title: Combined structural and functional patterns discriminating upper limb motor disability in multiple sclerosis using multivariate approaches.
abstract: A structural or functional pattern of neuroplasticity that could systematically discriminate between people with impaired and preserved motor performance could help us to understand the brain networks contributing to preservation or compensation of behavior in multiple sclerosis (MS). This study aimed to (1) investigate whether a machine learning-based technique could accurately classify MS participants into groups defined by upper extremity function (i.e. motor function preserved (MP) vs. motor function impaired (MI)) based on their regional grey matter measures (GMM, cortical thickness and deep grey matter volume) and inter-regional functional connection (FC), (2) investigate which features (GMM, FC, or GMM + FC) could classify groups more accurately, and (3) identify the multivariate patterns of GMM and FCs that are most discriminative between MP and MI participants, and between each of these groups and the healthy controls (HCs). With 26 MP, 25 MI, and 21 HCs (age and sex matched) underwent T1-weighted and resting-state functional MRI at 3 T, we applied support vector machine (SVM) based classification to learn discriminant functions indicating regions in which GMM or between which FCs were most discriminative between groups. This study demonstrates that there exist structural and FC patterns sufficient for correct classification of upper limb motor ability of people with MS. The classifier with GMM + FC features yielded the highest accuracy of 85.61 % (p < 0.001) to distinguish between the MS groups using leave-one-out cross-validation. It suggests that a machine-learning approach combining structural and functional features is useful for identifying the specific neural substrates that are necessary and sufficient to preserve motor function among people with MS.
authors.affiliation: Research Institute of the McGill University Health Centre, Montreal, QC, Canada. jidanz@gmail.com.|Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada. jidanz@gmail.com.|Toronto Western Hospital, 399 Bathurst Street, Toronto, ON, M5T 2S8, Canada. jidanz@gmail.com.
authors.forename: Jidan
authors.initials: J
authors.lastname: Zhong
authors.affiliation: Institute of Medical Science, University of Toronto, Toronto, ON, Canada.|Division of Brain, Imaging and Behaviour-Systems, Neuroscience, Krembil Research Institute, University Health Network, Toronto, ON, Canada.
authors.forename: David Qixiang
authors.initials: DQ
authors.lastname: Chen
authors.affiliation: Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada.|Integrated Program in Neuroscience, McGill University, Montreal, QC, Canada.
authors.forename: Julia C
authors.initials: JC
authors.lastname: Nantes
authors.affiliation: Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada.|Integrated Program in Neuroscience, McGill University, Montreal, QC, Canada.
authors.forename: Scott A
authors.initials: SA
authors.lastname: Holmes
authors.affiliation: Institute of Medical Science, University of Toronto, Toronto, ON, Canada.|Division of Brain, Imaging and Behaviour-Systems, Neuroscience, Krembil Research Institute, University Health Network, Toronto, ON, Canada.|Division of Neurosurgery, Toronto Western Hospital & University of Toronto, Toronto, ON, Canada.
authors.forename: Mojgan
authors.initials: M
authors.lastname: Hodaie
authors.affiliation: Research Institute of the McGill University Health Centre, Montreal, QC, Canada.|Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada.|Department of Psychology, McGill University, Montreal, QC, Canada.
authors.forename: Lisa
authors.initials: L
authors.lastname: Koski
mesh_terms: D019540:Area Under Curve; D003937:Diagnosis, Differential; D005260:Female; D007839:Functional Laterality; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods; D008297:Male; D008875:Middle Aged; D009043:Motor Activity; D009069:Movement Disorders / Q000000981:diagnostic imaging* / Q000188:drug therapy / Q000209:etiology / Q000503:physiopathology; D009103:Multiple Sclerosis / Q000145:classification / Q000000981:diagnostic imaging* / Q000188:drug therapy / Q000503:physiopathology; D015999:Multivariate Analysis; D009929:Organ Size; D012372:ROC Curve; D060388:Support Vector Machine; D034941:Upper Extremity / Q000503:physiopathology
keywords: Cortical thickness; Deep grey matter volume; Functional connectivity; Motor disability; Multiple sclerosis; Multivariate analysis; Support vector machine