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      A Multi-Target Motor Imagery Training Using Bimodal EEG-fMRI Neurofeedback: A Pilot Study in Chronic Stroke Patients

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          Abstract

          Traditional rehabilitation techniques present limitations and the majority of patients show poor 1-year post-stroke recovery. Thus, Neurofeedback (NF) or Brain-Computer-Interface applications for stroke rehabilitation purposes are gaining increased attention. Indeed, NF has the potential to enhance volitional control of targeted cortical areas and thus impact on motor function recovery. However, current implementations are limited by temporal, spatial or practical constraints of the specific imaging modality used. In this pilot work and for the first time in literature, we applied bimodal EEG-fMRI NF for upper limb stroke recovery on four stroke-patients with different stroke characteristics and motor impairment severity. We also propose a novel, multi-target training approach that guides the training towards the activation of the ipsilesional primary motor cortex. In addition to fMRI and EEG outcomes, we assess the integrity of the corticospinal tract (CST) with tractography. Preliminary results suggest the feasibility of our approach and show its potential to induce an augmented activation of ipsilesional motor areas, depending on the severity of the stroke deficit. Only the two patients with a preserved CST and subcortical lesions succeeded in upregulating the ipsilesional primary motor cortex and exhibited a functional improvement of upper limb motricity. These findings highlight the importance of taking into account the variability of the stroke patients’ population and enabled to identify inclusion criteria for the design of future clinical studies.

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          Most cited references37

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          Closed-loop brain training: the science of neurofeedback

          Neurofeedback is a psychophysiological procedure in which online feedback of neural activation is provided to the participant for the purpose of self-regulation. Learning control over specific neural substrates has been shown to change specific behaviours. As a progenitor of brain–machine interfaces, neurofeedback has provided a
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            Modulation of brain plasticity in stroke: a novel model for neurorehabilitation.

            Noninvasive brain stimulation (NIBS) techniques can be used to monitor and modulate the excitability of intracortical neuronal circuits. Long periods of cortical stimulation can produce lasting effects on brain function, paving the way for therapeutic applications of NIBS in chronic neurological disease. The potential of NIBS in stroke rehabilitation has been of particular interest, because stroke is the main cause of permanent disability in industrial nations, and treatment outcomes often fail to meet the expectations of patients. Despite promising reports from many clinical trials on NIBS for stroke recovery, the number of studies reporting a null effect remains a concern. One possible explanation is that the interhemispheric competition model--which posits that suppressing the excitability of the hemisphere not affected by stroke will enhance recovery by reducing interhemispheric inhibition of the stroke hemisphere, and forms the rationale for many studies--is oversimplified or even incorrect. Here, we critically review the proposed mechanisms of synaptic and functional reorganization after stroke, and suggest a bimodal balance-recovery model that links interhemispheric balancing and functional recovery to the structural reserve spared by the lesion. The proposed model could enable NIBS to be tailored to the needs of individual patients.
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              The neural network of motor imagery: an ALE meta-analysis.

              Motor imagery (MI) or the mental simulation of action is now increasingly being studied using neuroimaging techniques such as positron emission tomography and functional magnetic resonance imaging. The booming interest in capturing the neural underpinning of MI has provided a large amount of data which until now have never been quantitatively summarized. The aim of this activation likelihood estimation (ALE) meta-analysis was to provide a map of the brain structures involved in MI. Combining the data from 75 papers revealed that MI consistently recruits a large fronto-parietal network in addition to subcortical and cerebellar regions. Although the primary motor cortex was not shown to be consistently activated, the MI network includes several regions which are known to play a role during actual motor execution. The body part involved in the movements, the modality of MI and the nature of the MI tasks used all seem to influence the consistency of activation within the general MI network. In addition to providing the first quantitative cortical map of MI, we highlight methodological issues that should be addressed in future research. Copyright © 2013 Elsevier Ltd. All rights reserved.
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                Author and article information

                Contributors
                Journal
                Front Hum Neurosci
                Front Hum Neurosci
                Front. Hum. Neurosci.
                Frontiers in Human Neuroscience
                Frontiers Media S.A.
                1662-5161
                18 February 2020
                2020
                : 14
                : 37
                Affiliations
                [1] 1Univ Rennes, Inria, CNRS, Inserm, IRISA , Rennes, France
                [2] 2Departement of Physical and Rehabilitation Medicine, Centre Hospitalier Universitaire (CHU) Rennes , Rennes, France
                [3] 3Departement of Radiology, CHU Rennes , Rennes, France
                Author notes

                Edited by: Michal Ramot, National Institute of Mental Health (NIMH), United States

                Reviewed by: Anna Seydell-Greenwald, Georgetown University Medical Center, United States; David M. A. Mehler, University of Münster, Germany

                *Correspondence: Giulia Lioi lioi.giulia@ 123456gmail.com

                Specialty section: This article was submitted to Brain Imaging and Stimulation, a section of the journal Frontiers in Human Neuroscience

                Article
                10.3389/fnhum.2020.00037
                7040168
                32132910
                b8cae176-1a9e-4e32-9619-c4fa0fdbcae9
                Copyright © 2020 Lioi, Butet, Fleury, Bannier, Lécuyer, Bonan and Barillot.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 11 September 2019
                : 27 January 2020
                Page count
                Figures: 7, Tables: 2, Equations: 2, References: 44, Pages: 13, Words: 8334
                Funding
                Funded by: Agence Nationale de la Recherche 10.13039/501100001665
                Funded by: Fondation pour la Recherche Médicale 10.13039/501100002915
                Categories
                Human Neuroscience
                Clinical Trial

                Neurosciences
                neurofeedback,fmri,eeg,stroke,rehabilitation,multimodal neuroimaging
                Neurosciences
                neurofeedback, fmri, eeg, stroke, rehabilitation, multimodal neuroimaging

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