| Summary: | Introduction: Stroke remains a leading cause of long-term disability. Functional imaging studies report widespread changes in movement-related cortical networks after stroke. Whether these are a result of stroke-specific cognitive processes or reflect modulation of existing movement related networks is unknown. Understanding this distinction is critical in establishing more effective restorative therapies after stroke. Here we use multivariate analysis (tensor-independent component analysis - TICA) to map the array of neural networks involved during motor imagery (MI) and executed movement (EM) in subcortical stroke patients and age-matched controls. Methods: Twenty subcortical stroke patients and seventeen age-matched controls were recruited and screened for their ability to carry out MI (Chaotic MI Assessment). fMRI consisted of an auditory-paced (1Hz) right hand finger-thumb opposition sequence (2,3,4,5; 2…) with two separate runs acquired (MI & rest and EM & rest; block design). No distinction was made between groups or tasks until the final stage of processing. This allowed TICA to identify independent-components (IC) that were common or distinct to each group or task with no prior assumptions. Results: TICA defined 28 ICs. Non-significant ICs and those representing artifact were excluded. Only components in which the subject scores were significantly different to zero (for either EM or MI) were included. Seven independent components remained that involved the primary and secondary motor networks. All ICs were shared between the stroke and age-matched controls. Five ICs were common to both tasks and three were exclusive to EM. Two ICs were related to motor recovery and one with time since stroke onset, but all were shared with age-matched controls. No IC was exclusive to stroke patients. Conclusion: We report that the cortical networks in stroke patients that relate to recovery of motor function represent modulation of existing cortical networks present in age-matched controls. The absence of cortical networks specific to stroke patients suggests that motor adaptation and other potential confounds (e.g. effort, additional muscle use) are not responsible for the changes in the cortical networks reported after stroke. This highlights that recovery of motor function after subcortical stroke involves preexisting cortical networks which could help identify more effective restorative therapies.
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