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Wu J, Yang J, Yuan Z, Zhang J, Zhang Z, Qin T, Li X, Deng H, Gong L. Functional connectome gradient predicts clinical symptoms of chronic insomnia disorder. Prog Neuropsychopharmacol Biol Psychiatry 2024; 135:111120. [PMID: 39154930 DOI: 10.1016/j.pnpbp.2024.111120] [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: 05/29/2024] [Revised: 07/30/2024] [Accepted: 08/15/2024] [Indexed: 08/20/2024]
Abstract
Insomnia is the second most prevalent psychiatric disorder worldwide, but the understanding of the pathophysiology of insomnia remains fragmented. In this study, we calculated the connectome gradient in 50 chronic insomnia disorder (CID) patients and 38 healthy controls (HC) to assess changes due to insomnia and utilized these gradients in a connectome-based predictive modeling (CPM) to predict clinical symptoms associated with insomnia. The results suggested that insomnia led to significant alterations in the functional gradients of some brain areas. Specifically, the gradient scores in the middle frontal gyrus, superior anterior cingulate gyrus, and right nucleus accumbens were significantly higher in the CID patients than in the HC group, whereas the scores in the middle occipital gyrus, right fusiform gyrus, and right postcentral gyrus were significantly lower than in the HC group. Further correlation analysis revealed that the right middle frontal gyrus is positively correlated with the self-rating anxiety scale (r=0.3702). Additionally, the prediction model built with functional gradients could well predict the sleep quality (r=0.5858), anxiety (r=0.6150), and depression (r=0.4022) levels of insomnia patients. This offers an objective depiction of the clinical diagnosis of insomnia, yielding a beneficial impact on the identification of effective biomarkers and the comprehension of insomnia.
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Affiliation(s)
- Jiahui Wu
- College of Nuclear Technology and Automation Engineering, Chengdu University of Technology, Chengdu, China
| | - Jianbo Yang
- Sichuan University of Science and Engineering, Zigong, China
| | - Zhen Yuan
- Bioimaging Core, Faculty of Health Sciences, University of Macau, Macau, SAR China
| | - Jiang Zhang
- College of Electrical Engineering, Sichuan University, Chengdu, China.
| | - Zhiwei Zhang
- College of Electrical Engineering, Sichuan University, Chengdu, China
| | - Tianwei Qin
- College of Electrical Engineering, Sichuan University, Chengdu, China
| | - Xiaoxuan Li
- College of Electrical Engineering, Sichuan University, Chengdu, China
| | - Hanbin Deng
- Sichuan Institute of Computer Sciences, Chengdu, China.
| | - Liang Gong
- Department of Neurology, Chengdu Second People's Hospital, Chengdu, China.
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2
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Fan Y, White SR. Review of weighted exponential random graph models frameworks applied to neuroimaging. Stat Med 2024; 43:3881-3898. [PMID: 38932498 DOI: 10.1002/sim.10162] [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: 10/24/2023] [Revised: 05/15/2024] [Accepted: 06/16/2024] [Indexed: 06/28/2024]
Abstract
Neuro-imaging data can often be represented as statistical networks, especially for functional magnetic resonance imaging (fMRI) data, where brain regions are defined as nodes and the functional interactions between those regions are taken as edges. Such networks are commonly divided into classes depending on the type of edges, namely binary or weighted. A binary network means edges can either be present or absent. Whereas the edges of a weighted network are associated with weight values, and fMRI networks belong to weighted networks. Statistical methods are often adopted to analyse such networks, among which, the exponential random graph model (ERGM) is an important network analysis approach. Typically ERGMs are applied to binary networks, and weighted networks often need to be binarised by arbitrarily selecting a threshold value to define the presence of the edges, which can lead to non-robustness and loss of valuable edge weight information representing the strength of fMRI interaction in fMRI networks. While it is therefore important to gain deeper insight in adopting ERGM on weighted networks, there only exists a few different ERGM frameworks for weighted networks; some of these are not directly implementable on fMRI networks based on their original proposal. We systematically review, implement, analyse and compare five such frameworks via a simulation study and provide guidelines on each modelling framework as well as conclude the suitability of them on fMRI networks based on a range of criteria. We concluded that Multi-Layered ERGM is currently the most suitable framework.
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Affiliation(s)
- Yefeng Fan
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
| | - Simon R White
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
- Department of Psychiatry, University of Cambridge, Cambridge, UK
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3
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Siva K, Ponnusamy P, Ramanathan M. Disrupted Brain Network Measures in Parkinson's Disease Patients with Severe Hyposmia and Cognitively Normal Ability. Brain Sci 2024; 14:685. [PMID: 39061425 PMCID: PMC11274763 DOI: 10.3390/brainsci14070685] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2024] [Revised: 06/30/2024] [Accepted: 07/04/2024] [Indexed: 07/28/2024] Open
Abstract
Neuroscience has revolved around brain structural changes, functional activity, and connectivity alteration in Parkinson's Disease (PD); however, how the network topology organization becomes altered is still unclear, specifically in Parkinson's patients with severe hyposmia. In this study, we have examined the functional network topological alteration in patients affected by Parkinson's Disease with normal cognitive ability (ODN), Parkinson's Disease with severe hyposmia (ODP), and healthy controls (HCs) using resting-state functional magnetic resonance imaging (rsfMRI) data. We have analyzed brain topological organization using popular graph measures such as network segregation (clustering coefficient, modularity), network integration (participation coefficient, path length), small-worldness, efficiency, centrality, and assortativity. Then, we used a feature ranking approach based on the diagonal adaptation of neighborhood component analysis, aiming to determine a graph measure that is sensitive enough to distinguish between these three different groups. We noted significantly lower segregation and local efficiency and small-worldness in ODP compared to ODN and HCs. On the contrary, we did not find differences in network integration in ODP compared to ODN and HCs, which indicates that the brain network becomes fragmented in ODP. At the brain network level, a progressive increase in the DMN (Default Mode Network) was observed from healthy controls to ODN to ODP, and a continuous decrease in the cingulo-opercular network was observed from healthy controls to ODN to ODP. Further, the feature ranking approach has shown that the whole-brain clustering coefficient and small-worldness are sensitive measures to classify ODP vs. ODN, as well as HCs. Looking at the brain regional network segregation, we have found that the cerebellum and limbic, fronto-parietal, and occipital lobes have higher ODP reductions than ODN and HCs. Our results suggest network topological measures, specifically whole-brain segregation and small-worldness decreases. At the network level, an increase in DMN and a decrease in the cingulo-opercular network could be used as biomarkers to characterize ODN and ODP.
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Affiliation(s)
| | | | - Malmathanraj Ramanathan
- Department of Electronics and Communication Engineering, National Institute of Technology, Tiruchirappalli 620015, India; (K.S.); (P.P.)
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Deng S, Tan S, Song X, Lin X, Yang K, Li X. Prediction of disease progression in individuals with subjective cognitive decline using brain network analysis. CNS Neurosci Ther 2024; 30:e14859. [PMID: 39009557 PMCID: PMC11250750 DOI: 10.1111/cns.14859] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2024] [Revised: 06/25/2024] [Accepted: 07/01/2024] [Indexed: 07/17/2024] Open
Abstract
OBJECTIVE The objective of this study is to explore potential differences in brain functional networks at baseline between individuals with progressive subjective cognitive decline (P-SCD) and stable subjective cognitive decline (S-SCD), as well as to identify potential indicators that can effectively distinguish between P-SCD and S-SCD. METHODS Alzheimer's Disease Neuroimaging Initiative (ADNI) database was utilized to enroll SCD individuals with a follow-up period of over 3 years. This study included 39 individuals with S-SCD, 15 individuals with P-SCD, and 45 cognitively normal (CN) individuals. Brain functional networks were constructed based on the AAL template, and graph theory analysis was performed to determine the topological properties. RESULTS For global metric, the S-SCD group exhibited stronger small-worldness with reduced connectivity among nearby nodes and accelerated compensatory information transfer capacity. For nodal efficiency, the S-SCD group showed increased connectivity in bilateral posterior cingulate gyri (PCG). However, for nodal local efficiency, the P-SCD group exhibited significantly reduced connectivity in the right cerebellar Crus I compared with the S-SCD group. CONCLUSION There are differences in brain functional networks at baseline between P-SCD and S-SCD groups. Furthermore, the right cerebellar Crus I region may be a potentially useful brain area to distinguish between P-SCD and S-SCD.
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Affiliation(s)
- Simin Deng
- School of Public Health (Shenzhen)Shenzhen Campus of Sun Yat‐sen UniversityShenzhenGuangdongChina
- Department of Rehabilitation MedicineDongguan Eighth People's HospitalDongguanGuangdongChina
| | - Si Tan
- School of Public Health (Guangzhou)Sun Yat‐sen UniversityGuangzhouGuangdongChina
| | - Xiaojing Song
- School of Public Health (Guangzhou)Sun Yat‐sen UniversityGuangzhouGuangdongChina
| | - Xinyun Lin
- School of Public Health (Shenzhen)Shenzhen Campus of Sun Yat‐sen UniversityShenzhenGuangdongChina
| | - Kaize Yang
- School of Public Health (Shenzhen)Shenzhen Campus of Sun Yat‐sen UniversityShenzhenGuangdongChina
| | - Xiuhong Li
- School of Public Health (Shenzhen)Shenzhen Campus of Sun Yat‐sen UniversityShenzhenGuangdongChina
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5
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Churchill L, Chen YC, Lewis SJG, Matar E. Understanding REM Sleep Behavior Disorder through Functional MRI: A Systematic Review. Mov Disord 2024. [PMID: 38934216 DOI: 10.1002/mds.29898] [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: 02/23/2024] [Revised: 05/08/2024] [Accepted: 06/03/2024] [Indexed: 06/28/2024] Open
Abstract
Neuroimaging studies in rapid eye movement sleep behavior disorder (RBD) can inform fundamental questions about the pathogenesis of Parkinson's disease (PD). Across modalities, functional magnetic resonance imaging (fMRI) may be better suited to identify changes between neural networks in the earliest stages of Lewy body diseases when structural changes may be subtle or absent. This review synthesizes the findings from all fMRI studies of RBD to gain further insight into the pathophysiology and progression of Lewy body diseases. A total of 32 studies were identified using a systematic review conducted according to PRISMA guidelines between January 2000 to February 2024 for original fMRI studies in patients with either isolated RBD (iRBD) or RBD secondary to PD. Common functional alterations were detectable in iRBD patients compared with healthy controls across brainstem nuclei, basal ganglia, frontal and occipital lobes, and whole brain network measures. Patients with established PD and RBD demonstrated decreased functional connectivity across the whole brain and brainstem nuclei, but increased functional connectivity in the cerebellum and frontal lobe compared with those PD patients without RBD. Finally, longitudinal changes in resting state functional connectivity were found to track with disease progression. Currently, fMRI studies in RBD have demonstrated early signatures of neurodegeneration across both motor and non-motor pathways. Although more work is needed, such findings have the potential to inform our understanding of disease, help to distinguish between prodromal PD and prodromal dementia with Lewy bodies, and support the development of fMRI-based outcome measures of phenoconversion and progression in future disease modifying trials. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Lachlan Churchill
- Central Clinical School, Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia
| | - Yu-Chi Chen
- Brain Dynamic Centre, Westmead Institute for Medical Research, Westmead, New South Wales, Australia
| | - Simon J G Lewis
- Macquarie Medical School and Macquarie University Centre for Parkinson's Disease Research, Faculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, New South Wales, Australia
| | - Elie Matar
- Central Clinical School, Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia
- Centre for Integrated Research and Understanding of Sleep (CIRUS), Woolcock Institute of Medical Research, Sydney, New South Wales, Australia
- Department of Neurology, Royal Prince Alfred Hospital, Sydney, New South Wales, Australia
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6
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Chopra S, Cocuzza CV, Lawhead C, Ricard JA, Labache L, Patrick LM, Kumar P, Rubenstein A, Moses J, Chen L, Blankenbaker C, Gillis B, Germine LT, Harpaz-Rote I, Yeo BTT, Baker JT, Holmes AJ. The Transdiagnostic Connectome Project: a richly phenotyped open dataset for advancing the study of brain-behavior relationships in psychiatry. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.06.18.24309054. [PMID: 38946958 PMCID: PMC11213088 DOI: 10.1101/2024.06.18.24309054] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/02/2024]
Abstract
An important aim in psychiatry is the establishment of valid and reliable associations linking profiles of brain functioning to clinically relevant symptoms and behaviors across patient populations. To advance progress in this area, we introduce an open dataset containing behavioral and neuroimaging data from 241 individuals aged 18 to 70, comprising 148 individuals meeting diagnostic criteria for a broad range of psychiatric illnesses and a healthy comparison group of 93 individuals. These data include high-resolution anatomical scans, multiple resting-state, and task-based functional MRI runs. Additionally, participants completed over 50 psychological and cognitive assessments. Here, we detail available behavioral data as well as raw and processed MRI derivatives. Associations between data processing and quality metrics, such as head motion, are reported. Processed data exhibit classic task activation effects and canonical functional network organization. Overall, we provide a comprehensive and analysis-ready transdiagnostic dataset, which we hope will accelerate the identification of illness-relevant features of brain functioning, enabling future discoveries in basic and clinical neuroscience.
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Affiliation(s)
- Sidhant Chopra
- 1. Department of Psychology, Yale University, New Haven, CT, USA
- 2. Department of Psychiatry, Brain Health Institute, Rutgers University, Piscataway, NJ, USA
- 3. Orygen, Center for Youth Mental Health, University of Melbourne, Melbourne, Australia
| | - Carrisa V. Cocuzza
- 1. Department of Psychology, Yale University, New Haven, CT, USA
- 2. Department of Psychiatry, Brain Health Institute, Rutgers University, Piscataway, NJ, USA
| | - Connor Lawhead
- 1. Department of Psychology, Yale University, New Haven, CT, USA
- 4. Department of Psychology, Stony Brook University, Stony Brook, NY, USA
| | - Jocelyn A. Ricard
- 1. Department of Psychology, Yale University, New Haven, CT, USA
- 5. Stanford Neurosciences Interdepartmental Program, Stanford University School of Medicine, Stanford, CA, USA
| | - Loïc Labache
- 1. Department of Psychology, Yale University, New Haven, CT, USA
- 2. Department of Psychiatry, Brain Health Institute, Rutgers University, Piscataway, NJ, USA
| | - Lauren M. Patrick
- 1. Department of Psychology, Yale University, New Haven, CT, USA
- 6. Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA
- 7. Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Poornima Kumar
- 8. Department of Psychiatry, Harvard Medical School, Boston, USA
- 9. Centre for Depression, Anxiety and Stress Research, McLean Hospital, Boston, USA
| | | | - Julia Moses
- 1. Department of Psychology, Yale University, New Haven, CT, USA
| | - Lia Chen
- 10. Department of Psychology, Cornell University, Ithaca, NY, USA
| | | | - Bryce Gillis
- 11. Institute for Technology in Psychiatry, McLean Hospital, Boston, USA
- 12. Department of Psychiatry, Harvard Medical School, Boston, USA
| | - Laura T. Germine
- 11. Institute for Technology in Psychiatry, McLean Hospital, Boston, USA
- 12. Department of Psychiatry, Harvard Medical School, Boston, USA
| | - Ilan Harpaz-Rote
- 1. Department of Psychology, Yale University, New Haven, CT, USA
- 13. Department of Psychiatry, Yale University, New Haven, USA
- 14. Wu Tsai Institute, Yale University, New Haven, USA
| | - BT Thomas Yeo
- 15. Centre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- 16. Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore
- 17. N.1 Institute for Health National University of Singapore, Singapore, Singapore
- 18. Department of Medicine, Human Potential Translational Research Programme & Institute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- 19. Integrative Sciences and Engineering Programme (ISEP), National University of Singapore, Singapore, Singapore
- 20. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, USA
| | - Justin T. Baker
- 11. Institute for Technology in Psychiatry, McLean Hospital, Boston, USA
- 12. Department of Psychiatry, Harvard Medical School, Boston, USA
| | - Avram J. Holmes
- 1. Department of Psychology, Yale University, New Haven, CT, USA
- 2. Department of Psychiatry, Brain Health Institute, Rutgers University, Piscataway, NJ, USA
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Dannhauer M, Gomez LJ, Robins PL, Wang D, Hasan NI, Thielscher A, Siebner HR, Fan Y, Deng ZD. Electric Field Modeling in Personalizing Transcranial Magnetic Stimulation Interventions. Biol Psychiatry 2024; 95:494-501. [PMID: 38061463 PMCID: PMC10922371 DOI: 10.1016/j.biopsych.2023.11.022] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Revised: 11/21/2023] [Accepted: 11/25/2023] [Indexed: 01/21/2024]
Abstract
The modeling of transcranial magnetic stimulation (TMS)-induced electric fields (E-fields) is a versatile technique for evaluating and refining brain targeting and dosing strategies, while also providing insights into dose-response relationships in the brain. This review outlines the methodologies employed to derive E-field estimations, covering TMS physics, modeling assumptions, and aspects of subject-specific head tissue and coil modeling. We also summarize various numerical methods for solving the E-field and their suitability for various applications. Modeling methodologies have been optimized to efficiently execute numerous TMS simulations across diverse scalp coil configurations, facilitating the identification of optimal setups or rapid cortical E-field visualization for specific brain targets. These brain targets are extrapolated from neurophysiological measurements and neuroimaging, enabling precise and individualized E-field dosing in experimental and clinical applications. This necessitates the quantification of E-field estimates using metrics that enable the comparison of brain target engagement, functional localization, and TMS intensity adjustments across subjects. The integration of E-field modeling with empirical data has the potential to uncover pivotal insights into the aspects of E-fields responsible for stimulating and modulating brain function and states, enhancing behavioral task performance, and impacting the clinical outcomes of personalized TMS interventions.
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Affiliation(s)
- Moritz Dannhauer
- Computational Neurostimulation Research Program, Noninvasive Neuromodulation Unit, Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, Bethesda, Maryland
| | - Luis J Gomez
- School of Electrical and Computer Engineering, Purdue University, West Lafayette, Indiana
| | - Pei L Robins
- Computational Neurostimulation Research Program, Noninvasive Neuromodulation Unit, Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, Bethesda, Maryland
| | - Dezhi Wang
- School of Electrical and Computer Engineering, Purdue University, West Lafayette, Indiana
| | - Nahian I Hasan
- School of Electrical and Computer Engineering, Purdue University, West Lafayette, Indiana
| | - Axel Thielscher
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark; Department of Health Technology, Technical University of Denmark, Kongens Lyngby, Denmark
| | - Hartwig R Siebner
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark; Department of Neurology, Copenhagen University Hospital Bispebjerg, Copenhagen, Denmark; Institute for Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Yong Fan
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Zhi-De Deng
- Computational Neurostimulation Research Program, Noninvasive Neuromodulation Unit, Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, Bethesda, Maryland.
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8
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Wang XK, Yang C, Dong WQ, Zhang QR, Ma SZ, Zang YF, Yuan LX. Impaired segregation of the attention deficit hyperactivity disorder related pattern in children. J Psychiatr Res 2024; 170:111-121. [PMID: 38134720 DOI: 10.1016/j.jpsychires.2023.12.018] [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: 08/11/2023] [Revised: 12/05/2023] [Accepted: 12/10/2023] [Indexed: 12/24/2023]
Abstract
BACKGROUND Inattention is a key characteristic of attention deficit hyperactivity disorder (ADHD). Specific brain abnormalities associated with this symptom form a discernible pattern related with ADHD in children (i.e., ADHD related pattern) in our earlier research. The developmental processes of segregation and integration may be crucial to ADHD. However, how brains reconfigure these processes of the ADHD related pattern in different subtypes of ADHD and across sexes remain unclear. METHODS Nested-spectral partition method was applied to identify effects of subtype and sex on segregation and integration of the ADHD related pattern, using 145 ADHD patients and 135 typically developing controls (TDC) aged 7-14. Relationships between the measures and inattention symptoms were also investigated. RESULTS Children with ADHD exhibited lower segregation of the ADHD related pattern (p = 1.17 × 10-8) than TDCs. Only the main effect of subtype was significant (p = 1.14 × 10-5). Both ADHD-C (p = 2.16 × 10-6) and ADHD-I (p = 2.87 × 10-6) patients had lower segregation components relative to the TDC. Moreover, segregation components were negatively correlated with inattention scores. CONCLUSIONS This study identified impaired segregation in the ADHD related pattern of children with ADHD and found shared neural bases among different subtypes and sexes.
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Affiliation(s)
- Xing-Ke Wang
- Center for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, China; Jing Hengyi School of Education, Hangzhou Normal University, Hangzhou, China
| | - Chen Yang
- Center for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, China; Institute of Psychological Sciences, Hangzhou Normal University, Hangzhou, Zhejiang, China; Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou, Zhejiang, China
| | - Wen-Qiang Dong
- Center for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, China; Institute of Psychological Sciences, Hangzhou Normal University, Hangzhou, Zhejiang, China; Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou, Zhejiang, China
| | - Qiu-Rong Zhang
- Center for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, China; Institute of Psychological Sciences, Hangzhou Normal University, Hangzhou, Zhejiang, China; Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou, Zhejiang, China
| | - Sheng-Zhi Ma
- Center for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, China; Institute of Psychological Sciences, Hangzhou Normal University, Hangzhou, Zhejiang, China; Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou, Zhejiang, China
| | - Yu-Feng Zang
- Center for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, China; Institute of Psychological Sciences, Hangzhou Normal University, Hangzhou, Zhejiang, China; Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou, Zhejiang, China; TMS Center, Deqing Hospital of Hangzhou Normal University, Deqing, Zhejiang, China
| | - Li-Xia Yuan
- School of Physics, Zhejiang University, Hangzhou, China.
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9
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Wang H, Zhan X, Xu J, Yu M, Guo Z, Zhou G, Ren J, Zhang R, Liu W. Disrupted topologic efficiency of brain functional connectome in de novo Parkinson's disease with depression. Eur J Neurosci 2023; 58:4371-4383. [PMID: 37857484 DOI: 10.1111/ejn.16176] [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: 08/13/2023] [Revised: 09/23/2023] [Accepted: 10/05/2023] [Indexed: 10/21/2023]
Abstract
Growing evidence supports that depression in Parkinson's disease (PD) depends on disruptions in specific neural networks rather than regional dysfunction. According to the resting-state functional magnetic resonance imaging data, the study attempted to decipher the alterations in the topological properties of brain networks in de novo depression in PD (DPD). The study also explored the neural network basis for depressive symptoms in PD. We recruited 20 DPD, 37 non-depressed PD and 41 healthy controls (HC). The Graph theory and network-based statistical methods helped analyse the topological properties of brain functional networks and anomalous subnetworks across these groups. The relationship between altered properties and depression severity was also investigated. DPD revealed significantly reduced nodal efficiency in the left superior temporal gyrus. Additionally, DPD decreased five hubs, primarily located in the temporal-occipital cortex, and increased seven hubs, mainly distributed in the limbic cortico-basal ganglia circuit. The betweenness centrality of the left Medio Ventral Occipital Cortex was positively associated with depressive scores in DPD. In contrast to HC, DPD had a multi-connected subnetwork with significantly lower connectivity, primarily distributed in the visual, somatomotor, dorsal attention and default networks. Regional topological disruptions in the temporal-occipital region are critical in the DPD neurological mechanism. It might suggest a potential network biomarker among newly diagnosed DPD patients.
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Affiliation(s)
- Hui Wang
- Department of Neurology, Lianyungang Hospital of Traditional Chinese Medicine, Lianyungang Affiliated Hospital of Nanjing University of Chinese Medicine, Lianyungang, China
| | - Xiaoyan Zhan
- Department of Clinical Laboratory, Jiangsu Province Hospital of Traditional Chinese Medicine, Nanjing, China
| | - Jianxia Xu
- Department of Neurology, Dushu Lake Hospital Affiliated to Soochow University, Suzhou, China
| | - Miao Yu
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Zhiying Guo
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Gaiyan Zhou
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Jingru Ren
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Ronggui Zhang
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Weiguo Liu
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
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10
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Baxter LC, Limback-Stokin M, Patten KJ, Arreola AC, Locke DE, Hu L, Zhou Y, Caselli RJ. Hippocampal connectivity and memory decline in cognitively intact APOE ε4 carriers. Alzheimers Dement 2023; 19:3806-3814. [PMID: 36906845 PMCID: PMC11105018 DOI: 10.1002/alz.13023] [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: 08/24/2022] [Revised: 02/06/2023] [Accepted: 02/07/2023] [Indexed: 03/13/2023]
Abstract
INTRODUCTION Resting-state functional magnetic resonance imaging (fMRI) graph theory may help detect subtle functional connectivity changes affecting memory prior to impairment. METHODS Cognitively normal apolipoprotein E (APOE) ε4 carriers/noncarriers underwent longitudinal cognitive assessment and one-time MRI. The relationship of left/right hippocampal connectivity and memory trajectory were compared between carriers/noncarriers. RESULTS Steepness of verbal memory decline correlated with decreased connectivity in the left hippocampus, only among APOE ε4 carriers. Right hippocampal metrics were not correlated with memory and there were no significant correlations in the noncarriers. Verbal memory decline correlated with left hippocampal volume loss for both carriers and noncarriers, with no other significant volumetric findings. DISCUSSION Findings support early hippocampal dysfunction in intact carriers, the AD disconnection hypothesis, and left hippocampal dysfunction earlier than the right. Combining lateralized graph theoretical metrics with a sensitive measure of memory trajectory allowed for detection of early-stage changes in APOE ε4 carriers before symptoms of mild cognitive impairment are present. HIGHLIGHTS Graph theory connectivity detects preclinical hippocampal changes in APOE ε4 carriers. The AD disconnection hypothesis was supported in unimpaired APOE ε4 carriers. Hippocampal dysfunction starts asymmetrically on the left.
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Affiliation(s)
- Leslie C. Baxter
- Department of Psychiatry and Psychology, Mayo Clinic Arizona, Phoenix, Arizona, USA
| | | | - K. Jakob Patten
- Department of Speech and Hearing Sciences, Tempe, Arizona, 85281 USA
| | | | - Dona E.C. Locke
- Department of Psychiatry and Psychology, Mayo Clinic Arizona, Phoenix, Arizona, USA
| | - Leland Hu
- Department of Radiology, Mayo Clinic Arizona, Phoenix, Arizona, 85054 USA
| | - Yuxiang Zhou
- Department of Medical Physics, Mayo Clinic Arizona, Phoenix, Arizona, 85054 USA
| | - Richard J. Caselli
- Department of Neurology, Mayo Clinic Arizona, Phoenix, Arizona, 85259 USA
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Smith DD, Meca A, Bottenhorn KL, Bartley JE, Riedel MC, Salo T, Peraza JA, Laird RW, Pruden SM, Sutherland MT, Brewe E, Laird AR. Task-based attentional and default mode connectivity associated with science and math anxiety profiles among university physics students. Trends Neurosci Educ 2023; 32:100204. [PMID: 37689430 PMCID: PMC10501206 DOI: 10.1016/j.tine.2023.100204] [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: 11/15/2022] [Revised: 05/15/2023] [Accepted: 05/24/2023] [Indexed: 09/11/2023]
Abstract
PURPOSE Attentional control theory (ACT) posits that elevated anxiety increases the probability of re-allocating cognitive resources needed to complete a task to processing anxiety-related stimuli. This process impairs processing efficiency and can lead to reduced performance effectiveness. Science, technology, engineering, and math (STEM) students frequently experience anxiety about their coursework, which can interfere with learning and performance and negatively impact student retention and graduation rates. The objective of this study was to extend the ACT framework to investigate the neurobiological associations between science and math anxiety and cognitive performance among 123 physics undergraduate students. PROCEDURES Latent profile analysis (LPA) identified four profiles of science and math anxiety among STEM students, including two profiles that represented the majority of the sample (Low Science and Math Anxiety; 59.3% and High Math Anxiety; 21.9%) and two additional profiles that were not well represented (High Science and Math Anxiety; 6.5% and High Science Anxiety; 4.1%). Students underwent a functional magnetic resonance imaging (fMRI) session in which they performed two tasks involving physics cognition: the Force Concept Inventory (FCI) task and the Physics Knowledge (PK) task. FINDINGS No significant differences were observed in FCI or PK task performance between High Math Anxiety and Low Science and Math Anxiety students. During the three phases of the FCI task, we found no significant brain connectivity differences during scenario and question presentation, yet we observed significant differences during answer selection within and between the dorsal attention network (DAN), ventral attention network (VAN), and default mode network (DMN). Further, we found significant group differences during the PK task were limited to the DAN, including DAN-VAN and within-DAN connectivity. CONCLUSIONS These results highlight the different cognitive processes required for physics conceptual reasoning compared to physics knowledge retrieval, provide new insight into the underlying brain dynamics associated with anxiety and physics cognition, and confirm the relevance of ACT theory for science and math anxiety.
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Affiliation(s)
- Donisha D Smith
- Department of Psychology, Florida International University, Miami, FL, United States of America.
| | - Alan Meca
- Department of Psychology, University of Texas San Antonio, San Antonio, United States of America
| | - Katherine L Bottenhorn
- Department of Population and Public Health Sciences, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, United States of America
| | - Jessica E Bartley
- Department of Physics, Florida International University, Miami, FL, United States of America
| | - Michael C Riedel
- Department of Physics, Florida International University, Miami, FL, United States of America
| | - Taylor Salo
- Department of Psychology, Florida International University, Miami, FL, United States of America
| | - Julio A Peraza
- Department of Physics, Florida International University, Miami, FL, United States of America
| | - Robert W Laird
- Department of Physics, Florida International University, Miami, FL, United States of America
| | - Shannon M Pruden
- Department of Psychology, Florida International University, Miami, FL, United States of America
| | - Matthew T Sutherland
- Department of Psychology, Florida International University, Miami, FL, United States of America
| | - Eric Brewe
- Department of Physics, Drexel University, Philadelphia, PA, United States of America
| | - Angela R Laird
- Department of Physics, Florida International University, Miami, FL, United States of America
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12
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Wu Q, Lei H, Mao T, Deng Y, Zhang X, Jiang Y, Zhong X, Detre JA, Liu J, Rao H. Test-Retest Reliability of Resting Brain Small-World Network Properties across Different Data Processing and Modeling Strategies. Brain Sci 2023; 13:brainsci13050825. [PMID: 37239297 DOI: 10.3390/brainsci13050825] [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: 03/04/2023] [Revised: 05/02/2023] [Accepted: 05/12/2023] [Indexed: 05/28/2023] Open
Abstract
Resting-state functional magnetic resonance imaging (fMRI) with graph theoretical modeling has been increasingly applied for assessing whole brain network topological organization, yet its reproducibility remains controversial. In this study, we acquired three repeated resting-state fMRI scans from 16 healthy controls during a strictly controlled in-laboratory study and examined the test-retest reliability of seven global and three nodal brain network metrics using different data processing and modeling strategies. Among the global network metrics, the characteristic path length exhibited the highest reliability, whereas the network small-worldness performed the poorest. Nodal efficiency was the most reliable nodal metric, whereas betweenness centrality showed the lowest reliability. Weighted global network metrics provided better reliability than binary metrics, and reliability from the AAL90 atlas outweighed those from the Power264 parcellation. Although global signal regression had no consistent effects on the reliability of global network metrics, it slightly impaired the reliability of nodal metrics. These findings provide important implications for the future utility of graph theoretical modeling in brain network analyses.
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Affiliation(s)
- Qianying Wu
- Key Laboratory of Brain-Machine Intelligence for Information Behavior (Ministry of Education and Shanghai), School of Business and Management, Shanghai International Studies University, Shanghai 201613, China
- Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104, USA
- School of Life Sciences, University of Science and Technology of China, Hefei 230026, China
| | - Hui Lei
- Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104, USA
- College of Education, Hunan Agricultural University, Changsha 410127, China
| | - Tianxin Mao
- Key Laboratory of Brain-Machine Intelligence for Information Behavior (Ministry of Education and Shanghai), School of Business and Management, Shanghai International Studies University, Shanghai 201613, China
- Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Yao Deng
- Key Laboratory of Brain-Machine Intelligence for Information Behavior (Ministry of Education and Shanghai), School of Business and Management, Shanghai International Studies University, Shanghai 201613, China
- Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Xiaocui Zhang
- Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104, USA
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha 410017, China
- Medical Psychological Institute, Central South University, Changsha 410017, China
- National Clinical Research Center for Mental Disorders, Changsha 410011, China
| | - Yali Jiang
- Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104, USA
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha 410017, China
| | - Xue Zhong
- Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104, USA
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha 410017, China
| | - John A Detre
- Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Jianghong Liu
- Department of Family and Community Health, School of Nursing, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Hengyi Rao
- Key Laboratory of Brain-Machine Intelligence for Information Behavior (Ministry of Education and Shanghai), School of Business and Management, Shanghai International Studies University, Shanghai 201613, China
- Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104, USA
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13
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Zhang JP, Shen J, Xiang YT, Xing XX, Kang BX, Zhao C, Wu JJ, Zheng MX, Hua XY, Xiao LB, Xu JG. Modulation of Brain Network Topological Properties in Knee Osteoarthritis by Electroacupuncture in Rats. J Pain Res 2023; 16:1595-1605. [PMID: 37220632 PMCID: PMC10200108 DOI: 10.2147/jpr.s406374] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Accepted: 05/02/2023] [Indexed: 05/25/2023] Open
Abstract
Introduction Osteoarthritis is a chronic, ongoing disease that affects patients, and pain is considered a key factor affecting patients, but the brain changes during the development of osteoarthritis pain are currently unclear. In this study, we used electroacupuncture (EA) to intervene the rat model of knee osteoarthritis and analyzed the changes in topological properties of brain networks using graph theory. Methods Sixteen SD rat models of right-knee osteoarthritis with anterior cruciate ligament transection (ACLT) were randomly divided into electroacupuncture intervention group and control group. The electroacupuncture group was intervened on Zusanli (ST36) and Futu (ST32) for 20 min each time, five times a week for 3 weeks, while the control group was applied sham stimulation. Both groups were measured for pain threshold. The small-world properties and node properties of the brain network between the two groups after the intervention were statistically analyzed by graph theory methods. Results The differences are mainly in the changes in node attributes between the two groups, such as degree centrality, betweenness centrality, and so on in different brain regions (P<0.05). Both groups showed no small-world characteristics in the brain networks of the two groups. The mechanical thresholds and thermal pain thresholds were significantly higher in the EA group than in the control group (P<0.05). Conclusion The study demonstrated that electroacupuncture intervention enhanced the activity of nodes related to pain circuit and relieved pain in osteoarthritis, which provides a complementary basis for explaining the effect of electroacupuncture intervention on pain through graphical analysis of changes in brain network topological properties and helps to develop an imaging model for pain affected by electroacupuncture.
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Affiliation(s)
- Jun-Peng Zhang
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, People’s Republic of China
| | - Jun Shen
- Department of Orthopedic, Guanghua Hospital of Integrative Chinese and Western Medicine, Shanghai, People’s Republic of China
- Arthritis Institute of Integrated Traditional Chinese and Western Medicine, Shanghai Academy of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, People’s Republic of China
| | - Yun-Ting Xiang
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, People’s Republic of China
| | - Xiang-Xin Xing
- Department of Rehabilitation Medicine, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, People’s Republic of China
| | - Bing-Xin Kang
- The First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, People’s Republic of China
| | - Chi Zhao
- Department of Orthopedic, Guanghua Hospital of Integrative Chinese and Western Medicine, Shanghai, People’s Republic of China
| | - Jia-Jia Wu
- Department of Rehabilitation Medicine, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, People’s Republic of China
| | - Mou-Xiong Zheng
- Department of Rehabilitation Medicine, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, People’s Republic of China
- Department of Traumatology and Orthopedics, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, People’s Republic of China
| | - Xu-Yun Hua
- Department of Rehabilitation Medicine, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, People’s Republic of China
- Department of Traumatology and Orthopedics, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, People’s Republic of China
| | - Lian-Bo Xiao
- Department of Orthopedic, Guanghua Hospital of Integrative Chinese and Western Medicine, Shanghai, People’s Republic of China
- Arthritis Institute of Integrated Traditional Chinese and Western Medicine, Shanghai Academy of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, People’s Republic of China
| | - Jian-Guang Xu
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, People’s Republic of China
- Department of Rehabilitation Medicine, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, People’s Republic of China
- Engineering Research Center of Traditional Chinese Medicine Intelligent Rehabilitation, Ministry of Education, Shanghai, China
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14
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Dai YR, Wu YK, Chen X, Zeng YW, Li K, Li JT, Su YA, Zhu LL, Yan CG, Si TM. Eight-week antidepressant treatment changes intrinsic functional brain topology in first-episode drug-naïve patients with major depressive disorder. J Affect Disord 2023; 329:225-234. [PMID: 36858265 DOI: 10.1016/j.jad.2023.02.126] [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: 11/15/2022] [Revised: 02/20/2023] [Accepted: 02/22/2023] [Indexed: 03/03/2023]
Abstract
BACKGROUND A recent study revealed disrupted topological organization of whole-brain networks in patients with major depressive disorder (MDD); however, these results were mostly driven by recurrent MDD patients, rather than first-episode drug-naïve (FEDN) patients. Furthermore, few longitudinal studies have explored the effects of antidepressant therapy on the topological organization of whole-brain networks. METHODS We collected clinical and neuroimaging data from 159 FEDN MDD patients and 152 normal controls (NCs). A total of 115 MDD patients completed an eight-week antidepressant treatment procedure. Topological features of brain networks were calculated using graph theory-based methods and compared between FEDN MDD patients and NCs, as well as before and after treatment. RESULTS Decreased global efficiency, local efficiency, small-worldness, and modularity were found in pretreatment FEDN MDD patients compared with NCs. Nodal degrees, betweenness, and efficiency decreased in several networks compared with NCs. After antidepressant treatment, the global efficiency increased, while the local efficiency, the clustering coefficient of the network, the path length, and the normalized characteristic path length decreased. Moreover, the reduction rate of the normalized characteristic path length was positively correlated with the reduction rate of retardation factor scores. LIMITATIONS The interaction effects of groups and time on the topological features were not explored because of absence of the eighth-week data of NC group. CONCLUSIONS The topological architecture of functional brain networks is disrupted in FEDN MDD patients. After antidepressant therapy, the global efficiency shifted toward recovery, but the local efficiency deteriorated, suggesting a correlation between recovery of retardation symptoms and global efficiency.
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Affiliation(s)
- You-Ran Dai
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China
| | - Yan-Kun Wu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China
| | - Xiao Chen
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, China
| | - Ya-Wei Zeng
- PLA Strategic support Force Characteristic Medical Center, Beijing 100101, China
| | - Ke Li
- PLA Strategic support Force Characteristic Medical Center, Beijing 100101, China
| | - Ji-Tao Li
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China
| | - Yun-Ai Su
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China
| | - Lin-Lin Zhu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China.
| | - Chao-Gan Yan
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, China
| | - Tian-Mei Si
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China.
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15
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Skagenholt M, Lyons IM, Skagerlund K, Träff U. Connectome-based predictive modeling indicates dissociable neurocognitive mechanisms for numerical order and magnitude processing in children. Neuropsychologia 2023; 184:108563. [PMID: 37062424 DOI: 10.1016/j.neuropsychologia.2023.108563] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Revised: 03/16/2023] [Accepted: 04/13/2023] [Indexed: 04/18/2023]
Abstract
Symbolic numbers contain information about their relative numerical cardinal magnitude (e.g., 2 < 3) and ordinal placement in the count-list (e.g., 1, 2, 3). Previous research has primarily investigated magnitude discrimination skills and their predictive capacity for math achievement, whereas numerical ordering has been less systematically explored. At approximately 10-12 years of age, numerical order processing skills have been observed to surpass cardinal magnitude discrimination skills as the key predictor of arithmetic ability. The neurocognitive mechanisms underlying this shift remain unclear. To this end, we investigated children's (ages 10-12) neural correlates of numerical order and magnitude discrimination, as well as task-based functional connectomes and their predictive capacity for numeracy-related behavioral outcomes. Results indicated that number discrimination uniquely relied on bilateral temporoparietal correlates, whereas order processing recruited the bilateral IPS, cerebellum, and left premotor cortex. Connectome-based models were not cross-predictive for numerical order and magnitude, suggesting two dissociable mechanisms jointly supported by visuospatial working memory. Neural correlates of learning and memory were predictive of age and arithmetic ability, only for the ordinal task-connectome, indicating that the numerical order mechanism may undergo a developmental shift, dissociating it from mechanisms supporting cardinal number processing.
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Affiliation(s)
- Mikael Skagenholt
- Department of Behavioral Sciences and Learning, Linköping University, Linköping, Sweden; Department of Management and Engineering, JEDI-Lab, Linköping University, Linköping, Sweden.
| | - Ian M Lyons
- Department of Psychology, Georgetown University, Washington D.C, USA
| | - Kenny Skagerlund
- Department of Behavioral Sciences and Learning, Linköping University, Linköping, Sweden; Department of Management and Engineering, JEDI-Lab, Linköping University, Linköping, Sweden; Center for Social and Affective Neuroscience (CSAN), Linköping University, Linköping, Sweden
| | - Ulf Träff
- Department of Behavioral Sciences and Learning, Linköping University, Linköping, Sweden
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16
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Disrupted topological organization of resting-state functional brain networks in Parkinson's disease patients with glucocerebrosidase gene mutations. Neuroradiology 2023; 65:361-370. [PMID: 36269334 DOI: 10.1007/s00234-022-03067-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Accepted: 10/11/2022] [Indexed: 01/25/2023]
Abstract
PURPOSE The mutations of the glucocerebrosidase (GBA) gene are the greatest genetic risk factor for Parkinson's disease (PD). The mechanism underlying the association between GBA mutations and PD has not been fully elucidated. METHODS Using resting-state functional magnetic resonance imaging and graph theory analysis to investigate the disrupted topological organization in PD patients with GBA mutation (GBA-PD). Eleven GBA-PD patients, 11 noncarriers with PD, and 18 healthy controls (HCs) with a similar age and sex distribution were recruited. Individual whole-brain functional connectome was constructed, and the global and nodal topological disruptions were calculated among groups. Partial correlation analyses between the clinical features of patients with PD and topological alterations were performed. RESULTS The GBA-PD group showed prominently decreased characteristic path length (Lp) and increased global efficiency (Eg) compared to HCs at the global level; a significantly increased nodal betweenness centrality in the medial prefrontal cortex (mPFC) and precuneus within the default mode network, and precentral gyrus within the sensorimotor network, while a significantly decreased betweenness centrality in nodes within the cingulo-opercular network compared to the noncarrier group at the regional level. The altered nodal betweenness centrality of mPFC was positively correlated with fatigue severity scale scores in all patients with PD. CONCLUSION The preliminary pilot study found that GBA-PD patients had a higher functional integration at the global level. The nodal result of the mPFC is congruent with the potential fatigue pathology in PD and is suggestive of a profound effect of GBA mutations on the clinical fatigue in patients with PD.
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17
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Spadone S, de Pasquale F, Digiovanni A, Grande E, Pavone L, Sensi SL, Committeri G, Baldassarre A. Dynamic brain states in spatial neglect after stroke. Front Syst Neurosci 2023; 17:1163147. [PMID: 37205053 PMCID: PMC10185806 DOI: 10.3389/fnsys.2023.1163147] [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: 02/10/2023] [Accepted: 04/11/2023] [Indexed: 05/21/2023] Open
Abstract
Previous studies indicated that spatial neglect is characterized by widespread alteration of resting-state functional connectivity and changes in the functional topology of large-scale brain systems. However, whether such network modulations exhibit temporal fluctuations related to spatial neglect is still largely unknown. This study investigated the association between brain states and spatial neglect after the onset of focal brain lesions. A cohort of right-hemisphere stroke patients (n = 20) underwent neuropsychological assessment of neglect as well as structural and resting-state functional MRI sessions within 2 weeks from stroke onset. Brain states were identified using dynamic functional connectivity as estimated by the sliding window approach followed by clustering of seven resting state networks. The networks included visual, dorsal attention, sensorimotor, cingulo-opercular, language, fronto-parietal, and default mode networks. The analyses on the whole cohort of patients, i.e., with and without neglect, identified two distinct brain states characterized by different degrees of brain modularity and system segregation. Compared to non-neglect patients, neglect subjects spent more time in less modular and segregated state characterized by weak intra-network coupling and sparse inter-network interactions. By contrast, patients without neglect dwelt mainly in more modular and segregated states, which displayed robust intra-network connectivity and anti-correlations among task-positive and task-negative systems. Notably, correlational analyses indicated that patients exhibiting more severe neglect spent more time and dwelt more often in the state featuring low brain modularity and system segregation and vice versa. Furthermore, separate analyses on neglect vs. non-neglect patients yielded two distinct brain states for each sub-cohort. A state featuring widespread strong connections within and between networks and low modularity and system segregation was detected only in the neglect group. Such a connectivity profile blurred the distinction among functional systems. Finally, a state exhibiting a clear separation among modules with strong positive intra-network and negative inter-network connectivity was found only in the non-neglect group. Overall, our results indicate that stroke yielding spatial attention deficits affects the time-varying properties of functional interactions among large-scale networks. These findings provide further insights into the pathophysiology of spatial neglect and its treatment.
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Affiliation(s)
- Sara Spadone
- Department of Neuroscience, Imaging and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy
| | | | - Anna Digiovanni
- Department of Neuroscience, Imaging and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy
| | - Eleonora Grande
- Department of Neuroscience, Imaging and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy
| | | | - Stefano L. Sensi
- Department of Neuroscience, Imaging and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy
| | - Giorgia Committeri
- Department of Neuroscience, Imaging and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy
| | - Antonello Baldassarre
- Department of Neuroscience, Imaging and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy
- *Correspondence: Antonello Baldassarre
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18
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Yong W, Song J, Xing C, Xu JJ, Xue Y, Yin X, Wu Y, Chen YC. Disrupted Topological Organization of Resting-State Functional Brain Networks in Age-Related Hearing Loss. Front Aging Neurosci 2022; 14:907070. [PMID: 35669463 PMCID: PMC9163682 DOI: 10.3389/fnagi.2022.907070] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Accepted: 04/25/2022] [Indexed: 11/23/2022] Open
Abstract
Purpose Age-related hearing loss (ARHL), associated with the function of speech perception decreases characterized by bilateral sensorineural hearing loss at high frequencies, has become an increasingly critical public health problem. This study aimed to investigate the topological features of the brain functional network and structural dysfunction of the central nervous system in ARHL using graph theory. Methods Forty-six patients with ARHL and forty-five age, sex, and education-matched healthy controls were recruited to undergo a resting-state functional magnetic resonance imaging (fMRI) scan in this study. Graph theory was applied to analyze the topological properties of the functional connectomes by studying the local and global organization of neural networks. Results Compared with healthy controls, the patient group showed increased local efficiency (Eloc) and clustering coefficient (Cp) of the small-world network. Besides, the degree centrality (Dc) and nodal efficiency (Ne) values of the left inferior occipital gyrus (IOG) in the patient group showed a decrease in contrast with the healthy control group. In addition, the intra-modular interaction of the occipital lobe module and the inter-modular interaction of the parietal occipital module decreased in the patient group, which was positively correlated with Dc and Ne. The intra-modular interaction of the occipital lobe module decreased in the patient group, which was negatively correlated with the Eloc. Conclusion Based on fMRI and graph theory, we indicate the aberrant small-world network topology in ARHL and dysfunctional interaction of the occipital lobe and parietal lobe, emphasizing the importance of dysfunctional left IOG. These results suggest that early diagnosis and treatment of patients with ARHL is necessary, which can avoid the transformation of brain topology and decreased brain function.
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Affiliation(s)
- Wei Yong
- Department of Radiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - Jiajie Song
- Department of Radiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
- Department of Radiology, Nanjing Pukou Central Hospital, Pukou Branch Hospital of Jiangsu Province Hospital, Nanjing, China
| | - Chunhua Xing
- Department of Radiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - Jin-Jing Xu
- Department of Otolaryngology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - Yuan Xue
- Department of Otolaryngology, Nanjing Pukou Central Hospital, Pukou Branch Hospital of Jiangsu Province Hospital, Nanjing, China
| | - Xindao Yin
- Department of Radiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - Yuanqing Wu
- Department of Otolaryngology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
- *Correspondence: Yuanqing Wu
| | - Yu-Chen Chen
- Department of Radiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
- Yu-Chen Chen
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Hua JC, Xu XM, Xu ZG, Xu JJ, Hu JH, Xue Y, Wu Y. Aberrant Functional Network of Small-World in Sudden Sensorineural Hearing Loss With Tinnitus. Front Neurosci 2022; 16:898902. [PMID: 35663555 PMCID: PMC9160300 DOI: 10.3389/fnins.2022.898902] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Accepted: 04/20/2022] [Indexed: 11/30/2022] Open
Abstract
Few researchers investigated the topological properties and relationships with cognitive deficits in sudden sensorineural hearing loss (SNHL) with tinnitus. To explore the topological characteristics of the brain connectome following SNHL from the global level and nodal level, we recruited 36 bilateral SNHL patients with tinnitus and 37 well-matched healthy controls. Every subject underwent pure tone audiometry tests, neuropsychological assessments, and MRI scanning. AAL atlas was employed to divide a brain into 90 cortical and subcortical regions of interest, then investigated the global and nodal properties of “small world” network in SNHL and control groups using a graph-theory analysis. The global characteristics include small worldness, cluster coefficient, characteristic path length, local efficiency, and global efficiency. Node properties include degree centrality, betweenness centrality, nodal efficiency, and nodal clustering coefficient. Interregional connectivity analysis was also computed among 90 nodes. We found that the SNHL group had significantly higher hearing thresholds and cognitive impairments, as well as disrupted internal connections among 90 nodes. SNHL group displayed lower AUC of cluster coefficient and path length lambda, but increased global efficiency. The opercular and triangular parts of the inferior frontal gyrus, rectus gyrus, parahippocampal gyrus, precuneus, and amygdala showed abnormal local features. Some of these connectome alterations were correlated with cognitive ability and the duration of SNHL. This study may prove potential imaging biomarkers and treatment targets for future studies.
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Affiliation(s)
- Jin-Chao Hua
- Department of Otolaryngology, Nanjing Pukou Central Hospital, Pukou Branch Hospital of Jiangsu Province Hospital, Nanjing, China
| | - Xiao-Min Xu
- Department of Radiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - Zhen-Gui Xu
- Department of Otolaryngology, Nanjing Pukou Central Hospital, Pukou Branch Hospital of Jiangsu Province Hospital, Nanjing, China
| | - Jin-Jing Xu
- Department of Otolaryngology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - Jing-Hua Hu
- Department of Otolaryngology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - Yuan Xue
- Department of Otolaryngology, Nanjing Pukou Central Hospital, Pukou Branch Hospital of Jiangsu Province Hospital, Nanjing, China
- *Correspondence: Yuan Xue,
| | - Yuanqing Wu
- Department of Otolaryngology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
- Yuanqing Wu,
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20
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Chen S, Wang SH, Bai YY, Zhang JW, Zhang HJ. Comparative Study on Topological Properties of the Whole-Brain Functional Connectome in Idiopathic Rapid Eye Movement Sleep Behavior Disorder and Parkinson’s Disease Without RBD. Front Aging Neurosci 2022; 14:820479. [PMID: 35478699 PMCID: PMC9036484 DOI: 10.3389/fnagi.2022.820479] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Accepted: 03/07/2022] [Indexed: 11/18/2022] Open
Abstract
Purpose Idiopathic rapid eye movement Sleep Behavior Disorder (iRBD) is considered as a prodromal and most valuable warning symptom for Parkinson’s disease (PD). Although iRBD and PD without RBD (nRBD-PD) are both α-synucleinopathies, whether they share the same neurodegeneration process is not clear enough. In this study, the pattern and extent of neurodegeneration were investigated and compared between early-stage nRBD-PD and iRBD from the perspective of whole-brain functional network changes. Methods Twenty-one patients with iRBD, 23 patients with early-stage nRBD-PD, and 22 matched healthy controls (HCs) were enrolled. Functional networks were constructed using resting-state functional MRI (fMRI) data. Network topological properties were analyzed and compared among groups by graph theory approaches. Correlation analyses were performed between network topological properties and cognition in the iRBD and nRBD-PD groups. Results Both patients with iRBD and patients with early-stage nRBD-PD had attention, executive function, and some memory deficits. On global topological organization, iRBD and nRBD-PD groups still presented small-worldness, but both groups exhibited decreased global/local efficiency and increased characteristic path length. On regional topological organization, compared with HC, nRBD-PD presented decreased nodal efficiency, decreased degree centrality, and increased nodal shortest path length, while iRBD presented decreased nodal efficiency and nodal shortest path. For iRBD, brain regions with decreased nodal efficiency were included in the corresponding regions of nRBD-PD. Nodal shortest path changes were significantly different in terms of brain regions and directions between nRBD-PD and iRBD. Attention deficits were correlated with local topological properties of the occipital lobe in both iRBD and nRBD-PD groups. Conclusion Both global and local efficiency of functional networks declined in nRBD-PD and iRBD groups. The overlaps and differences in local topological properties between nRBD-PD and iRBD indicate that iRBD not only shares functional changes of PD but also presents distinct features.
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21
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Zarei AA, Jensen W, Faghani Jadidi A, Lontis R, Atashzar SF. Gamma-band Enhancement of Functional Brain Connectivity Following Transcutaneous Electrical Nerve Stimulation. J Neural Eng 2022; 19. [PMID: 35234662 DOI: 10.1088/1741-2552/ac59a1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 03/01/2022] [Indexed: 11/11/2022]
Abstract
OBJECTIVE Transcutaneous electrical nerve stimulation (TENS) has been suggested as a possible non-invasive pain treatment. However, the underlying mechanism of the analgesic effect of TENS and how brain network functional connectivity is affected following the use of TENS is not yet fully understood. The purpose of this study was to investigate the effect of high-frequency TENS on the alternation of functional brain network connectivity and the corresponding topographical changes, besides perceived sensations. APPROACH Forty healthy subjects participated in this study. EEG data and sensory profiles were recorded before and up to an hour following high-frequency TENS (100 Hz) in sham and intervention groups. Brain source activity from EEG data was estimated using the LORETA algorithm. In order to generate the brain connectivity network, the Phase lag index was calculated for all pair-wise connections of eight selected brain areas over six different frequency bands (i.e., δ, θ, α, β, γ, and 0.5-90 Hz). MAIN RESULTS The results suggested that the functional connectivity between the primary somatosensory cortex (SI) and the anterior cingulate cortex (ACC), in addition to functional connectivity between S1 and the medial prefrontal cortex (mPFC), were significantly increased in the gamma-band, following the TENS intervention. Additionally, using graph theory, several significant changes were observed in global and local characteristics of functional brain connectivity in gamma-band. SIGNIFICANCE Our observations in this paper open a neuropsychological window of understanding the underlying mechanism of TENS and the corresponding changes in functional brain connectivity, simultaneously with alternation in sensory perception.
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Affiliation(s)
- Ali Asghar Zarei
- Center for Neuroplasticity and Pain (CNAP), Department of Health Science and Technology, Aalborg Universitet, Fredrik Bajers Vej 7 D3, Aalborg, 9220, DENMARK
| | - Winnie Jensen
- Center for Sensory-Motor Interaction Department of Health Science and Technology, Aalborg University, Fredrik Bajers Vej 7, 9220 Aalborg, Aalborg, 9220, DENMARK
| | - Armita Faghani Jadidi
- Center for Neuroplasticity and Pain (CNAP), Department of Health Science and Technology, Aalborg Universitet, Fredrik Bajers Vej 7 D3, Aalborg, 9220, DENMARK
| | - Romulus Lontis
- Center for Neuroplasticity and Pain (CNAP), Department of Health Science and Technology, Aalborg Universitet, Fredrik Bajers Vej 7 D3, Aalborg, 9220, DENMARK
| | - S Farokh Atashzar
- Departments of Electrical and Computer Engineering, and Mechanical and Aerospace Engineering, New York University, 5 MetroTech Center #266D Brooklyn, NY 11201, New York, New York, NY 11201, UNITED STATES
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22
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Miao G, Rao B, Wang S, Fang P, Chen Z, Chen L, Zhang X, Zheng J, Xu H, Liao W. Decreased Functional Connectivities of Low-Degree Level Rich Club Organization and Caudate in Post-stroke Cognitive Impairment Based on Resting-State fMRI and Radiomics Features. Front Neurosci 2022; 15:796530. [PMID: 35250435 PMCID: PMC8890030 DOI: 10.3389/fnins.2021.796530] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2021] [Accepted: 12/31/2021] [Indexed: 11/13/2022] Open
Abstract
BackgroundStroke is an important cause of cognitive impairment. Rich club organization, a highly interconnected network brain core region, is closely related to cognition. We hypothesized that the disturbance of rich club organization exists in patients with post-stroke cognitive impairment (PSCI).MethodsWe collected data on resting-state functional magnetic resonance imaging (rs-fMRI) with 21 healthy controls (HC), 16 hemorrhagic stroke (hPSCI), and 21 infarct stroke (iPSCI). 3D shape features and first-order statistics of stroke lesions were extracted using 3D slicer software. Additionally, we assessed cognitive function using the Montreal Cognitive Assessment (MoCA) and Mini-Mental State Examination (MMSE).ResultsNormalized rich club coefficients were higher in hPSCI and iPSCI than HC at low-degree k-levels (k = 1–8 in iPSCI, k = 2–8 in hPSCI). Feeder and local connections were significantly decreased in PSCI patients versus HC, mainly distributed in salience network (SN), default-mode network (DMN), cerebellum network (CN), and orbitofrontal cortex (ORB), especially involving the right and left caudate with changed nodal efficiency. The feeder and local connections of significantly between-group difference were positively related to MMSE and MoCA scores, primarily distributed in the sensorimotor network (SMN) and visual network (VN) in hPSCI, SN, and DMN in iPSCI. Additionally, decreased local connections and low-degree ϕnorm(k) were correlated to 3D shape features and first-order statistics of stroke lesions.ConclusionThis study reveals the disrupted low-degree level rich club organization and relatively preserved functional core network in PSCI patients. Decreased feeder and local connections in cognition-related networks (DMN, SN, CN, and ORB), particularly involving the caudate nucleus, may offer insight into pathological mechanism of PSCI patients. The shape and signal features of stroke lesions may provide an essential clue for the damage of functional connectivity and the whole brain networks.
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Affiliation(s)
- Guofu Miao
- Department of Rehabilitation Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Bo Rao
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Sirui Wang
- Department of Rehabilitation Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Pinyan Fang
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China
- Department of Radiology, TEDA International Cardiovascular Hospital, Tianjin, China
| | - Zhuo Chen
- Department of Rehabilitation Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Linglong Chen
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Xin Zhang
- Department of Rehabilitation Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Jun Zheng
- Department of Rehabilitation Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Haibo Xu
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China
- *Correspondence: Haibo Xu,
| | - Weijing Liao
- Department of Rehabilitation Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China
- Weijing Liao,
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23
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Gupta A, Bhatt RR, Rivera-Cancel A, Makkar R, Kragel PA, Rodriguez T, Graner JL, Alaverdyan A, Hamadani K, Vora P, Naliboff B, Labus JS, LaBar KS, Mayer EA, Zucker N. Complex functional brain network properties in anorexia nervosa. J Eat Disord 2022; 10:13. [PMID: 35123579 PMCID: PMC8817538 DOI: 10.1186/s40337-022-00534-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Accepted: 01/19/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Anorexia nervosa (AN) is a disorder characterized by an incapacitating fear of weight gain and by a disturbance in the way the body is experienced, facets that motivate dangerous weight loss behaviors. Multimodal neuroimaging studies highlight atypical neural activity in brain networks involved in interoceptive awareness and reward processing. METHODS The current study used resting-state neuroimaging to model the architecture of large-scale functional brain networks and characterize network properties of individual brain regions to clinical measures. Resting-state neuroimaging was conducted in 62 adolescents, 22 (21 female) with a history of AN and 40 (39 female) healthy controls (HCs). Sensorimotor and basal ganglia regions, as part of a 165-region whole-brain network, were investigated. Subject-specific functional brain networks were computed to index centrality. A contrast analysis within the general linear model covarying for age was performed. Correlations between network properties and behavioral measures were conducted (significance q < .05). RESULTS Compared to HCs, AN had lower connectivity from sensorimotor regions, and greater connectivity from the left caudate nucleus to the right postcentral gyrus. AN demonstrated lower sensorimotor centrality, but higher basal ganglia centrality. Sensorimotor connectivity dyads and centrality exhibited negative correlations with body dissatisfaction and drive for thinness, two essential features of AN. CONCLUSIONS These findings suggest that AN is associated with greater communication from the basal ganglia, and lower information propagation in sensorimotor cortices. This is consistent with the clinical presentation of AN, where individuals exhibit patterns of rigid habitual behavior that is not responsive to bodily needs, and seem "disconnected" from their bodies.
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Affiliation(s)
- Arpana Gupta
- G. Oppenheimer Center for Neurobiology of Stress and Resilience, UCLA, Los Angeles, CA, 90095, USA. .,David Geffen School of Medicine, UCLA, Los Angeles, CA, 90095, USA. .,Vatche and Tamar Manoukian Division of Digestive Diseases, UCLA, Los Angeles, CA, 90095, USA.
| | - Ravi R Bhatt
- G. Oppenheimer Center for Neurobiology of Stress and Resilience, UCLA, Los Angeles, CA, 90095, USA.,Imaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine at USC, University of Southern California, Los Angeles, USA
| | | | - Rishi Makkar
- G. Oppenheimer Center for Neurobiology of Stress and Resilience, UCLA, Los Angeles, CA, 90095, USA
| | | | - Thomas Rodriguez
- G. Oppenheimer Center for Neurobiology of Stress and Resilience, UCLA, Los Angeles, CA, 90095, USA
| | - John L Graner
- Department of Psychology and Neuroscience, Duke University, Durham, USA
| | - Anita Alaverdyan
- G. Oppenheimer Center for Neurobiology of Stress and Resilience, UCLA, Los Angeles, CA, 90095, USA
| | - Kareem Hamadani
- G. Oppenheimer Center for Neurobiology of Stress and Resilience, UCLA, Los Angeles, CA, 90095, USA
| | - Priten Vora
- G. Oppenheimer Center for Neurobiology of Stress and Resilience, UCLA, Los Angeles, CA, 90095, USA
| | - Bruce Naliboff
- G. Oppenheimer Center for Neurobiology of Stress and Resilience, UCLA, Los Angeles, CA, 90095, USA.,David Geffen School of Medicine, UCLA, Los Angeles, CA, 90095, USA.,Vatche and Tamar Manoukian Division of Digestive Diseases, UCLA, Los Angeles, CA, 90095, USA
| | - Jennifer S Labus
- G. Oppenheimer Center for Neurobiology of Stress and Resilience, UCLA, Los Angeles, CA, 90095, USA.,David Geffen School of Medicine, UCLA, Los Angeles, CA, 90095, USA.,Vatche and Tamar Manoukian Division of Digestive Diseases, UCLA, Los Angeles, CA, 90095, USA
| | - Kevin S LaBar
- Department of Psychology and Neuroscience, Duke University, Durham, USA
| | - Emeran A Mayer
- G. Oppenheimer Center for Neurobiology of Stress and Resilience, UCLA, Los Angeles, CA, 90095, USA.,David Geffen School of Medicine, UCLA, Los Angeles, CA, 90095, USA.,Vatche and Tamar Manoukian Division of Digestive Diseases, UCLA, Los Angeles, CA, 90095, USA.,Ahmanson-Lovelace Brain Mapping Center, UCLA, Los Angeles, CA, 90095, USA
| | - Nancy Zucker
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, USA.,Department of Psychology and Neuroscience, Duke University, Durham, USA
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24
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Rao B, Cheng H, Xu H, Peng Y. Random Network and Non-rich-club Organization Tendency in Children With Non-syndromic Cleft Lip and Palate After Articulation Rehabilitation: A Diffusion Study. Front Neurol 2022; 13:790607. [PMID: 35185761 PMCID: PMC8847279 DOI: 10.3389/fneur.2022.790607] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2021] [Accepted: 01/03/2022] [Indexed: 11/30/2022] Open
Abstract
Objective The neuroimaging pattern in brain networks after articulation rehabilitation can be detected using graph theory and multivariate pattern analysis (MVPA). In this study, we hypothesized that the characteristics of the topology pattern of brain structural network in articulation-rehabilitated children with non-syndromic cleft lip and palate (NSCLP) were similar to that in healthy comparisons. Methods A total of 28 children with NSCLP and 28 controls with typical development were scanned for diffusion tensor imaging on a 3T MRI scanner. Structural networks were constructed, and their topological properties were obtained. Besides, the Chinese language clear degree scale (CLCDS) scores were used for correlation analysis with topological features in patients with NSCLP. Results The NSCLP group showed a similar rich-club connection pattern, but decreased small-world index, normalized rich-club coefficient, and increased connectivity strength of connections compared to controls. The univariate and multivariate patterns of the structural network in articulation-rehabilitated children were primarily in the feeder and local connections, covering sensorimotor, visual, frontoparietal, default mode, salience, and language networks, and orbitofrontal cortex. In addition, the connections that were significantly correlated with the CLCDS scores, as well as the weighted regions for classification, were chiefly distributed in the dorsal and ventral stream associated with the language networks of the non-dominant hemisphere. Conclusion The average level rich-club connection pattern and the compensatory of the feeder and local connections mainly covering language networks may be related to the CLCDS in articulation-rehabilitated children with NSCLP. However, the patterns of small-world and rich-club structural organization in the articulation-rehabilitated children exhibited a random network and non-rich-club organization tendency. These findings enhanced the understanding of neuroimaging patterns in children with NSCLP after articulation rehabilitation.
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Affiliation(s)
- Bo Rao
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan, China
| | - Hua Cheng
- Department of Radiology, National Center for Children's Health, Beijing Children's Hospital, Capital Medical University, Beijing, China
| | - Haibo Xu
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan, China
- *Correspondence: Haibo Xu
| | - Yun Peng
- Department of Radiology, National Center for Children's Health, Beijing Children's Hospital, Capital Medical University, Beijing, China
- Yun Peng
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25
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Cui W, Wang S, Chen B, Fan G. Altered Functional Network in Infants With Profound Bilateral Congenital Sensorineural Hearing Loss: A Graph Theory Analysis. Front Neurosci 2022; 15:810833. [PMID: 35095404 PMCID: PMC8795617 DOI: 10.3389/fnins.2021.810833] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Accepted: 12/22/2021] [Indexed: 12/17/2022] Open
Abstract
Functional magnetic resonance imaging (fMRI) studies have suggested that there is a functional reorganization of brain areas in patients with sensorineural hearing loss (SNHL). Recently, graph theory analysis has brought a new understanding of the functional connectome and topological features in central neural system diseases. However, little is known about the functional network topology changes in SNHL patients, especially in infants. In this study, 34 infants with profound bilateral congenital SNHL and 28 infants with normal hearing aged 11–36 months were recruited. No difference was found in small-world parameters and network efficiency parameters. Differences in global and nodal topologic organization, hub distribution, and whole-brain functional connectivity were explored using graph theory analysis. Both normal-hearing infants and SNHL infants exhibited small-world topology. Furthermore, the SNHL group showed a decreased nodal degree in the bilateral thalamus. Six hubs in the SNHL group and seven hubs in the normal-hearing group were identified. The left middle temporal gyrus was a hub only in the SNHL group, while the right parahippocampal gyrus and bilateral temporal pole were hubs only in the normal-hearing group. Functional connectivity between auditory regions and motor regions, between auditory regions and default-mode-network (DMN) regions, and within DMN regions was found to be decreased in the SNHL group. These results indicate a functional reorganization of brain functional networks as a result of hearing loss. This study provides evidence that functional reorganization occurs in the early stage of life in infants with profound bilateral congenital SNHL from the perspective of complex networks.
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26
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Stefano Filho CA, Attux RRDF, Castellano G. Motor imagery practice and feedback effects on functional connectivity. J Neural Eng 2021; 18:066048. [PMID: 34933292 DOI: 10.1088/1741-2552/ac456d] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
- Objective: the use of motor imagery (MI) in motor rehabilitation protocols has been increasingly investigated as a potential technique for enhancing traditional treatments, yielding better clinical outcomes. However, since MI performance can be challenging, practice is usually required. This demands appropriate training, actively engaging the MI-related brain areas, consequently enabling the user to properly benefit from it. The role of feedback is central for MI practice. Yet, assessing which underlying neural changes are feedback-specific or purely due to MI practice is still a challenging effort, mainly due to the difficulty in isolating their contributions. In this work, we aimed to assess functional connectivity (FC) changes following MI practice that are either extrinsic or specific to feedback. APPROACH to achieve this, we investigated FC, using graph theory, in electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data, during MI performance and at resting-state (rs), respectively. Thirty healthy subjects were divided into three groups, receiving no feedback (control), "false" feedback (sham) or actual neurofeedback (active). Participants underwent 12 to 13 hands-MI EEG sessions and pre- and post-MI training fMRI exams. MAIN RESULTS following MI practice, control participants presented significant increases in degree and in eigenvector centrality for occipital nodes at rs-fMRI scans, whereas sham-feedback produced similar effects, but to a lesser extent. Therefore, MI practice, by itself, seems to stimulate visual information processing mechanisms that become apparent during basal brain activity. Additionally, only the active group displayed decreases in inter-subject FC patterns, both during MI performance and at rs-fMRI. SIGNIFICANCE hence, actual neurofeedback impacted FC by disrupting common inter-subject patterns, suggesting that subject-specific neural plasticity mechanisms become important. Future studies should consider this when designing experimental NFBT protocols and analyses.
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Affiliation(s)
| | - Romis Ribeiro de Faisol Attux
- Laboratory of Signal Processing for Communications, School of Electrical and Computer Engineering, University of Campinas, Laboratório de Processamento de Sinais para Comunicações, Campinas, São Paulo, 13083-852, BRAZIL
| | - Gabriela Castellano
- Department of Cosmic Rays and Chronology, University of Campinas - UNICAMP, Institute of Physics Gleb Wataghin, R. Sérgio Buarque de Holanda, nº 777, Cidade Universitária, Campinas, SP, 13083-859, BRAZIL
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27
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Deng S, Sun L, Chen W, Liu X, Chen S. Effect of APOEε4 on Functional Brain Network in Patients with Subjective Cognitive Decline: A Resting State Functional MRI Study. Int J Gen Med 2021; 14:9761-9771. [PMID: 34934350 PMCID: PMC8684393 DOI: 10.2147/ijgm.s342673] [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: 10/04/2021] [Accepted: 12/06/2021] [Indexed: 11/29/2022] Open
Abstract
PURPOSE Subjective cognitive decline (SCD) is the earliest symptom stage of Alzheimer's disease (AD), and the APOEε4 allele is the strongest genetic risk factor for sporadic AD. Based on graph theory, the resting state functional connectivity (rsFC) in SCD patients with APOEε4 was studied to explore the effect of APOEε4 on the rsFC network properties of SCD patients. PATIENTS AND METHODS This cross-sectional study included MRI image data from 19 SCD patients with APOEε4 (SCD+), 29 SCD patients without APOEε4 (SCD-), and 30 normal control (NC-) individuals without APOEε4. We generated a binary matrix based on anatomical automatic labeling (AAL) 90 atlas to construct the functional network. We then calculated the whole brain network characteristics and intracerebral node characteristics by graph theory. RESULTS For the whole brain network characteristics, all three groups showed small-worldness. The SCD+ group had increased compensatory information transfer speed and enhanced integration capability. This group also had high heterogeneity for intracerebral node characteristics, mainly in the default mode network, left superior occipital gyrus, and bilateral putamen. CONCLUSION APOEε4 effects the functional brain network in patients with SCD and may be a potential indicator for the identification of SCD.
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Affiliation(s)
- Simin Deng
- The Second School of Clinical Medicine, Southern Medical University, Dongguan Tung Wah Hospital, Guangdong, People’s Republic of China
| | - Lingyu Sun
- Department of Rehabilitation Medicine, Dongguan Tung Wah Hospital, Guangdong, People’s Republic of China
| | - Weijie Chen
- The Second School of Clinical Medicine, Southern Medical University, Dongguan Tung Wah Hospital, Guangdong, People’s Republic of China
| | - Xiaorong Liu
- Department of Rehabilitation Medicine, Dongguan Tung Wah Hospital, Guangdong, People’s Republic of China
| | - Shangjie Chen
- Department of Rehabilitation Medicine, Affiliated Baoan Hospital of Shenzhen, Southern Medical University, Guangdong, People’s Republic of China
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28
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Wu C, Matias C, Foltynie T, Limousin P, Zrinzo L, Akram H. Dynamic Network Connectivity Reveals Markers of Response to Deep Brain Stimulation in Parkinson's Disease. Front Hum Neurosci 2021; 15:729677. [PMID: 34690721 PMCID: PMC8526554 DOI: 10.3389/fnhum.2021.729677] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Accepted: 07/19/2021] [Indexed: 01/10/2023] Open
Abstract
Background: Neuronal loss in Parkinson's Disease (PD) leads to widespread neural network dysfunction. While graph theory allows for analysis of whole brain networks, patterns of functional connectivity (FC) associated with motor response to deep brain stimulation of the subthalamic nucleus (STN-DBS) have yet to be explored. Objective/Hypothesis: To investigate the distributed network properties associated with STN-DBS in patients with advanced PD. Methods: Eighteen patients underwent 3-Tesla resting state functional MRI (rs-fMRI) prior to STN-DBS. Improvement in UPDRS-III scores following STN-DBS were assessed 1 year after implantation. Independent component analysis (ICA) was applied to extract spatially independent components (ICs) from the rs-fMRI. FC between ICs was calculated across the entire time series and for dynamic brain states. Graph theory analysis was performed to investigate whole brain network topography in static and dynamic states. Results: Dynamic analysis identified two unique brain states: a relative hypoconnected state and a relative hyperconnected state. Time spent in a state, dwell time, and number of transitions were not correlated with DBS response. There were no significant FC findings, but graph theory analysis demonstrated significant relationships with STN-DBS response only during the hypoconnected state - STN-DBS was negatively correlated with network assortativity. Conclusion: Given the widespread effects of dopamine depletion in PD, analysis of whole brain networks is critical to our understanding of the pathophysiology of this disease. Only by leveraging graph theoretical analysis of dynamic FC were we able to isolate a hypoconnected brain state that contained distinct network properties associated with the clinical effects of STN-DBS.
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Affiliation(s)
- Chengyuan Wu
- Department of Neurological Surgery, Vickie and Jack Farber Institute for Neuroscience, Thomas Jefferson University, Philadelphia, PA, United States
- Jefferson Integrated Magnetic Resonance Imaging Center, Department of Radiology, Thomas Jefferson University, Philadelphia, PA, United States
| | - Caio Matias
- Department of Neurological Surgery, Vickie and Jack Farber Institute for Neuroscience, Thomas Jefferson University, Philadelphia, PA, United States
| | - Thomas Foltynie
- Unit of Functional Neurosurgery, UCL Institute of Neurology, London, United Kingdom
| | - Patricia Limousin
- Unit of Functional Neurosurgery, UCL Institute of Neurology, London, United Kingdom
| | - Ludvic Zrinzo
- Unit of Functional Neurosurgery, UCL Institute of Neurology, London, United Kingdom
- Victor Horsley Department of Neurosurgery, The National Hospital for Neurology and Neurosurgery, London, United Kingdom
| | - Harith Akram
- Unit of Functional Neurosurgery, UCL Institute of Neurology, London, United Kingdom
- Victor Horsley Department of Neurosurgery, The National Hospital for Neurology and Neurosurgery, London, United Kingdom
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29
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Yang Y, Cheng Y, Wang X, Upreti B, Cui R, Liu S, Shan B, Yu H, Luo C, Xu J. Gout Is Not Just Arthritis: Abnormal Cortical Thickness and Structural Covariance Networks in Gout. Front Neurol 2021; 12:662497. [PMID: 34603178 PMCID: PMC8481804 DOI: 10.3389/fneur.2021.662497] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2021] [Accepted: 08/12/2021] [Indexed: 12/27/2022] Open
Abstract
Background: Hyperuricemia is the cause of gout. The antioxidant and neuroprotective effects of uric acid seem to benefit some patients with central nervous system injury. However, changes in the brain structure have not been discovered in patients with gout. Object: Clarify the changes in cortical thickness in patients with gout and the alteration of the structural covariance networks (SCNs) based on cortical thickness. Methods: We collected structural MRIs of 23 male gout patients and 23 age-matched healthy controls. After calculating and comparing the difference in cortical thickness between the two groups, we constructed and analyzed the cortical thickness covariance networks of the two groups, and we investigated for any changes in SCNs of gout patients. Results: Gout patients have thicker cortices in the left postcentral, left supramarginal, right medial temporal, and right medial orbitofrontal regions; and thinner cortices were found in the left insula, left superior frontal, right pericalcarine, and right precentral regions. In SCN analysis, between-group differences in global network measures showed that gout patients have a higher global efficiency. In regional network measures, more nodes in gout patients have increased centrality. In network hub analysis, we found that the transfer of the core hub area, rather than the change in number, may be the characteristic of the gout's cortical thickness covariance network. Conclusion: This is the first study on changes in brain cortical thickness and SCN based on graph theory in patients with gout. The present study found that, compared with healthy controls, gout patients show regional cortical thinning or thickening, and variation in the properties of the cortical thickness covariance network also changed. These alterations may be the combined effect of disease damage and physiological compensation. More research is needed to fully understand the complex underlying mechanisms of gout brain variation.
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Affiliation(s)
- Yifan Yang
- Department of Rheumatology and Immunology, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Yuqi Cheng
- Department of Psychiatry, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Xiangyu Wang
- Department of Rheumatology and Immunology, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Bibhuti Upreti
- Department of Rheumatology and Immunology, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Ruomei Cui
- Department of Rheumatology and Immunology, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Shuang Liu
- Department of Rheumatology and Immunology, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Baoci Shan
- Nuclear Analysis Technology Key Laboratory, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing, China
| | - Hongjun Yu
- Magnetic Resonance Imaging Center, The First Hospital of Kunming, Kunming, China
| | - Chunrong Luo
- Magnetic Resonance Imaging Center, The First Hospital of Kunming, Kunming, China
| | - Jian Xu
- Department of Rheumatology and Immunology, First Affiliated Hospital of Kunming Medical University, Kunming, China
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You J, Zhang J, Shang S, Gu W, Hu L, Zhang Y, Xiong Z, Chen YC, Yin X. Altered Brain Functional Network Topology in Lung Cancer Patients After Chemotherapy. Front Neurol 2021; 12:710078. [PMID: 34408724 PMCID: PMC8367296 DOI: 10.3389/fneur.2021.710078] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Accepted: 07/05/2021] [Indexed: 12/24/2022] Open
Abstract
Purpose: This study aimed to explore the topological features of brain functional network in lung cancer patients before and after chemotherapy using graph theory. Methods: Resting-state functional magnetic resonance imaging scans were obtained from 44 post-chemotherapy and 46 non-chemotherapy patients as well as 49 healthy controls (HCs). All groups were age- and gender-matched. Then, the topological features of brain functional network were assessed using graph theory analysis. Results: At the global level, compared with the HCs, both the non-chemotherapy group and the post-chemotherapy group showed significantly increased values in sigma (p < 0.05), gamma (p < 0.05), and local efficiency, Eloc (p < 0.05). The post-chemotherapy group and the non-chemotherapy group did not differ significantly in the above-mentioned parameters. At the nodal level, when non-chemotherapy or post-chemotherapy patients were compared with the HCs, abnormal nodal centralities were mainly observed in widespread brain regions. However, when the post-chemotherapy group was compared with the non-chemotherapy group, significantly decreased nodal centralities were observed primarily in the prefrontal–subcortical regions. Conclusions: These results indicate that lung cancer and chemotherapy can disrupt the topological features of functional networks, and chemotherapy may cause a pattern of prefrontal–subcortical brain network abnormality. As far as we know, this is the first study to report that altered functional brain networks are related to lung cancer and chemotherapy.
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Affiliation(s)
- Jia You
- Department of Radiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - Juan Zhang
- Department of Neurology, Nanjing Yuhua Hospital, Yuhua Branch of Nanjing First Hospital, Nanjing, China
| | - Song'an Shang
- Department of Radiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - Wei Gu
- Department of Respiratory Medicine, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - Lanyue Hu
- Department of Radiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - Yujie Zhang
- Department of Radiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - Zhenyu Xiong
- Department of Radiation Oncology, The University of Texas Southwestern Medical Center, Dallas, TX, United States
| | - Yu-Chen Chen
- Department of Radiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - Xindao Yin
- Department of Radiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
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Argyropoulou MI, Xydis VG, Drougia A, Giantsouli AS, Giapros V, Astrakas LG. Structural and functional brain connectivity in moderate-late preterm infants with low-grade intraventricular hemorrhage. Neuroradiology 2021; 64:197-204. [PMID: 34342681 DOI: 10.1007/s00234-021-02770-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Accepted: 07/11/2021] [Indexed: 11/30/2022]
Abstract
PURPOSE Brain functional connectivity (FC) changes and microstructural abnormalities are reported in infants born moderate and late preterm (MLPT). We evaluated the effect of low-grade (grades I, II) intraventricular hemorrhage (IVH) in MLPT babies on brain structural connectivity (SC) and FC. METHODS Babies born MLPT between January 2014 and May 2017 underwent brain ultrasound (US) at 72 h and 7 days after birth, and MRI at around term equivalent. The MRI protocol comprised T1- and T2-weighted sequences, diffusion tensor imaging (DTI), and resting-state functional MRI (fMRI). SC and FC were assessed using graph analysis. RESULTS Of 350 MLPT neonates, 15 showed low-grade IVH on US at 72 h, for which brain MRI was available in 10. These 10 infants, with mean gestational age (GA) 34.0 ± 0.8 weeks, comprised the study group, and 10 MLPT infants of mean GA 33.9 ± 1.1 weeks, with no abnormalities on brain US and MRI, were control subjects. All study subjects presented modularity, small world topology, and rich club organization for both SC and FC. The patients with low-grade IVH had lower FC rich club coefficient and lower SC betweenness centrality in the left frontoparietal operculum, and lower SC rich club coefficient in the right superior orbitofrontal cortex than the control subjects. CONCLUSIONS Topological and functional properties of mature brain connectivity are present in MLPT infants. IVH in these infants was associated with structural and functional abnormalities in the left frontoparietal operculum and right orbitofrontal cortex, regions related to language and cognition.
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Affiliation(s)
- Maria I Argyropoulou
- Department of Radiology, Faculty of Medicine, School of Health Sciences, University of Ioannina, P.O. Box 1186, 45110, Ioannina, Greece.
| | - Vasileios G Xydis
- Department of Radiology, Faculty of Medicine, School of Health Sciences, University of Ioannina, P.O. Box 1186, 45110, Ioannina, Greece
| | - Aikaterini Drougia
- Neonatal Intensive Care Unit, Child Health Department, Faculty of Medicine, University of Ioannina, Ioannina, Greece
| | - Anastasia S Giantsouli
- Department of Radiology, Faculty of Medicine, School of Health Sciences, University of Ioannina, P.O. Box 1186, 45110, Ioannina, Greece
| | - Vasileios Giapros
- Neonatal Intensive Care Unit, Child Health Department, Faculty of Medicine, University of Ioannina, Ioannina, Greece
| | - Loukas G Astrakas
- Department of Medical Physics, Faculty of Medicine, University of Ioannina, Ioannina, Greece
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Cheng H, Rao B, Zhang W, Chen R, Peng Y. Increased modularity of the resting-state network in children with nonsyndromic cleft lip and palate after speech rehabilitation. Brain Behav 2021; 11:e02094. [PMID: 34343416 PMCID: PMC8413807 DOI: 10.1002/brb3.2094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Revised: 02/17/2021] [Accepted: 02/18/2021] [Indexed: 11/10/2022] Open
Abstract
INTRODUCTION Speech therapy is the primary management followed the physical management through surgery for children with nonsyndromic cleft lip and palate (NSCLP). However, the topological pattern of the resting-state network after rehabilitation remains poorly understood. We aimed to explore the functional topological pattern of children with NSCLP after speech rehabilitation compared with healthy controls. METHODS We examined 28 children with NSCLP after speech rehabilitation (age = 10.0 ± 2.3 years) and 28 healthy controls for resting-state functional MRI. We calculated functional connections and the degree strength, betweenness centrality, network clustering coefficient (Cp), characteristic path length (Lp), global network efficiency (Eg), local network efficiency (Eloc), modularity index (Q), module number, and participation coefficient for the between-group differences using two-sample t tests (corrected p < .05). Additionally, we performed a correlation analysis between the Chinese language clear degree scale (CLCDS) scores and topological properties in children with NSCLP. RESULTS We detected significant between-group differences in the areas under the curve (AUCs) of degree strength and betweenness centrality in language-related brain regions. There were no significant between-group differences in module number, participation coefficient, Cp, Lp, Eg, or Eloc. However, the Q (density: 0.05-0.30) and QAUC (t = 2.46, p = .02) showed significant between-group differences. Additionally, there was no significant correlation between topological properties of statistical between-group differences and CLCDS scores. CONCLUSIONS Although nodal metric differences existed in the language-related brain regions, the children with NSCLP after speech rehabilitation had similar global network properties, module numbers, and participation coefficient, but increased modularity. Our results suggested that children with NSCLP achieved speech rehabilitation through function specialization in the language-related brain regions. The resting-state topology pattern could be of substantive neurobiological importance and potential imaging biomarkers for speech rehabilitation.
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Affiliation(s)
- Hua Cheng
- Department of Radiology, Beijing Children's Hospital, National Center for Children's Health, Capital Medical University, Beijing, China
| | - Bo Rao
- Departments of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Wenjing Zhang
- Department of Oral and Maxillofacial Plastic and Trauma Surgery, Center of Cleft Lip and Palate Treatment, Beijing Stomatological Hospital, Beijing, China
| | - Renji Chen
- Department of Oral and Maxillofacial Plastic and Trauma Surgery, Center of Cleft Lip and Palate Treatment, Beijing Stomatological Hospital, Beijing, China
| | - Yun Peng
- Department of Radiology, Beijing Children's Hospital, National Center for Children's Health, Capital Medical University, Beijing, China
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Ji C, Zhou Q, Qiu Y, Pan X, Sun X, Ding W, Mao J, Zhou Y, Luo Y. Decline of anterior cingulate functional network efficiency in first-episode, medication-naïve somatic symptom disorder and its relationship with catastrophizing. J Psychiatr Res 2021; 140:468-473. [PMID: 34147934 DOI: 10.1016/j.jpsychires.2021.06.019] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/10/2020] [Revised: 05/17/2021] [Accepted: 06/09/2021] [Indexed: 11/16/2022]
Abstract
The high prevalence of somatic symptom disorder (SSD) led to cumulative burdens to the medical system. However, the pathogenesis of this disease still remains unclear. Graph theoretical analysis discovered altered network topology across various psychiatric disorders, yet alteration in the topological structure of brain functional network in SSD patients is still unexplored. Catastrophizing is a common cognitive distortion in SSD. We hypothesize that the network topological metrics of SSD should be altered, and should correlate with catastrophizing scales. 32 medication-naïve, first-episode SSD patients and 30 age, gender matched HCs were recruited. The 17-item Hamilton Depression Rating Scale (HAMD-17), Hamilton Anxiety Rating Scale (HAMA) and Cognitive Emotion Regulation Questionnaire (CERQ) were accessed. Functional MRI were scanned and brain functional networks were constructed based on 166 anatomically cerebrum regions from the automated anatomical labeling 3 (AAL3) template. Network topological metrics were calculated and compared between the two groups. Correlation between these metrics and clinical scales were also calculated. Network global efficiency of SSD was significantly lower than that of HC. Nodal global efficiency of the left subgenual anterior cingulate cortex (sgACC) of SSD was significantly lower than that of HC. FCs between the left sgACC and other 21 seed nodes were significantly declined in SSD in comparison with HC. In SSD group, HAMD total score was significantly negatively correlated with the connection between the left medial superior frontal gyrus and the left sgACC. CERQ catastrophizing score was significantly negatively correlated with nodal global efficiency of left sgACC and with the FCs between the left sgACC and other 13 seed nodes. Catastrophizing could reflect the specific sgACC-centered dysfunction of brain network global efficiency of SSD. The left sgACC may be a future treatment target of dealing with catastrophizing, which is a core cognitive distortion of SSD.
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Affiliation(s)
- Chenfeng Ji
- Department of Psychological Medicine, Renji Hospital, Shanghai Jiao Tong University School of Medicine, 160 Pujian Road, Pudong New District, Shanghai, 200127, China
| | - Qian Zhou
- Department of Psychological Medicine, Renji Hospital, Shanghai Jiao Tong University School of Medicine, 160 Pujian Road, Pudong New District, Shanghai, 200127, China
| | - Yage Qiu
- Department of Radiology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, 160 Pujian Road, Pudong New District, Shanghai, 200127, China
| | - Xiandi Pan
- Shanghai Pudong New Area Mental Health Center, Tongji University School of Medicine, 165 Sanlin Road, Pudong New District, Shanghai, 200124, China
| | - Xia Sun
- Department of Psychological Medicine, Renji Hospital, Shanghai Jiao Tong University School of Medicine, 160 Pujian Road, Pudong New District, Shanghai, 200127, China
| | - Weina Ding
- Department of Radiology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, 160 Pujian Road, Pudong New District, Shanghai, 200127, China
| | - Jialiang Mao
- Department of Cardiology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, 160 Pujian Road, Pudong New District, Shanghai, 200127, China
| | - Yan Zhou
- Department of Radiology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, 160 Pujian Road, Pudong New District, Shanghai, 200127, China.
| | - Yanli Luo
- Department of Psychological Medicine, Renji Hospital, Shanghai Jiao Tong University School of Medicine, 160 Pujian Road, Pudong New District, Shanghai, 200127, China.
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Merhar SL, Jiang W, Parikh NA, Yin W, Zhou Z, Tkach JA, Wang L, Kline-Fath BM, He L, Braimah A, Vannest J, Lin W. Effects of prenatal opioid exposure on functional networks in infancy. Dev Cogn Neurosci 2021; 51:100996. [PMID: 34388637 PMCID: PMC8363826 DOI: 10.1016/j.dcn.2021.100996] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2021] [Revised: 07/22/2021] [Accepted: 07/29/2021] [Indexed: 11/20/2022] Open
Abstract
Prenatal opioid exposure has been linked to altered neurodevelopment and visual problems such as strabismus and nystagmus. The neural substrate underlying these alterations is unclear. Resting-state functional connectivity MRI (rsfMRI) is an advanced and well-established technique to evaluate brain networks. Few studies have examined the effects of prenatal opioid exposure on resting-state network connectivity in infancy. In this pilot study, we characterized network connectivity in opioid-exposed infants (n = 19) and controls (n = 20) between 4–8 weeks of age using both a whole-brain connectomic approach and a seed-based approach. Prenatal opioid exposure was associated with differences in distribution of betweenness centrality and connection length, with positive connections unique to each group significantly longer than common connections. The unique connections in the opioid-exposed group were more often inter-network connections while unique connections in controls and connections common to both groups were more often intra-network. The opioid-exposed group had smaller network volumes particularly in the primary visual network, but similar network strength as controls. Network topologies as determined by dice similarity index were different between groups, particularly in visual and executive control networks. These results may provide insight into the neural basis for the developmental and visual problems associated with prenatal opioid exposure.
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Affiliation(s)
- Stephanie L Merhar
- Perinatal Institute, Division of Neonatology, Cincinnati Children's Hospital and University of Cincinnati, Department of Pediatrics, Cincinnati, OH, USA.
| | - Weixiong Jiang
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Nehal A Parikh
- Perinatal Institute, Division of Neonatology, Cincinnati Children's Hospital and University of Cincinnati, Department of Pediatrics, Cincinnati, OH, USA
| | - Weiyan Yin
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Zhen Zhou
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Jean A Tkach
- Imaging Research Center, Cincinnati Children's Hospital, Cincinnati, OH, USA; Department of Radiology, Cincinnati Children's Hospital, Cincinnati, OH, USA
| | - Li Wang
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Beth M Kline-Fath
- Imaging Research Center, Cincinnati Children's Hospital, Cincinnati, OH, USA; Department of Radiology, Cincinnati Children's Hospital, Cincinnati, OH, USA
| | - Lili He
- Perinatal Institute, Division of Neonatology, Cincinnati Children's Hospital and University of Cincinnati, Department of Pediatrics, Cincinnati, OH, USA
| | - Adebayo Braimah
- Imaging Research Center, Cincinnati Children's Hospital, Cincinnati, OH, USA
| | - Jennifer Vannest
- Department of Communication Sciences and Disorders, College of Allied Health Sciences, University of Cincinnati, Cincinnati, OH, USA
| | - Weili Lin
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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Mäki-Marttunen V. Pupil-based States of Brain Integration across Cognitive States. Neuroscience 2021; 471:61-71. [PMID: 34303781 DOI: 10.1016/j.neuroscience.2021.07.016] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2020] [Revised: 06/14/2021] [Accepted: 07/15/2021] [Indexed: 01/21/2023]
Abstract
Arousal is a potent mechanism that provides the brain with functional flexibility and adaptability to external conditions. Within the wake state, arousal levels driven by activity in the neuromodulatory systems are related to specific signatures of neural activation and brain synchrony. However, direct evidence is still lacking on the varying effects of arousal on macroscopic brain characteristics and across a variety of cognitive states in humans. Using a concurrent fMRI-pupillometry approach, we used pupil size as a proxy for arousal and obtained patterns of brain integration associated with increasing arousal levels. We carried out this analysis on resting-state data and data from two attentional tasks implicating different cognitive processes. We found that an increasing level of arousal was related to a state of increased brain integration. This effect was prominent in the salience, visual and default-mode networks in all conditions, while other regions showed task-specificity. Increased integration in the salience network was also related to faster pupil dilation in the two attentional tasks. Furthermore, task performance was related to arousal level, with lower accuracy at higher level of arousal. Taken together, our study provides evidence in humans for pupil size as an index of brain network state, and supports the role of arousal as a switch that drives brain coordination in specific brain regions according to the cognitive state.
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Affiliation(s)
- Verónica Mäki-Marttunen
- Department of Psychology, University of Oslo, Postboks 1094, Blindern, 0317 Oslo, Norway; Cognitive Psychology Unit, Faculty of Social Sciences, Leiden University, Pieter de la Court, Wassenaarseweg 52, 2333 AK Leiden, Netherlands.
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Broeders TAA, Schoonheim MM, Vink M, Douw L, Geurts JJG, van Leeuwen JMC, Vinkers CH. Dorsal attention network centrality increases during recovery from acute stress exposure. NEUROIMAGE-CLINICAL 2021; 31:102721. [PMID: 34134017 PMCID: PMC8214139 DOI: 10.1016/j.nicl.2021.102721] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Revised: 05/19/2021] [Accepted: 06/04/2021] [Indexed: 12/17/2022]
Abstract
Stress is a major risk factor for the development of almost all psychiatric disorders. In addition to the acute stress response, an efficient recovery in the aftermath of stress is important for optimal resilience. Increased stress vulnerability across psychiatric disorders may therefore be related to altered trajectories during the recovery phase following stress. Such recovery trajectories can be quantified by changes in functional brain networks. This study therefore evaluated longitudinal functional network changes related to stress in healthy individuals (N = 80), individuals at risk for psychiatric disorders (healthy siblings of schizophrenia patients) (N = 39), and euthymic bipolar I disorder (BD) patients (N = 36). Network changes were evaluated before and at 20 and 90 min after onset of an experimental acute stress task (Trier Social Stress Test) or a control condition. Whole-brain functional networks were analyzed using eigenvector centrality as a proxy for network importance, centrality change over time was related to the acute stress response and recovery for each group. In healthy individuals, centrality of the dorsal attention network (DAN; p = 0.007) changed over time in relation to stress. More specifically, DAN centrality increased during the recovery phase after acute stress exposure (p = 0.020), while no DAN centrality change was observed during the initial stress response (p = 0.626). Such increasing DAN centrality during stress recovery was also found in healthy siblings (p = 0.016), but not in BD patients (p = 0.554). This study highlights that temporally complex and precise changes in network configuration are vital to understand the response to and recovery from stress.
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Affiliation(s)
- T A A Broeders
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
| | - M M Schoonheim
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - M Vink
- Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands; Department of Experimental, Utrecht University, Utrecht, The Netherlands; Department Developmental Psychology, Utrecht University, Utrecht, The Netherlands
| | - L Douw
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - J J G Geurts
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - J M C van Leeuwen
- Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands; Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition, and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - C H Vinkers
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands; Department of Psychiatry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands; Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands
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Lee J, Ko W, Kang E, Suk HI. A unified framework for personalized regions selection and functional relation modeling for early MCI identification. Neuroimage 2021; 236:118048. [PMID: 33878379 DOI: 10.1016/j.neuroimage.2021.118048] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Accepted: 04/02/2021] [Indexed: 12/21/2022] Open
Abstract
Resting-state functional magnetic resonance imaging (rs-fMRI) has been widely adopted to investigate functional abnormalities in brain diseases. Rs-fMRI data is unsupervised in nature because the psychological and neurological labels are coarse-grained, and no accurate region-wise label is provided along with the complex co-activities of multiple regions. To the best of our knowledge, most studies regarding univariate group analysis or multivariate pattern recognition for brain disease identification have focused on discovering functional characteristics shared across subjects; however, they have paid less attention to individual properties of neural activities that result from different symptoms or degrees of abnormality. In this work, we propose a novel framework that can identify subjects with early-stage mild cognitive impairment (eMCI) and consider individual variability by learning functional relations from automatically selected regions of interest (ROIs) for each subject concurrently. In particular, we devise a deep neural network composed of a temporal embedding module, an ROI selection module, and a disease-identification module. Notably, the ROI selection module is equipped with a reinforcement learning mechanism so it adaptively selects ROIs to facilitate the learning of discriminative feature representations from a temporally embedded blood-oxygen-level-dependent signals. Furthermore, our method allows us to capture the functional relations of a subject-specific ROI subset through the use of a graph-based neural network. Our method considers individual characteristics for diagnosis, as opposed to most conventional methods that identify the same biomarkers across subjects within a group. Based on the ADNI cohort, we validate the effectiveness of our method by presenting the superior performance of our network in eMCI identification. Furthermore, we provide insightful neuroscientific interpretations by analyzing the regions selected for the eMCI classification.
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Affiliation(s)
- Jiyeon Lee
- Department of Brain and Cognitive Engineering, Korea University, Republic of Korea
| | - Wonjun Ko
- Department of Brain and Cognitive Engineering, Korea University, Republic of Korea
| | - Eunsong Kang
- Department of Brain and Cognitive Engineering, Korea University, Republic of Korea
| | - Heung-Il Suk
- Department of Brain and Cognitive Engineering, Korea University, Republic of Korea; Department of Artificial Intelligence, Korea University, Republic of Korea.
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Trofimova A, Smith JL, Ahluwalia V, Hurtado J, Gore RK, Allen JW. Alterations in Resting-State Functional Brain Connectivity and Correlations with Vestibular/Ocular-Motor Screening Measures in Postconcussion Vestibular Dysfunction. J Neuroimaging 2021; 31:277-286. [PMID: 33476477 DOI: 10.1111/jon.12834] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Revised: 12/31/2020] [Accepted: 12/31/2020] [Indexed: 11/30/2022] Open
Abstract
BACKGROUND AND PURPOSE Vestibular symptoms after concussion are common and associated with protracted recovery. The purpose of this study is to define resting-state functional MRI (rs-fMRI) brain connectivity alterations in patients with postconcussion vestibular dysfunction (PCVD) and correlations between rs-fMRI connectivity and symptoms provoked during Vestibular/Ocular-Motor Screening (VOMS) assessment. METHODS Prospective IRB approved study. STUDY GROUP 12 subjects with subacute PCVD (2-10 weeks); control group: 10 age-matched subjects without history of concussion or vestibular impairment. Both groups underwent clinical vestibular assessment. rs-fMRI was acquired on 3.0T Siemens Trio with a 12-channel head coil. rs-fMRI data analysis included independent component analysis-based functional connectivity group differences, graph theory analysis, and ROI-to-ROI connectivity correlation analysis with VOMS clinical derivatives. Group difference maps between resting-state networks were calculated using dual regression method and corrected for multiple comparisons. Correlation analysis between ROI-to-ROI rs-fMRI brain activation and VOMS assessment ratings was performed using Pearson correlation coefficient, with a significance threshold of P ≤ .05. RESULTS Compared to controls, PCVD group demonstrated significantly increased rs-fMRI connectivity between the default-mode network and right middle frontal gyrus and right postcentral gyrus; and between a vestibular-sensorimotor network and right prefrontal cortex. Significant positive correlations were found between clinical derivative VOMS scores and components of the vestibular, visual networks, and multisensory processing cortical representations. CONCLUSION Altered rs-fMRI brain connectivity with increased connectivity of visual input, multisensory processing, and spatial memory in PCVD is correlative with clinical derivative VOMS scores, suggesting maladaptive brain plasticity underlying vestibular symptomatology.
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Affiliation(s)
- Anna Trofimova
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA
| | - Jeremy L Smith
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA
| | - Vishwadeep Ahluwalia
- Georgia Statue University/Georgia Tech Center for Advanced Brain Imaging, Atlanta, GA
| | | | - Russell K Gore
- Shepherd Center, Atlanta, GA.,Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA
| | - Jason W Allen
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA.,Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA.,Department of Neurology, Emory University, Atlanta, GA
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Identifying Diurnal Variability of Brain Connectivity Patterns Using Graph Theory. Brain Sci 2021; 11:brainsci11010111. [PMID: 33467070 PMCID: PMC7830976 DOI: 10.3390/brainsci11010111] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2020] [Revised: 01/11/2021] [Accepted: 01/13/2021] [Indexed: 11/18/2022] Open
Abstract
Significant differences exist in human brain functions affected by time of day and by people’s diurnal preferences (chronotypes) that are rarely considered in brain studies. In the current study, using network neuroscience and resting-state functional MRI (rs-fMRI) data, we examined the effect of both time of day and the individual’s chronotype on whole-brain network organization. In this regard, 62 participants (39 women; mean age: 23.97 ± 3.26 years; half morning- versus half evening-type) were scanned about 1 and 10 h after wake-up time for morning and evening sessions, respectively. We found evidence for a time-of-day effect on connectivity profiles but not for the effect of chronotype. Compared with the morning session, we found relatively higher small-worldness (an index that represents more efficient network organization) in the evening session, which suggests the dominance of sleep inertia over the circadian and homeostatic processes in the first hours after waking. Furthermore, local graph measures were changed, predominantly across the left hemisphere, in areas such as the precentral gyrus, putamen, inferior frontal gyrus (orbital part), inferior temporal gyrus, as well as the bilateral cerebellum. These findings show the variability of the functional neural network architecture during the day and improve our understanding of the role of time of day in resting-state functional networks.
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Jiang H, Cao P, Xu M, Yang J, Zaiane O. Hi-GCN: A hierarchical graph convolution network for graph embedding learning of brain network and brain disorders prediction. Comput Biol Med 2020; 127:104096. [DOI: 10.1016/j.compbiomed.2020.104096] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Revised: 10/24/2020] [Accepted: 10/24/2020] [Indexed: 02/06/2023]
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Liu C, Jiao L, Li Z, Timmer K, Wang R. Language control network adapts to second language learning: A longitudinal rs-fMRI study. Neuropsychologia 2020; 150:107688. [PMID: 33212139 DOI: 10.1016/j.neuropsychologia.2020.107688] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2020] [Revised: 08/20/2020] [Accepted: 11/10/2020] [Indexed: 12/31/2022]
Abstract
The current longitudinal resting-state functional magnetic resonance imaging study examined changes in language control network after one year of L2 English classroom learning. A group of Chinese college freshmen majoring in English underwent two scans, one before (i.e., Session 1) and one after (i.e., Session 2) the one-year L2 courses. Learners' language control abilities were assessed via a behavioral language switching task. Our graph theory and functional connectivity analyses revealed that with increased exposure to the L2, nodal betweenness in language control areas, such as the dorsal anterior cingulate cortex (dACC), decreased and connectivity between dACC and pre-supplementary motor area (pre-SMA) increased. Critically, these neural changes were correlated with participants' behavioral performance on the language switching task. Taken together, these findings suggest that the language control network in resting brain could be modulated by long-term L2 learning in a naturalistic classroom setting, and that the dACC/pre-SMA complex appears to play a critical role in language control.
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Affiliation(s)
- Cong Liu
- Department of Psychology, Normal College & School of Teacher Education, Qingdao University, Qingdao, China; Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, & Guangdong Provincial Key Laboratory of Mental Health and Cognitive Science, Center for Studies of Psychological Application, School of Psychology, South China Normal University, Guangzhou, China
| | - Lu Jiao
- Department of Psychology, Normal College & School of Teacher Education, Qingdao University, Qingdao, China
| | - Zilong Li
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, & Guangdong Provincial Key Laboratory of Mental Health and Cognitive Science, Center for Studies of Psychological Application, School of Psychology, South China Normal University, Guangzhou, China
| | - Kalinka Timmer
- Psychology of Language and Bilingualism Lab, Institute of Psychology, Jagiellonian University, Kraków, Poland
| | - Ruiming Wang
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, & Guangdong Provincial Key Laboratory of Mental Health and Cognitive Science, Center for Studies of Psychological Application, School of Psychology, South China Normal University, Guangzhou, China.
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International Federation of Clinical Neurophysiology (IFCN) – EEG research workgroup: Recommendations on frequency and topographic analysis of resting state EEG rhythms. Part 1: Applications in clinical research studies. Clin Neurophysiol 2020; 131:285-307. [DOI: 10.1016/j.clinph.2019.06.234] [Citation(s) in RCA: 94] [Impact Index Per Article: 23.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2017] [Revised: 05/17/2019] [Accepted: 06/02/2019] [Indexed: 01/22/2023]
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43
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Graph theory and network topological metrics may be the potential biomarker in Parkinson’s disease. J Clin Neurosci 2019; 68:235-242. [DOI: 10.1016/j.jocn.2019.07.082] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2018] [Revised: 06/20/2019] [Accepted: 07/29/2019] [Indexed: 01/05/2023]
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Benito-León J, Sanz-Morales E, Melero H, Louis ED, Romero JP, Rocon E, Malpica N. Graph theory analysis of resting-state functional magnetic resonance imaging in essential tremor. Hum Brain Mapp 2019; 40:4686-4702. [PMID: 31332912 DOI: 10.1002/hbm.24730] [Citation(s) in RCA: 43] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2019] [Revised: 07/05/2019] [Accepted: 07/08/2019] [Indexed: 11/10/2022] Open
Abstract
Essential tremor (ET) is a neurological disease with both motor and nonmotor manifestations; however, little is known about its underlying brain basis. Furthermore, the overall organization of the brain network in ET remains largely unexplored. We investigated the topological properties of brain functional network, derived from resting-state functional magnetic resonance imaging (MRI) data, in 23 ET patients versus 23 healthy controls. Graph theory analysis was used to assess the functional network organization. At the global level, the functional network of ET patients was characterized by lower small-worldness values than healthy controls-less clustered functionality of the brain. At the regional level, compared with the healthy controls, ET patients showed significantly higher values of global efficiency, cost and degree, and a shorter average path length in the left inferior frontal gyrus (pars opercularis), right inferior temporal gyrus (posterior division and temporo-occipital part), right inferior lateral occipital cortex, left paracingulate, bilateral precuneus bilaterally, left lingual gyrus, right hippocampus, left amygdala, nucleus accumbens bilaterally, and left middle temporal gyrus (posterior part). In addition, ET patients showed significant higher local efficiency and clustering coefficient values in frontal medial cortex bilaterally, subcallosal cortex, posterior cingulate cortex, parahippocampal gyri bilaterally (posterior division), right lingual gyrus, right cerebellar flocculus, right postcentral gyrus, right inferior semilunar lobule of cerebellum and culmen of vermis. Finally, the right intracalcarine cortex and the left orbitofrontal cortex showed a shorter average path length in ET patients, while the left frontal operculum and the right planum polare showed a higher betweenness centrality in ET patients. In conclusion, the efficiency of the overall brain functional network in ET is disrupted. Further, our results support the concept that ET is a disorder that disrupts widespread brain regions, including those outside of the brain regions responsible for tremor.
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Affiliation(s)
- Julián Benito-León
- Department of Neurology, University Hospital 12 de Octubre, Madrid, Spain.,Center of Biomedical Network Research on Neurodegenerative Diseases (CIBERNED), Madrid, Spain.,Department of Medicine, Faculty of Medicine, Complutense University, Madrid, Spain
| | - Emilio Sanz-Morales
- Medical Image Analysis Laboratory (LAIMBIO), Rey Juan Carlos University, Madrid, Spain
| | - Helena Melero
- Medical Image Analysis Laboratory (LAIMBIO), Rey Juan Carlos University, Madrid, Spain
| | - Elan D Louis
- Department of Neurology, Yale School of Medicine, Yale University, New Haven, Connecticut.,Department of Chronic Disease Epidemiology, Yale School of Public Health, Yale University, New Haven, Connecticut.,Center for Neuroepidemiology and Clinical Neurological Research, Yale School of Medicine, Yale University, New Haven, Connecticut
| | - Juan P Romero
- Faculty of Biosanitary Sciences, Francisco de Vitoria University, Madrid, Spain.,Brain Damage Unit, Hospital Beata Maria Ana, Madrid, Spain
| | - Eduardo Rocon
- Neural and Cognitive Engineering group, Center for Automation and Robotics (CAR) CSIC-UPM, Arganda del Rey, Spain
| | - Norberto Malpica
- Medical Image Analysis Laboratory (LAIMBIO), Rey Juan Carlos University, Madrid, Spain
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Thibaut F. New ways of understanding brain neurocircuitry. DIALOGUES IN CLINICAL NEUROSCIENCE 2018. [PMID: 30250385 PMCID: PMC6136127 DOI: 10.31887/dcns.2018.20.2/fthibaut] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Inside the brain, neural regions dynamically interact at multiple spatial and temporal scales through a highly structured and adaptive neurocircuitry. Comprehensive maps of brain connectivity have led to the emerging field of connectomics. Graph theory methods are interesting tools to improve our understanding of the brain as a complex interconnected system.
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Affiliation(s)
- Florence Thibaut
- Professor of Psychiatry, University Hospital Cochin (site Tarnier), Faculty of Medicine Paris Descartes (University SorbonneParis Cite), INSERM U 894 Centre Psychiatry-Neurosctences, Paris, France
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Oliveira ÍAF, Guimarães TM, Souza RM, Dos Santos AC, Machado-de-Sousa JP, Hallak JEC, Leoni RF. Brain functional and perfusional alterations in schizophrenia: an arterial spin labeling study. Psychiatry Res Neuroimaging 2018; 272:71-78. [PMID: 29229240 DOI: 10.1016/j.pscychresns.2017.12.001] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/18/2017] [Revised: 11/30/2017] [Accepted: 12/01/2017] [Indexed: 01/10/2023]
Abstract
Schizophrenia is a severe mental disorder that affects the anatomy and function of the brain, with an impact on one's thoughts, feelings, and behavior. The purpose of the study was to investigate cerebral blood flow (CBF) and brain connectivity in a group of patients with schizophrenia. Pseudo-continuous arterial spin labeling (pCASL) images were acquired from 28 patients in treatment and 28 age-matched healthy controls. Mean CBF and connectivity patterns were assessed. Schizophrenia patients had decreased CBF in the bilateral frontal pole and superior frontal gyrus, right medial frontal gyrus, triangular and opercular parts of the inferior frontal gyrus, posterior division of the left supramarginal gyrus, superior and inferior divisions of the left lateral occipital cortex, and bilateral occipital pole. Moreover, through different methods to assess connectivity, our results showed abnormal connectivity patterns in regions involved in motor, sensorial, and cognitive functions. Using pCASL, a non-invasive technique, we found CBF deficits and altered functional organization of the brain in schizophrenia patients that are associated with the symptoms and characteristics of the disorder.
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Affiliation(s)
- Ícaro A F Oliveira
- Inbrain Lab, Department of Physics, FFCLRP, University of Sao Paulo, Ribeirao Preto, Brazil
| | - Tiago M Guimarães
- Department of Neuroscience and Behavior, FMRP, University of Sao Paulo, Ribeirao Preto, Brazil
| | - Roberto M Souza
- Department of Neuroscience and Behavior, FMRP, University of Sao Paulo, Ribeirao Preto, Brazil
| | - Antônio C Dos Santos
- Department of Medical Clinic, FMRP, University of Sao Paulo, Ribeirao Preto, Brazil
| | - João Paulo Machado-de-Sousa
- Department of Neuroscience and Behavior, FMRP, University of Sao Paulo, Ribeirao Preto, Brazil; National Institute of Science and Technology - Translational Medicine (INCT-TM), CNPq, Brazil
| | - Jaime E C Hallak
- Department of Neuroscience and Behavior, FMRP, University of Sao Paulo, Ribeirao Preto, Brazil; National Institute of Science and Technology - Translational Medicine (INCT-TM), CNPq, Brazil
| | - Renata F Leoni
- Inbrain Lab, Department of Physics, FFCLRP, University of Sao Paulo, Ribeirao Preto, Brazil.
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