Matteo Pardini1, Laura Bonzano1, Maurizio Bergamino1, Giulia Bommarito1, Paola Feraco1, Abitha Murugavel1, Marco Bove2, Giampaolo Brichetto3, Antonio Uccelli4, Gianluigi Mancardi1, Luca Roccatagliata5. 1. Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, Italy/Magnetic Resonance Research Centre on Nervous System Diseases, University of Genoa, Italy. 2. Section of Human Physiology and Centro Polifunzionale di Scienze Motorie, University of Genoa, Italy. 3. Scientific Research Area, Italian Multiple Sclerosis Foundation (FISM), Genoa, Italy. 4. University of Genoa, Italy. 5. Magnetic Resonance Research Centre on Nervous System Diseases, University of Genoa/San Martino University Hospital/ University of Genoa, Genoa, Italy lroccatagliata@neurologia.unige.it.
Abstract
OBJECTIVE: To evaluate the neural basis of subjective fatigue in subjects with multiple sclerosis (MS) using a connectionist framework. METHODS: Seventy seven subjects with relapsing-remitting MS were recruited in the study and underwent subjective fatigue evaluations and a diffusion MRI scan. Firstly, local white matter Fractional Anisotropy values were correlated with subjective fatigue scores using a voxel-wise approach. The long-range loss of connectivity due to structural damage in the white matter voxels thus associated with subjective fatigue was then assessed using the Network Modification (NeMo) package. RESULTS: A voxel-wise regression analysis with fatigue scores revealed a significant association between structural damage and fatigue levels in two discrete white matter clusters, both included in the left cingulate bundle. The connectivity analysis revealed that damage in these clusters was associated with loss of structural connectivity in the anterior and medial cingulate cortices, dorsolateral prefrontal areas and in the left caudate. DISCUSSION: Our data point to the cingulum bundle and its projections as the key network involved in subjective fatigue perception in MS. More generally, these results suggest the potential of the connectionist framework to generate coherent models of the neural basis of complex symptomatology in MS.
OBJECTIVE: To evaluate the neural basis of subjective fatigue in subjects with multiple sclerosis (MS) using a connectionist framework. METHODS: Seventy seven subjects with relapsing-remitting MS were recruited in the study and underwent subjective fatigue evaluations and a diffusion MRI scan. Firstly, local white matter Fractional Anisotropy values were correlated with subjective fatigue scores using a voxel-wise approach. The long-range loss of connectivity due to structural damage in the white matter voxels thus associated with subjective fatigue was then assessed using the Network Modification (NeMo) package. RESULTS: A voxel-wise regression analysis with fatigue scores revealed a significant association between structural damage and fatigue levels in two discrete white matter clusters, both included in the left cingulate bundle. The connectivity analysis revealed that damage in these clusters was associated with loss of structural connectivity in the anterior and medial cingulate cortices, dorsolateral prefrontal areas and in the left caudate. DISCUSSION: Our data point to the cingulum bundle and its projections as the key network involved in subjective fatigue perception in MS. More generally, these results suggest the potential of the connectionist framework to generate coherent models of the neural basis of complex symptomatology in MS.
Authors: Emily Wasson; Andrea L Rosso; Adam J Santanasto; Caterina Rosano; Meryl A Butters; W Jack Rejeski; Robert M Boudreau; Howard Aizenstein; Theresa Gmelin; Nancy W Glynn Journal: Exp Gerontol Date: 2018-12-04 Impact factor: 4.032
Authors: Declan T Chard; Adnan A S Alahmadi; Bertrand Audoin; Thalis Charalambous; Christian Enzinger; Hanneke E Hulst; Maria A Rocca; Àlex Rovira; Jaume Sastre-Garriga; Menno M Schoonheim; Betty Tijms; Carmen Tur; Claudia A M Gandini Wheeler-Kingshott; Alle Meije Wink; Olga Ciccarelli; Frederik Barkhof Journal: Nat Rev Neurol Date: 2021-01-12 Impact factor: 42.937