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Rocca MA, D’Amore G, Valsasina P, Tedone N, Meani A, Filippi M. 2.5-Year changes of connectivity dynamism are relevant for physical and cognitive deterioration in multiple sclerosis. Mult Scler 2024; 30:546-557. [PMID: 38372039 PMCID: PMC11010569 DOI: 10.1177/13524585241231155] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Revised: 01/11/2024] [Accepted: 01/20/2024] [Indexed: 02/20/2024]
Abstract
BACKGROUND In MS, functional connectivity (FC) dynamism may influence disease evolution. OBJECTIVES The objective is to assess time-varying functional connectivity (TVFC) changes over time at 2.5-year follow-up in MS patients according to physical and cognitive worsening. METHODS We collected 3T magnetic resonance imaging (MRI) for TVFC assessment (performed using sliding-window analysis of centrality) and clinical evaluations at baseline and 2.5-year follow-up from 28 healthy controls and 129 MS patients. Of these, 79 underwent baseline and follow-up neuropsychological assessment. At 2.5 years, physical/cognitive worsening was defined according to disability/neuropsychological score changes. RESULTS At follow-up, 25/129 (19.3%) MS patients worsened physically and 14/79 (17.7%) worsened cognitively. At baseline, MS patients showed reduced TVFC versus controls. At 2.5-year follow-up, no TVFC changes were detected in controls. Conversely, TVFC decreased over time in parieto-temporal regions in stable MS patients and in default-mode network in worsened MS. In physically worsened MS, basal ganglia TVFC reductions were also found. Reduced TVFC over time in the putamen in physically worsened and reduced TVFC in the precuneus in cognitively worsened were significant versus stable MS. DISCUSSION At 2.5-year follow-up, default-mode network TVFC reductions were found in worsening MS. Moreover, reduced deep gray matter TVFC characterized physically worsened patients, whereas precuneus involvement characterized cognitively worsened MS patients.
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Affiliation(s)
- Maria A Rocca
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy/
- Vita-Salute San Raffaele University, Milan, Italy
| | - Giulia D’Amore
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Paola Valsasina
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Nicolò Tedone
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Alessandro Meani
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy/Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
- Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy
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2
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Zheng C, Cao Y, Li Y, Ye Z, Jia X, Li M, Yu Y, Liu W. Long-term table tennis training alters dynamic functional connectivity and white matter microstructure in large scale brain regions. Brain Res 2024; 1838:148889. [PMID: 38552934 DOI: 10.1016/j.brainres.2024.148889] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2024] [Revised: 03/22/2024] [Accepted: 03/26/2024] [Indexed: 05/12/2024]
Abstract
Table tennis training has been employed as an exercise treatment to enhance cognitive brain functioning in patients with mental illnesses. However, research on its underlying mechanisms remains limited. In this study, we investigated functional and structural changes in large-scale brain regions between 20 table tennis players (TTPs) and 21 healthy controls (HCs) using 7-Tesla magnetic resonance imaging (MRI) techniques. Compared with those of HCs, TTPs exhibited significantly greater fractional anisotropy (FA) and axial diffusivity (AD) values in multiple fiber tracts. We used the locations with the most significant structural changes in white matter as the seed areas and then compared static and dynamic functional connectivity (sFC and dFC). Brodmann 11, located in the orbitofrontal cortex, showed altered dFC values to large-scale brain regions, such as the occipital lobe, thalamus, and cerebellar hemispheres, in TTPs. Brodmann 48, located in the temporal lobe, showed altered dFC to the parietal lobe, frontal lobe, cerebellum, and occipital lobe. Furthermore, the AD values of the forceps minor (Fmi) and right anterior thalamic radiations (ATRs) were negatively correlated with useful field of view (UFOV) test scores in TTPs. Our results suggest that table tennis players exhibit a unique pattern of dynamic neural activity, this provides evidence for potential mechanisms through which table tennis interventions can enhance attention and other cognitive functions.
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Affiliation(s)
- Chanying Zheng
- Interdisciplinary Institute of Neuroscience and Technology, Key Laboratory of Medical Neurobiology of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, China; Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Yuting Cao
- Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Yuyang Li
- Interdisciplinary Institute of Neuroscience and Technology, Key Laboratory of Medical Neurobiology of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, China
| | | | - Xize Jia
- School of Psychology, Zhejiang Normal University, Jinhua, China
| | - Mengting Li
- School of Psychology, Zhejiang Normal University, Jinhua, China.
| | - Yang Yu
- Psychiatry Department, the Second Affiliated Hospital Zhejiang University School of Medicine, Zhejiang, Hangzhou, China.
| | - Wenming Liu
- Department of Sport Science, College of Education, Zhejiang University, Hangzhou, China.
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Wang Y, Yang Z, Zheng X, Liang X, Chen J, He T, Zhu Y, Wu L, Huang M, Zhang N, Zhou F. Temporal and topological properties of dynamic networks reflect disability in patients with neuromyelitis optica spectrum disorders. Sci Rep 2024; 14:4199. [PMID: 38378887 PMCID: PMC10879085 DOI: 10.1038/s41598-024-54518-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2023] [Accepted: 02/13/2024] [Indexed: 02/22/2024] Open
Abstract
Approximately 36% of patients with neuromyelitis optica spectrum disorders (NMOSD) suffer from severe visual and motor disability (blindness or light perception or unable to walk) with abnormalities of whole-brain functional networks. However, it remains unclear how whole-brain functional networks and their dynamic properties are related to clinical disability in patients with NMOSD. Our study recruited 30 NMOSD patients (37.70 ± 11.99 years) and 45 healthy controls (HC, 41.84 ± 11.23 years). The independent component analysis, sliding-window approach and graph theory analysis were used to explore the static strength, time-varying and topological properties of large-scale functional networks and their associations with disability in NMOSD. Compared to HC, NMOSD patients showed significant alterations in dynamic networks rather than static networks. Specifically, NMOSD patients showed increased occurrence (fractional occupancy; P < 0.001) and more dwell times of the low-connectivity state (P < 0.001) with fewer transitions (P = 0.028) between states than HC, and higher fractional occupancy, increased dwell times of the low-connectivity state and lower transitions were related to more severe disability. Moreover, NMOSD patients exhibited altered small-worldness, decreased degree centrality and reduced clustering coefficients of hub nodes in dynamic networks, related to clinical disability. NMOSD patients exhibited higher occurrence and more dwell time in low-connectivity states, along with fewer transitions between states and decreased topological organizations, revealing the disrupted communication and coordination among brain networks over time. Our findings could provide new perspective to help us better understand the neuropathological mechanism of the clinical disability in NMOSD.
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Affiliation(s)
- Yao Wang
- Department of Radiology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330006, Jiangxi Province, China
- Clinical Research Center for Medical Imaging in Jiangxi Province, Nanchang, 330006, Jiangxi Province, China
| | - Ziwei Yang
- Department of Radiology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330006, Jiangxi Province, China
- Clinical Research Center for Medical Imaging in Jiangxi Province, Nanchang, 330006, Jiangxi Province, China
| | - Xiumei Zheng
- Department of Radiology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330006, Jiangxi Province, China
- Clinical Research Center for Medical Imaging in Jiangxi Province, Nanchang, 330006, Jiangxi Province, China
| | - Xiao Liang
- Department of Radiology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330006, Jiangxi Province, China
- Clinical Research Center for Medical Imaging in Jiangxi Province, Nanchang, 330006, Jiangxi Province, China
| | - Jin Chen
- Department of Neurology, The First Affiliated Hospital of Nanchang University, Nanchang, 330006, Jiangxi Province, China
| | - Ting He
- Department of Radiology, Pingxiang People's Hospital, Pingxiang, 337055, Jiangxi Province, China
| | - Yanyan Zhu
- Department of Radiology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330006, Jiangxi Province, China
- Clinical Research Center for Medical Imaging in Jiangxi Province, Nanchang, 330006, Jiangxi Province, China
| | - Lin Wu
- Department of Radiology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330006, Jiangxi Province, China
- Clinical Research Center for Medical Imaging in Jiangxi Province, Nanchang, 330006, Jiangxi Province, China
| | - Muhua Huang
- Department of Radiology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330006, Jiangxi Province, China
- Clinical Research Center for Medical Imaging in Jiangxi Province, Nanchang, 330006, Jiangxi Province, China
| | - Ningnannan Zhang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, China.
| | - Fuqing Zhou
- Department of Radiology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330006, Jiangxi Province, China.
- Clinical Research Center for Medical Imaging in Jiangxi Province, Nanchang, 330006, Jiangxi Province, China.
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Al‐Sa'd M, Vanhatalo S, Tokariev A. Multiplex dynamic networks in the newborn brain disclose latent links with neurobehavioral phenotypes. Hum Brain Mapp 2024; 45:e26610. [PMID: 38339895 PMCID: PMC10839739 DOI: 10.1002/hbm.26610] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Revised: 01/08/2024] [Accepted: 01/16/2024] [Indexed: 02/12/2024] Open
Abstract
The higher brain functions arise from coordinated neural activity between distinct brain regions, but the spatial, temporal, and spectral complexity of these functional connectivity networks (FCNs) has challenged the identification of correlates with neurobehavioral phenotypes. Characterizing behavioral correlates of early life FCNs is important to understand the activity dependent emergence of neurodevelopmental performance and for improving health outcomes. Here, we develop an analysis pipeline for identifying multiplex dynamic FCNs that combine spectral and spatiotemporal characteristics of the newborn cortical activity. This data-driven approach automatically uncovers latent networks that show robust neurobehavioral correlations and consistent effects by in utero drug exposure. Altogether, the proposed pipeline provides a robust end-to-end solution for an objective assessment and quantitation of neurobehaviorally meaningful network constellations in the highly dynamic cortical functions.
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Affiliation(s)
- Mohammad Al‐Sa'd
- BABA Center, Pediatric Research Center, Department of Clinical Neurophysiology, Children's Hospital, HUS imaging, HUS Diagnostic CenterUniversity of Helsinki and Helsinki University HospitalHelsinkiFinland
- Department of PhysiologyUniversity of HelsinkiHelsinkiFinland
- Faculty of Information Technology and Communication SciencesTampere UniversityTampereFinland
| | - Sampsa Vanhatalo
- BABA Center, Pediatric Research Center, Department of Clinical Neurophysiology, Children's Hospital, HUS imaging, HUS Diagnostic CenterUniversity of Helsinki and Helsinki University HospitalHelsinkiFinland
- Department of PhysiologyUniversity of HelsinkiHelsinkiFinland
| | - Anton Tokariev
- BABA Center, Pediatric Research Center, Department of Clinical Neurophysiology, Children's Hospital, HUS imaging, HUS Diagnostic CenterUniversity of Helsinki and Helsinki University HospitalHelsinkiFinland
- Department of PhysiologyUniversity of HelsinkiHelsinkiFinland
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Wang Y, Duan Y, Wu Y, Zhuo Z, Zhang N, Han X, Zeng C, Chen X, Huang M, Zhu Y, Li H, Cao G, Sun J, Li Y, Zhou F, Li Y. Male and female are not the same: a multicenter study of static and dynamic functional connectivity in relapse-remitting multiple sclerosis in China. Front Immunol 2023; 14:1216310. [PMID: 37885895 PMCID: PMC10597802 DOI: 10.3389/fimmu.2023.1216310] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Accepted: 08/30/2023] [Indexed: 10/28/2023] Open
Abstract
Background Sex-related effects have been observed in relapsing-remitting multiple sclerosis (RRMS), but their impact on functional networks remains unclear. Objective To investigate the sex-related differences in connectivity strength and time variability within large-scale networks in RRMS. Methods This is a multi-center retrospective study. A total of 208 RRMS patients (135 females; 37.55 ± 11.47 years old) and 228 healthy controls (123 females; 36.94 ± 12.17 years old) were included. All participants underwent clinical and MRI assessments. Independent component analysis was used to extract resting-state networks (RSNs). We assessed the connectivity strength using spatial maps (SMs) and static functional network connectivity (sFNC), evaluated temporal properties and dynamic functional network connectivity (dFNC) patterns of RSNs using dFNC, and investigated their associations with structural damage or clinical variables. Results For static connectivity, only male RRMS patients displayed decreased SMs in the attention network and reduced sFNC between the sensorimotor network and visual or frontoparietal networks compared with healthy controls [P<0.05, false discovery rate (FDR) corrected]. For dynamic connectivity, three recurring states were identified for all participants: State 1 (sparse connected state; 42%), State 2 (middle-high connected state; 36%), and State 3 (high connected state; 16%). dFNC analyses suggested that altered temporal properties and dFNC patterns only occurred in females: female patients showed a higher fractional time (P<0.001) and more dwell time in State 1 (P<0.001) with higher transitions (P=0.004) compared with healthy females. Receiver operating characteristic curves revealed that the fraction time and mean dwell time of State 1 could significantly distinguish female patients from controls (area under the curve: 0.838-0.896). In addition, female patients with RRMS also mainly showed decreased dFNC in all states, particularly within cognitive networks such as the default mode, frontoparietal, and visual networks compared with healthy females (P < 0.05, FDR corrected). Conclusion Our results observed alterations in connectivity strength only in male patients and time variability in female patients, suggesting that sex-related effects may play an important role in the functional impairment and reorganization of RRMS.
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Affiliation(s)
- Yao Wang
- Department of Radiology, The First Affiliated Hospital, Nanchang University, Nanchang, Jiangxi, China
- Clinical Research Center For Medical Imaging In Jiangxi Province, Nanchang, Jiangxi, China
| | - Yunyun Duan
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yuling Wu
- Department of Radiology, The First Affiliated Hospital, Nanchang University, Nanchang, Jiangxi, China
- Clinical Research Center For Medical Imaging In Jiangxi Province, Nanchang, Jiangxi, China
| | - Zhizheng Zhuo
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Ningnannan Zhang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Xuemei Han
- Department of Neurology, China-Japan Union Hospital of Jilin University, Changchun, Jilin, China
| | - Chun Zeng
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Xiaoya Chen
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Muhua Huang
- Department of Radiology, The First Affiliated Hospital, Nanchang University, Nanchang, Jiangxi, China
- Clinical Research Center For Medical Imaging In Jiangxi Province, Nanchang, Jiangxi, China
| | - Yanyan Zhu
- Department of Radiology, The First Affiliated Hospital, Nanchang University, Nanchang, Jiangxi, China
- Clinical Research Center For Medical Imaging In Jiangxi Province, Nanchang, Jiangxi, China
| | - Haiqing Li
- Department of Radiology, Huashan Hospital, Fudan University, Shanghai, China
| | - Guanmei Cao
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Jie Sun
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Yongmei Li
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Fuqing Zhou
- Department of Radiology, The First Affiliated Hospital, Nanchang University, Nanchang, Jiangxi, China
- Clinical Research Center For Medical Imaging In Jiangxi Province, Nanchang, Jiangxi, China
| | - Yuxin Li
- Department of Radiology, Huashan Hospital, Fudan University, Shanghai, China
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Antypa D, Simos NJ, Panou T, Spyridaki E, Kagialis A, Kosteletou E, Kavroulakis E, Mastorodemos V, Papadaki E. Distinct hemodynamic and functional connectivity features of fatigue in clinically isolated syndrome and multiple sclerosis: accounting for the confounding effect of concurrent depression symptoms. Neuroradiology 2023:10.1007/s00234-023-03174-1. [PMID: 37301785 DOI: 10.1007/s00234-023-03174-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Accepted: 06/04/2023] [Indexed: 06/12/2023]
Abstract
PURPOSE This study aims to identify common and distinct hemodynamic and functional connectivity (FC) features for self-rated fatigue and depression symptoms in patients with clinically isolated syndrome (CIS) and relapsing-remitting multiple sclerosis (RR-MS). METHODS Twenty-four CIS, 29 RR-MS patients, and 39 healthy volunteers were examined using resting-state fMRI (rs-fMRI) to obtain whole-brain maps of (i) hemodynamic response patterns (through time shift analysis), (ii) FC (via intrinsic connectivity contrast maps), and (iii) coupling between hemodynamic response patterns and FC. Each regional map was correlated with fatigue scores, controlling for depression, and with depression scores, controlling for fatigue. RESULTS In CIS patients, the severity of fatigue was associated with accelerated hemodynamic response in the insula, hyperconnectivity of the superior frontal gyrus, and evidence of reduced hemodynamics-FC coupling in the left amygdala. In contrast, depression severity was associated with accelerated hemodynamic response in the right limbic temporal pole, hypoconnectivity of the anterior cingulate gyrus, and increased hemodynamics-FC coupling in the left amygdala. In RR-MS patients, fatigue was associated with accelerated hemodynamic response in the insula and medial superior frontal cortex, increased functional role of the left amygdala, and hypoconnectivity of the dorsal orbitofrontal cortex, while depression symptom severity was linked to delayed hemodynamic response in the medial superior frontal gyrus; hypoconnectivity of the insula, ventromedial thalamus, dorsolateral prefrontal cortex, and posterior cingulate; and decreased hemodynamics-FC coupling of the medial orbitofrontal cortex. CONCLUSION There are distinct FC and hemodynamic responses, as well as different magnitude and topography of hemodynamic connectivity coupling, associated with fatigue and depression in early and later stages of MS.
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Affiliation(s)
- Despina Antypa
- Department of Psychiatry, School of Medicine, University of Crete, University Hospital of Heraklion, Crete, Greece
| | - Nicholas John Simos
- Computational Bio-Medicine Laboratory, Institute of Computer Science, Foundation for Research and Technology, Hellas, Heraklion, Crete, Greece
| | - Theodora Panou
- Department of Psychiatry, School of Medicine, University of Crete, University Hospital of Heraklion, Crete, Greece
| | - Eirini Spyridaki
- Department of Psychiatry, School of Medicine, University of Crete, University Hospital of Heraklion, Crete, Greece
| | - Antonios Kagialis
- Department of Psychiatry, School of Medicine, University of Crete, University Hospital of Heraklion, Crete, Greece
| | - Emmanouela Kosteletou
- Institute of Applied Mathematics, Foundation for Research and Technology, Hellas, Heraklion, Crete, Greece
| | - Eleftherios Kavroulakis
- Department of Radiology, School of Medicine, University of Crete, University Hospital of Heraklion, Crete, Greece
| | - Vasileios Mastorodemos
- Department of Neurology, School of Medicine, University of Crete, University Hospital of Heraklion, Crete, Greece
| | - Efrosini Papadaki
- Computational Bio-Medicine Laboratory, Institute of Computer Science, Foundation for Research and Technology, Hellas, Heraklion, Crete, Greece.
- Department of Radiology, School of Medicine, University of Crete, University Hospital of Heraklion, Crete, Greece.
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Cagna CJ, Ceceli AO, Sandry J, Bhanji JP, Tricomi E, Dobryakova E. Altered functional connectivity during performance feedback processing in multiple sclerosis. Neuroimage Clin 2023; 37:103287. [PMID: 36516729 PMCID: PMC9755233 DOI: 10.1016/j.nicl.2022.103287] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Revised: 12/01/2022] [Accepted: 12/06/2022] [Indexed: 12/13/2022]
Abstract
Effective learning from performance feedback is vital for adaptive behavior regulation necessary for successful cognitive performance. Yet, how this learning operates in clinical groups that experience cognitive dysfunction is not well understood. Multiple sclerosis (MS) is an autoimmune, degenerative disease of the central nervous system characterized by physical and cognitive dysfunction. A highly prevalent impairment in MS is cognitive fatigue (CF). CF is associated with altered functioning within cortico-striatal regions that also facilitate feedback-based learning in neurotypical (NT) individuals. Despite this cortico-striatal overlap, research about feedback-based learning in MS, its associated neural underpinnings, and its sensitivity to CF, are all lacking. The present study investigated feedback-based learning ability in MS, as well as associated cortico-striatal function and connectivity. MS and NT participants completed a functional magnetic resonance imaging (fMRI) paired-word association task during which they received trial-by-trial monetary, non-monetary, and uninformative performance feedback. Despite reporting greater CF throughout the task, MS participants displayed comparable task performance to NTs, suggesting preserved feedback-based learning ability in the MS group. Both groups recruited the ventral striatum (VS), caudate nucleus, and ventromedial prefrontal cortex in response to the receipt of performance feedback, suggesting that people with MS also recruit cortico-striatal regions during feedback-based learning. However, compared to NT participants, MS participants also displayed stronger functional connectivity between the VS and task-relevant regions, including the left angular gyrus and right superior temporal gyrus, in response to feedback receipt. Results indicate that CF may not interfere with feedback-based learning in MS. Nonetheless, people with MS may recruit alternative connections with the striatum to assist with this form of learning. These findings have implications for cognitive rehabilitation treatments that incorporate performance feedback to remediate cognitive dysfunction in clinical populations.
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Affiliation(s)
- Christopher J Cagna
- Department of Psychology, Rutgers University - Newark, 101 Warren Street, Newark, NJ 07102, United States.
| | - Ahmet O Ceceli
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Place, New York, NY 10029, United States.
| | - Joshua Sandry
- Department of Psychology, Montclair State University, 1 Normal Avenue, Montclair, NJ 07043, United States.
| | - Jamil P Bhanji
- Department of Psychology, Rutgers University - Newark, 101 Warren Street, Newark, NJ 07102, United States.
| | - Elizabeth Tricomi
- Department of Psychology, Rutgers University - Newark, 101 Warren Street, Newark, NJ 07102, United States.
| | - Ekaterina Dobryakova
- Center for Traumatic Brain Injury Research, Kessler Foundation, 120 Eagle Rock Avenue, East Hanover, NJ 07936, United States.
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von Schwanenflug N, Koch SP, Krohn S, Broeders TAA, Lydon-Staley DM, Bassett DS, Schoonheim MM, Paul F, Finke C. Increased flexibility of brain dynamics in patients with multiple sclerosis. Brain Commun 2023; 5:fcad143. [PMID: 37188221 PMCID: PMC10176242 DOI: 10.1093/braincomms/fcad143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Revised: 03/08/2023] [Accepted: 04/28/2023] [Indexed: 05/17/2023] Open
Abstract
Patients with multiple sclerosis consistently show widespread changes in functional connectivity. Yet, alterations are heterogeneous across studies, underscoring the complexity of functional reorganization in multiple sclerosis. Here, we aim to provide new insights by applying a time-resolved graph-analytical framework to identify a clinically relevant pattern of dynamic functional connectivity reconfigurations in multiple sclerosis. Resting-state data from 75 patients with multiple sclerosis (N = 75, female:male ratio of 3:2, median age: 42.0 ± 11.0 years, median disease duration: 6 ± 11.4 years) and 75 age- and sex-matched controls (N = 75, female:male ratio of 3:2, median age: 40.2 ± 11.8 years) were analysed using multilayer community detection. Local, resting-state functional system and global levels of dynamic functional connectivity reconfiguration were characterized using graph-theoretical measures including flexibility, promiscuity, cohesion, disjointedness and entropy. Moreover, we quantified hypo- and hyper-flexibility of brain regions and derived the flexibility reorganization index as a summary measure of whole-brain reorganization. Lastly, we explored the relationship between clinical disability and altered functional dynamics. Significant increases in global flexibility (t = 2.38, PFDR = 0.024), promiscuity (t = 1.94, PFDR = 0.038), entropy (t = 2.17, PFDR = 0.027) and cohesion (t = 2.45, PFDR = 0.024) were observed in patients and were driven by pericentral, limbic and subcortical regions. Importantly, these graph metrics were correlated with clinical disability such that greater reconfiguration dynamics tracked greater disability. Moreover, patients demonstrate a systematic shift in flexibility from sensorimotor areas to transmodal areas, with the most pronounced increases located in regions with generally low dynamics in controls. Together, these findings reveal a hyperflexible reorganization of brain activity in multiple sclerosis that clusters in pericentral, subcortical and limbic areas. This functional reorganization was linked to clinical disability, providing new evidence that alterations of multilayer temporal dynamics play a role in the manifestation of multiple sclerosis.
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Affiliation(s)
- Nina von Schwanenflug
- Department of Neurology and Experimental Neurology, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin 10098, Germany
- Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin 10117, Germany
| | - Stefan P Koch
- Department of Experimental Neurology, Center for Stroke Research Berlin, Berlin 10117, Germany
- NeuroCure Cluster of Excellence and Charité Core Facility 7T Experimental MRIs, Charité - Universitätsmedizin Berlin, Berlin 10117, Germany
| | - Stephan Krohn
- Department of Neurology and Experimental Neurology, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin 10098, Germany
- Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin 10117, Germany
| | - Tommy A A Broeders
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam 1007 MB, The Netherlands
| | - David M Lydon-Staley
- Annenberg School for Communication, University of Pennsylvania, Philadelphia 19104, PA, USA
- Department of Bioengineering, University of Pennsylvania, Philadelphia 19104, PA, USA
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia 19104, PA, USA
| | - Dani S Bassett
- Department of Biological Engineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia 19104, PA, USA
- Department of Physics & Astronomy, College of Arts & Sciences, University of Pennsylvania, Philadelphia 19104, PA, USA
- Department of Electrical & Systems Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia 19104, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia 19104, PA, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia 19104, PA, USA
- Santa Fe Institute, Santa Fe 87501, NM, USA
| | - Menno M Schoonheim
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam 1007 MB, The Netherlands
| | - Friedemann Paul
- Department of Neurology and Experimental Neurology, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin 10098, Germany
- Experimental and Clinical Research Center, Max Delbrück Center for Molecular Medicine and Charité—Universitätsmedizin Berlin, Berlin 10117, Germany
- NeuroCure Clinical Research Center, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin 10017, Germany
| | - Carsten Finke
- Correspondence to: Carsten Finke Charité - Universitätsklinikum Berlin Department of Neurology and Experimental Neurology Campus Mitte, Bonhoeffer Weg 3, 10098 Berlin, Germany E-mail:
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Romanello A, Krohn S, von Schwanenflug N, Chien C, Bellmann-Strobl J, Ruprecht K, Paul F, Finke C. Functional connectivity dynamics reflect disability and multi-domain clinical impairment in patients with relapsing-remitting multiple sclerosis. Neuroimage Clin 2022; 36:103203. [PMID: 36179389 DOI: 10.1016/j.nicl.2022.103203] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Revised: 09/05/2022] [Accepted: 09/16/2022] [Indexed: 12/14/2022]
Abstract
BACKGROUND & AIM Multiple sclerosis (MS) is an autoimmune disease of the central nervous system associated with deficits in cognitive and motor functioning. While structural brain changes such as demyelination are an early hallmark of the disease, a characteristic profile of functional brain alterations in early MS is lacking. Functional neuroimaging studies at various disease stages have revealed complex and heterogeneous patterns of aberrant functional connectivity (FC) in MS, with previous studies largely being limited to a static account of FC. Thus, it remains unclear how time-resolved FC relates to variance in clinical disability status in early MS. We here aimed to characterize brain network organization in early MS patients with time-resolved FC analysis and to explore the relationship between disability status, multi-domain clinical outcomes and altered network dynamics. METHODS Resting-state functional MRI (rs-fMRI) data were acquired from 101 MS patients and 101 age- and sex-matched healthy controls (HC). Based on the Expanded Disability Status Score (EDSS), patients were split into two sub-groups: patients without clinical disability (EDSS ≤ 1, n = 36) and patients with mild to moderate levels of disability (EDSS ≥ 2, n = 39). Five dynamic FC states were extracted from whole-brain rs-fMRI data. Group differences in static and dynamic FC strength, across-state overall connectivity, dwell time, transition frequency, modularity, and global connectivity were assessed. Patients' impairment was quantified as custom clinical outcome z-scores (higher: worse) for the domains depressive symptoms, fatigue, motor, vision, cognition, total brain atrophy, and lesion load. Correlation analyses between functional measures and clinical outcomes were performed with Spearman partial correlation analyses controlling for age. RESULTS Patients with mild to moderate levels of disability exhibited a more widespread spatiotemporal pattern of altered FC and spent more time in a high-connectivity, low-occurrence state compared to patients without disability and HCs. Worse symptoms in all clinical outcome domains were positively associated with EDSS scores. Furthermore, depressive symptom severity was positively related to functional dynamics as measured by state-specific global connectivity and default mode network connectivity with attention networks, while fatigue and motor impairment were related to reduced frontoparietal network connectivity with the basal ganglia. CONCLUSIONS Despite comparably low impairment levels in early MS, we identified distinct connectivity alterations between patients with mild to moderate disability and those without disability, and these changes were sensitive to clinical outcomes in multiple domains. Furthermore, time-resolved analysis uncovered alterations in network dynamics and clinical correlations that remained undetected with conventional static analyses, showing that accounting for temporal dynamics helps disentangle the relationship between functional alterations, disability status, and symptoms in early MS.
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Schoonheim MM, Broeders TAA, Geurts JJG. The network collapse in multiple sclerosis: An overview of novel concepts to address disease dynamics. Neuroimage Clin 2022; 35:103108. [PMID: 35917719 PMCID: PMC9421449 DOI: 10.1016/j.nicl.2022.103108] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Revised: 07/01/2022] [Accepted: 07/10/2022] [Indexed: 11/16/2022]
Abstract
Multiple sclerosis (MS) can be considered as a network disorder. This review discusses network concepts in order to understand progression in MS. Damage is hypothesized to lead to a “network collapse” and clinical progression. New concepts are discussed that will likely influence the field in the near future. These include brain wiring, how regions communicate and robustness to damage.
Multiple sclerosis is a neuroinflammatory and neurodegenerative disorder of the central nervous system that can be considered a network disorder. In MS, lesional pathology continuously disconnects structural pathways in the brain, forming a disconnection syndrome. Complex functional network changes then occur that are poorly understood but closely follow clinical status. Studying these structural and functional network changes has been and remains crucial to further decipher complex symptoms like cognitive impairment and physical disability. Recent insights especially implicate the importance of monitoring network hubs in MS, like the thalamus and default-mode network which seem especially hit hard. Such network insights in MS have led to the hypothesis that as the network continues to become disconnected and dysfunctional, exceeding a certain threshold of network efficiency loss leads to a “network collapse”. After this collapse, crucial network hubs become rigid and overloaded, and at the same time a faster neurodegeneration and accelerated clinical (and cognitive) progression can be seen. As network neuroscience has evolved, the MS field can now move towards a clearer classification of the network collapse itself and specific milestone events leading up to it. Such an updated network-focused conceptual framework of MS could directly impact clinical decision making as well as the design of network-tailored rehabilitation strategies. This review therefore provides an overview of recent network concepts that have enhanced our understanding of clinical progression in MS, especially focusing on cognition, as well as new concepts that will likely move the field forward in the near future.
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Affiliation(s)
- Menno M Schoonheim
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
| | - Tommy A A Broeders
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Jeroen J G Geurts
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
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Rocca MA, Schoonheim MM, Valsasina P, Geurts JJG, Filippi M. Task- and resting-state fMRI studies in multiple sclerosis: From regions to systems and time-varying analysis. Current status and future perspective. Neuroimage Clin 2022; 35:103076. [PMID: 35691253 PMCID: PMC9194954 DOI: 10.1016/j.nicl.2022.103076] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Revised: 06/01/2022] [Accepted: 06/02/2022] [Indexed: 01/12/2023]
Abstract
Functional MRI is able to detect adaptive and maladaptive abnormalities at different MS stages. Increased fMRI activity is a feature of early MS, while progressive exhaustion of adaptive mechanisms is detected later on in the disease. Collapse of long-range connections and impaired hub integration characterize MS network reorganization. Time-varying connectivity analysis provides useful and complementary pieces of information to static functional connectivity. New perspectives might be the use of multimodal MRI and artificial intelligence.
Multiple sclerosis (MS) is a neurological disorder affecting the central nervous system and features extensive functional brain changes that are poorly understood but relate strongly to clinical impairments. Functional magnetic resonance imaging (fMRI) is a non-invasive, powerful technique able to map activity of brain regions and to assess how such regions interact for an efficient brain network. FMRI has been widely applied to study functional brain changes in MS, allowing to investigate functional plasticity consequent to disease-related structural injury. The first studies in MS using active fMRI tasks mainly aimed to study such plastic changes by identifying abnormal activity in salient brain regions (or systems) involved by the task. In later studies the focus shifted towards resting state (RS) functional connectivity (FC) studies, which aimed to map large-scale functional networks of the brain and to establish how MS pathology impairs functional integration, eventually leading to the hypothesized network collapse as patients clinically progress. This review provides a summary of the main findings from studies using task-based and RS fMRI and illustrates how functional brain alterations relate to clinical disability and cognitive deficits in this condition. We also give an overview of longitudinal studies that used task-based and RS fMRI to monitor disease evolution and effects of motor and cognitive rehabilitation. In addition, we discuss the results of studies using newer technologies involving time-varying FC to investigate abnormal dynamism and flexibility of network configurations in MS. Finally, we show some preliminary results from two recent topics (i.e., multimodal MRI analysis and artificial intelligence) that are receiving increasing attention. Together, these functional studies could provide new (conceptual) insights into disease stage-specific mechanisms underlying progression in MS, with recommendations for future research.
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Affiliation(s)
- Maria A Rocca
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy.
| | - Menno M Schoonheim
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Paola Valsasina
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Jeroen J G Geurts
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy
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