Alessandro d'Ambrosio1, Paola Valsasina1, Antonio Gallo2, Nicola De Stefano3, Deborah Pareto4, Frederik Barkhof5, Olga Ciccarelli6, Christian Enzinger7, Gioacchino Tedeschi2, M Laura Stromillo3, Maria J Arévalo8, Hanneke E Hulst9, Nils Muhlert6, Marisa Koini7, Massimo Filippi10, Maria A Rocca10. 1. Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy. 2. I Division of Neurology, Department of Medical, Surgical, Neurological, Metabolic and Aging Sciences, University of Campania "L. Vanvitelli," Naples, Italy. 3. Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy. 4. Magnetic Resonance Unit, Department of Radiology, Hospital Universitari Vall d'Hebron, Barcelona, Spain. 5. Department of Radiology & Nuclear Medicine, VU University Medical Center, Amsterdam, The Netherlands/Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, University College London (UCL), London, UK. 6. Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, University College London (UCL), London, UK. 7. Department of Neurology, Medical University of Graz, Graz, Austria. 8. Department of Neurology/Neuroimmunology, Multiple Sclerosis Centre of Catalonia (Cemcat), Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain. 9. Department of Anatomy & Neurosciences, VU University Medical Center, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands. 10. Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy/Department of Neurology, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy.
Abstract
BACKGROUND: In multiple sclerosis (MS), abnormalities of brain network dynamics and their relevance for cognitive impairment have never been investigated. OBJECTIVES: The aim of this study was to assess the dynamic resting state (RS) functional connectivity (FC) on 62 relapsing-remitting MS patients and 65 sex-matched healthy controls enrolled at 7 European sites. METHODS: MS patients underwent clinical and cognitive evaluation. Between-group network FC differences were evaluated using a dynamic approach (based on sliding-window correlation analysis) and grouping correlation matrices into recurrent FC states. RESULTS: Dynamic FC analysis revealed, in healthy controls and MS patients, three recurrent FC states: two characterized by strong intra- and inter-network connectivity and one characterized by weak inter-network connectivity (State 3). A total of 23 MS patients were cognitively impaired (CI). Compared to cognitively preserved (CP), CI-MS patients had reduced RS-FC between subcortical and default-mode networks in the low-connectivity State 3 and lower dwell time (i.e. time spent in a given state) in the high-connectivity State 2. CI-MS patients also exhibited a lower number and a less frequent switching between meta-states, as well as a smaller distance traveled through connectivity states. CONCLUSION: Time-varying RS-FC was markedly less dynamic in CI- versus CP-MS patients, suggesting that slow inter-network connectivity contributes to cognitive dysfunction in MS.
BACKGROUND: In multiple sclerosis (MS), abnormalities of brain network dynamics and their relevance for cognitive impairment have never been investigated. OBJECTIVES: The aim of this study was to assess the dynamic resting state (RS) functional connectivity (FC) on 62 relapsing-remitting MS patients and 65 sex-matched healthy controls enrolled at 7 European sites. METHODS: MS patients underwent clinical and cognitive evaluation. Between-group network FC differences were evaluated using a dynamic approach (based on sliding-window correlation analysis) and grouping correlation matrices into recurrent FC states. RESULTS: Dynamic FC analysis revealed, in healthy controls and MS patients, three recurrent FC states: two characterized by strong intra- and inter-network connectivity and one characterized by weak inter-network connectivity (State 3). A total of 23 MS patients were cognitively impaired (CI). Compared to cognitively preserved (CP), CI-MSpatients had reduced RS-FC between subcortical and default-mode networks in the low-connectivity State 3 and lower dwell time (i.e. time spent in a given state) in the high-connectivity State 2. CI-MSpatients also exhibited a lower number and a less frequent switching between meta-states, as well as a smaller distance traveled through connectivity states. CONCLUSION: Time-varying RS-FC was markedly less dynamic in CI- versus CP-MS patients, suggesting that slow inter-network connectivity contributes to cognitive dysfunction in MS.
Entities:
Keywords:
Cognitive impairment; brain dynamics; functional connectivity; functional magnetic resonance imaging; multiple sclerosis; resting state
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