neural activity in frontotemporal networks associated with speech and auditory processing was commonly observed, as well as in cerebellar and emotion regulation regions. Neuroimaging analyses identified neural substrates with direct correlations to post-rTMS AVH severity, propounding their use as therapeutic targets. DISCUSSION Combined rTMS-neuroimaging highlights the multidimensional alterations of rTMS on brain activity and structure in treatment-resistant AVH, which may be used to develop more efficacious therapies. Larger randomized, sham-controlled studies are needed. Future studies should explore alternate stimulation targets, investigate the neural effects of high-frequency rTMS and evaluate long-term neuroimaging outcomes.
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Affiliation(s)
- Dhvani D Mehta
- Institute of Medical Sciences, Temerty Faculty of Medicine, University of Toronto, Canada; Department of Psychiatry, Vanderbilt University, Nashville, TN, USA; Hartford Hospital and Department of Psychiatry and Behavioural Sciences, Yale University, New Haven, CT, USA; Department of Psychiatry, University of Toronto, Canada; Addictions Division and Institute for Mental Health Policy and Research, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada.
| | - Salsabil Siddiqui
- Institute of Medical Sciences, Temerty Faculty of Medicine, University of Toronto, Canada; Department of Psychiatry, Vanderbilt University, Nashville, TN, USA; Hartford Hospital and Department of Psychiatry and Behavioural Sciences, Yale University, New Haven, CT, USA; Department of Psychiatry, University of Toronto, Canada; Addictions Division and Institute for Mental Health Policy and Research, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada
| | - Heather B Ward
- Institute of Medical Sciences, Temerty Faculty of Medicine, University of Toronto, Canada; Department of Psychiatry, Vanderbilt University, Nashville, TN, USA; Hartford Hospital and Department of Psychiatry and Behavioural Sciences, Yale University, New Haven, CT, USA; Department of Psychiatry, University of Toronto, Canada; Addictions Division and Institute for Mental Health Policy and Research, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada
| | - Vaughn R Steele
- Institute of Medical Sciences, Temerty Faculty of Medicine, University of Toronto, Canada; Department of Psychiatry, Vanderbilt University, Nashville, TN, USA; Hartford Hospital and Department of Psychiatry and Behavioural Sciences, Yale University, New Haven, CT, USA; Department of Psychiatry, University of Toronto, Canada; Addictions Division and Institute for Mental Health Policy and Research, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada
| | - Godfrey D Pearlson
- Institute of Medical Sciences, Temerty Faculty of Medicine, University of Toronto, Canada; Department of Psychiatry, Vanderbilt University, Nashville, TN, USA; Hartford Hospital and Department of Psychiatry and Behavioural Sciences, Yale University, New Haven, CT, USA; Department of Psychiatry, University of Toronto, Canada; Addictions Division and Institute for Mental Health Policy and Research, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada
| | - Tony P George
- Institute of Medical Sciences, Temerty Faculty of Medicine, University of Toronto, Canada; Department of Psychiatry, Vanderbilt University, Nashville, TN, USA; Hartford Hospital and Department of Psychiatry and Behavioural Sciences, Yale University, New Haven, CT, USA; Department of Psychiatry, University of Toronto, Canada; Addictions Division and Institute for Mental Health Policy and Research, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada.
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Kuang LD, Li HQ, Zhang J, Gui Y, Zhang J. Dynamic functional network connectivity analysis in schizophrenia based on a spatiotemporal CPD framework. J Neural Eng 2024; 21:016032. [PMID: 38335544 DOI: 10.1088/1741-2552/ad27ee] [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: 09/12/2023] [Accepted: 02/09/2024] [Indexed: 02/12/2024]
Abstract
Objective.Dynamic functional network connectivity (dFNC), based on data-driven group independent component (IC) analysis, is an important avenue for investigating underlying patterns of certain brain diseases such as schizophrenia. Canonical polyadic decomposition (CPD) of a higher-way dynamic functional connectivity tensor, can offer an innovative spatiotemporal framework to accurately characterize potential dynamic spatial and temporal fluctuations. Since multi-subject dFNC data from sliding-window analysis are also naturally a higher-order tensor, we propose an innovative sparse and low-rank CPD (SLRCPD) for the three-way dFNC tensor to excavate significant dynamic spatiotemporal aberrant changes in schizophrenia.Approach.The proposed SLRCPD approach imposes two constraints. First, the L1regularization on spatial modules is applied to extract sparse but significant dynamic connectivity and avoid overfitting the model. Second, low-rank constraint is added on time-varying weights to enhance the temporal state clustering quality. Shared dynamic spatial modules, group-specific dynamic spatial modules and time-varying weights can be extracted by SLRCPD. The strength of connections within- and between-IC networks and connection contribution are proposed to inspect the spatial modules. K-means clustering and classification are further conducted to explore temporal group difference.Main results.82 subject resting-state functional magnetic resonance imaging (fMRI) dataset and opening Center for Biomedical Research Excellence (COBRE) schizophrenia dataset both containing schizophrenia patients (SZs) and healthy controls (HCs) were utilized in our work. Three typical dFNC patterns between different brain functional regions were obtained. Compared to the spatial modules of HCs, the aberrant connections among auditory network, somatomotor, visual, cognitive control and cerebellar networks in 82 subject dataset and COBRE dataset were detected. Four temporal states reveal significant differences between SZs and HCs for these two datasets. Additionally, the accuracy values for SZs and HCs classification based on time-varying weights are larger than 0.96.Significance.This study significantly excavates spatio-temporal patterns for schizophrenia disease.
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Affiliation(s)
- Li-Dan Kuang
- School of Computer and Communication Engineering, Changsha University of Science and Technology, Changsha, People's Republic of China
| | - He-Qiang Li
- School of Computer and Communication Engineering, Changsha University of Science and Technology, Changsha, People's Republic of China
| | - Jianming Zhang
- School of Computer and Communication Engineering, Changsha University of Science and Technology, Changsha, People's Republic of China
| | - Yan Gui
- School of Computer and Communication Engineering, Changsha University of Science and Technology, Changsha, People's Republic of China
| | - Jin Zhang
- School of Computer and Communication Engineering, Changsha University of Science and Technology, Changsha, People's Republic of China
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Xie Y, Li C, Guan M, Zhang T, Ma C, Wang Z, Ma Z, Wang H, Fang P. Low-frequency rTMS induces modifications in cortical structural connectivity - functional connectivity coupling in schizophrenia patients with auditory verbal hallucinations. Hum Brain Mapp 2024; 45:e26614. [PMID: 38375980 PMCID: PMC10878014 DOI: 10.1002/hbm.26614] [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: 08/17/2023] [Revised: 01/09/2024] [Accepted: 01/19/2024] [Indexed: 02/21/2024] Open
Abstract
Auditory verbal hallucinations (AVH) are distinctive clinical manifestations of schizophrenia. While low-frequency repetitive transcranial magnetic stimulation (rTMS) has demonstrated potential in mitigating AVH, the precise mechanisms by which it operates remain obscure. This study aimed to investigate alternations in structural connectivity and functional connectivity (SC-FC) coupling among schizophrenia patients with AVH prior to and following treatment with 1 Hz rTMS that specifically targets the left temporoparietal junction. Initially, patients exhibited significantly reduced macroscopic whole brain level SC-FC coupling compared to healthy controls. Notably, SC-FC coupling increased significantly across multiple networks, including the somatomotor, dorsal attention, ventral attention, frontoparietal control, and default mode networks, following rTMS treatment. Significant alternations in SC-FC coupling were noted in critical nodes comprising the somatomotor network and the default mode network, such as the precentral gyrus and the ventromedial prefrontal cortex, respectively. The alternations in SC-FC coupling exhibited a correlation with the amelioration of clinical symptom. The results of our study illuminate the intricate relationship between white matter structures and neuronal activity in patients who are receiving low-frequency rTMS. This advances our understanding of the foundational mechanisms underlying rTMS treatment for AVH.
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Affiliation(s)
- Yuanjun Xie
- Military Medical Psychology SchoolFourth Military Medical UniversityXi'anChina
- Department of Radiology, Xijing HospitalFourth Military Medical UniversityXi'anChina
| | - Chenxi Li
- Military Medical Psychology SchoolFourth Military Medical UniversityXi'anChina
| | - Muzhen Guan
- Department of Mental HealthXi'an Medical CollegeXi'anChina
| | - Tian Zhang
- Military Medical Psychology SchoolFourth Military Medical UniversityXi'anChina
| | - Chaozong Ma
- Military Medical Psychology SchoolFourth Military Medical UniversityXi'anChina
| | - Zhongheng Wang
- Department of Psychiatry, Xijing HospitalFourth Military Medical UniversityXi'anChina
| | - Zhujing Ma
- Military Medical Psychology SchoolFourth Military Medical UniversityXi'anChina
| | - Huaning Wang
- Department of Psychiatry, Xijing HospitalFourth Military Medical UniversityXi'anChina
| | - Peng Fang
- Military Medical Psychology SchoolFourth Military Medical UniversityXi'anChina
- Shaanxi Provincial Key Laboratory of Bioelectromagnetic Detection and Intelligent PerceptionXi'anChina
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Voineskos AN, Hawco C, Neufeld NH, Turner JA, Ameis SH, Anticevic A, Buchanan RW, Cadenhead K, Dazzan P, Dickie EW, Gallucci J, Lahti AC, Malhotra AK, Öngür D, Lencz T, Sarpal DK, Oliver LD. Functional magnetic resonance imaging in schizophrenia: current evidence, methodological advances, limitations and future directions. World Psychiatry 2024; 23:26-51. [PMID: 38214624 PMCID: PMC10786022 DOI: 10.1002/wps.21159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/13/2024] Open
Abstract
Functional neuroimaging emerged with great promise and has provided fundamental insights into the neurobiology of schizophrenia. However, it has faced challenges and criticisms, most notably a lack of clinical translation. This paper provides a comprehensive review and critical summary of the literature on functional neuroimaging, in particular functional magnetic resonance imaging (fMRI), in schizophrenia. We begin by reviewing research on fMRI biomarkers in schizophrenia and the clinical high risk phase through a historical lens, moving from case-control regional brain activation to global connectivity and advanced analytical approaches, and more recent machine learning algorithms to identify predictive neuroimaging features. Findings from fMRI studies of negative symptoms as well as of neurocognitive and social cognitive deficits are then reviewed. Functional neural markers of these symptoms and deficits may represent promising treatment targets in schizophrenia. Next, we summarize fMRI research related to antipsychotic medication, psychotherapy and psychosocial interventions, and neurostimulation, including treatment response and resistance, therapeutic mechanisms, and treatment targeting. We also review the utility of fMRI and data-driven approaches to dissect the heterogeneity of schizophrenia, moving beyond case-control comparisons, as well as methodological considerations and advances, including consortia and precision fMRI. Lastly, limitations and future directions of research in the field are discussed. Our comprehensive review suggests that, in order for fMRI to be clinically useful in the care of patients with schizophrenia, research should address potentially actionable clinical decisions that are routine in schizophrenia treatment, such as which antipsychotic should be prescribed or whether a given patient is likely to have persistent functional impairment. The potential clinical utility of fMRI is influenced by and must be weighed against cost and accessibility factors. Future evaluations of the utility of fMRI in prognostic and treatment response studies may consider including a health economics analysis.
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Affiliation(s)
- Aristotle N Voineskos
- Campbell Family Mental Health Research Institute and Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Colin Hawco
- Campbell Family Mental Health Research Institute and Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Nicholas H Neufeld
- Campbell Family Mental Health Research Institute and Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Jessica A Turner
- Department of Psychiatry and Behavioral Health, Wexner Medical Center, Ohio State University, Columbus, OH, USA
| | - Stephanie H Ameis
- Campbell Family Mental Health Research Institute and Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
- Cundill Centre for Child and Youth Depression and McCain Centre for Child, Youth and Family Mental Health, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Alan Anticevic
- Interdepartmental Neuroscience Program, Yale University, New Haven, CT, USA
- Department of Psychiatry, Yale University, New Haven, CT, USA
| | - Robert W Buchanan
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Kristin Cadenhead
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Paola Dazzan
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Erin W Dickie
- Campbell Family Mental Health Research Institute and Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Julia Gallucci
- Campbell Family Mental Health Research Institute and Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
| | - Adrienne C Lahti
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Anil K Malhotra
- Institute for Behavioral Science, Feinstein Institutes for Medical Research, Manhasset, NY, USA
- Department of Psychiatry, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
- Department of Molecular Medicine, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
- Department of Psychiatry, Zucker Hillside Hospital Division of Northwell Health, Glen Oaks, NY, USA
| | - Dost Öngür
- McLean Hospital/Harvard Medical School, Belmont, MA, USA
| | - Todd Lencz
- Institute for Behavioral Science, Feinstein Institutes for Medical Research, Manhasset, NY, USA
- Department of Psychiatry, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
- Department of Molecular Medicine, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
- Department of Psychiatry, Zucker Hillside Hospital Division of Northwell Health, Glen Oaks, NY, USA
| | - Deepak K Sarpal
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Lindsay D Oliver
- Campbell Family Mental Health Research Institute and Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
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Fan L, Li Y, Huang ZG, Zhang W, Wu X, Liu T, Wang J. Low-frequency repetitive transcranial magnetic stimulation alters the individual functional dynamical landscape. Cereb Cortex 2023; 33:9583-9598. [PMID: 37376783 DOI: 10.1093/cercor/bhad228] [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: 04/26/2023] [Revised: 06/05/2023] [Accepted: 06/06/2023] [Indexed: 06/29/2023] Open
Abstract
Repetitive transcranial magnetic stimulation (rTMS) is a noninvasive approach to modulate brain activity and behavior in humans. Still, how individual resting-state brain dynamics after rTMS evolves across different functional configurations is rarely studied. Here, using resting state fMRI data from healthy subjects, we aimed to examine the effects of rTMS to individual large-scale brain dynamics. Using Topological Data Analysis based Mapper approach, we construct the precise dynamic mapping (PDM) for each participant. To reveal the relationship between PDM and canonical functional representation of the resting brain, we annotated the graph using relative activation proportion of a set of large-scale resting-state networks (RSNs) and assigned the single brain volume to corresponding RSN-dominant or a hub state (not any RSN was dominant). Our results show that (i) low-frequency rTMS could induce changed temporal evolution of brain states; (ii) rTMS didn't alter the hub-periphery configurations underlined resting-state brain dynamics; and (iii) the rTMS effects on brain dynamics differ across the left frontal and occipital lobe. In conclusion, low-frequency rTMS significantly alters the individual temporo-spatial dynamics, and our finding further suggested a potential target-dependent alteration of brain dynamics. This work provides a new perspective to comprehend the heterogeneous effect of rTMS.
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Affiliation(s)
- Liming Fan
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitation Science, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
- National Engineering Research Center of Health Care and Medical Devices, Guangzhou, Guangdong 510500, China
| | - Youjun Li
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitation Science, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
- National Engineering Research Center of Health Care and Medical Devices, Guangzhou, Guangdong 510500, China
| | - Zi-Gang Huang
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitation Science, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
- National Engineering Research Center of Health Care and Medical Devices, Guangzhou, Guangdong 510500, China
| | - Wenlong Zhang
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitation Science, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
- National Engineering Research Center of Health Care and Medical Devices, Guangzhou, Guangdong 510500, China
| | - Xiaofeng Wu
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitation Science, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
- National Engineering Research Center of Health Care and Medical Devices, Guangzhou, Guangdong 510500, China
| | - Tian Liu
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitation Science, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
- National Engineering Research Center of Health Care and Medical Devices, Guangzhou, Guangdong 510500, China
| | - Jue Wang
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitation Science, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
- National Engineering Research Center of Health Care and Medical Devices, Guangzhou, Guangdong 510500, China
- The Key Laboratory of Neuro-Informatics & Rehabilitation Engineering of Ministry of Civil Affairs, Xi'an, Shaanxi 710049, China
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Battaglia S, Schmidt A, Hassel S, Tanaka M. Editorial: Case reports in neuroimaging and stimulation. Front Psychiatry 2023; 14:1264669. [PMID: 37599881 PMCID: PMC10433894 DOI: 10.3389/fpsyt.2023.1264669] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Accepted: 07/24/2023] [Indexed: 08/22/2023] Open
Affiliation(s)
- Simone Battaglia
- Center for Studies and Research in Cognitive Neuroscience, Department of Psychology “Renzo Canestrari”, Alma Mater Studiorum Università di Bologna, Cesena, Italy
| | - André Schmidt
- Department of Psychiatry (UPK), University of Basel, Basel, Switzerland
| | - Stefanie Hassel
- Department of Psychiatry, Mathison Centre for Mental Health Research and Education, University of Calgary, Calgary, AB, Canada
| | - Masaru Tanaka
- ELKH-SZTE Neuroscience Research Group, Danube Neuroscience Research Laboratory, Eötvös Loránd Research Network, University of Szeged (ELKH-SZTE), Szeged, Hungary
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