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      Graded fMRI Neurofeedback Training of Motor Imagery in Middle Cerebral Artery Stroke Patients: A Preregistered Proof-of-Concept Study

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          Abstract

          Ischemic stroke of the middle cerebral artery (MCA), a major brain vessel that supplies the primary motor and premotor cortex, is one of the most common causes for severe upper limb impairment. Currently available motor rehabilitation training largely lacks satisfying efficacy with over 70% of stroke survivors showing residual upper limb dysfunction. Motor imagery-based functional magnetic resonance imaging neurofeedback (fMRI-NF) has been suggested as a potential therapeutic technique to improve motor impairment in stroke survivors. In this preregistered proof-of-concept study ( https://osf.io/y69jc/), we translated graded fMRI-NF training, a new paradigm that we have previously studied in healthy participants, to first-time MCA stroke survivors with residual mild to severe impairment of upper limb motor function. Neurofeedback was provided from the supplementary motor area (SMA) targeting two different neurofeedback target levels (low and high). We hypothesized that MCA stroke survivors will show (1) sustained SMA-region of interest (ROI) activation and (2) a difference in SMA-ROI activation between low and high neurofeedback conditions during graded fMRI-NF training. At the group level, we found only anecdotal evidence for these preregistered hypotheses. At the individual level, we found anecdotal to moderate evidence for the absence of the hypothesized graded effect for most subjects. These null findings are relevant for future attempts to employ fMRI-NF training in stroke survivors. The study introduces a Bayesian sequential sampling plan, which incorporates prior knowledge, yielding higher sensitivity. The sampling plan was preregistered together with a priori hypotheses and all planned analysis before data collection to address potential publication/researcher biases. Unforeseen difficulties in the translation of our paradigm to a clinical setting required some deviations from the preregistered protocol. We explicitly detail these changes, discuss the accompanied additional challenges that can arise in clinical neurofeedback studies, and formulate recommendations for how these can be addressed. Taken together, this work provides new insights about the feasibility of motor imagery-based graded fMRI-NF training in MCA stroke survivors and serves as a first example for comprehensive study preregistration of an (fMRI) neurofeedback experiment.

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          Most cited references76

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          Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion.

          Here, we demonstrate that subject motion produces substantial changes in the timecourses of resting state functional connectivity MRI (rs-fcMRI) data despite compensatory spatial registration and regression of motion estimates from the data. These changes cause systematic but spurious correlation structures throughout the brain. Specifically, many long-distance correlations are decreased by subject motion, whereas many short-distance correlations are increased. These changes in rs-fcMRI correlations do not arise from, nor are they adequately countered by, some common functional connectivity processing steps. Two indices of data quality are proposed, and a simple method to reduce motion-related effects in rs-fcMRI analyses is demonstrated that should be flexibly implementable across a variety of software platforms. We demonstrate how application of this technique impacts our own data, modifying previous conclusions about brain development. These results suggest the need for greater care in dealing with subject motion, and the need to critically revisit previous rs-fcMRI work that may not have adequately controlled for effects of transient subject movements. Copyright © 2011 Elsevier Inc. All rights reserved.
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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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              Recovery of motor function after stroke.

              The natural history of recovery of motor function after stroke is described using data from a 1-year community-based study in Auckland, New Zealand. Of 680 patients, 88% presented with a hemiparesis; the proportion of survivors with a persisting deficit declined to 71% at 1 month and 62% at 6 months after the onset of the stroke. At onset, there were equal proportions of people with mild, moderate, and severe motor deficits, but the majority (76%) of those who survived 6 months had either no or only a mild deficit. Recovery of motor function was associated with the stroke severity but not with age or sex; patients with a mild motor deficit at onset were 10 times more likely to recover their motor function than those with a severe stroke. Our results confirm the reasonably optimistic outcome for survivors of stroke and further suggest that recovery of motor function is confined to patients whose motor deficit at onset is either mild or moderate.
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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
                14 July 2020
                2020
                : 14
                : 226
                Affiliations
                [1] 1School of Psychology, Cardiff University Brain Research Imaging Centre (CUBRIC) , Cardiff, United Kingdom
                [2] 2Department of Psychiatry, University of Münster , Münster, Germany
                [3] 3Max Planck Adaptive Memory Research Group, Max Planck Institute for Human Cognitive and Brain Sciences , Leipzig, Germany
                [4] 4School of Physics and Astronomy, Cardiff University , Cardiff, United Kingdom
                [5] 5Department of Cognitive Neuroscience, Maastricht University , Maastricht, Netherlands
                [6] 6Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center , Nijmegen, Netherlands
                [7] 7Research Department, Brain Innovation B.V. , Maastricht, Netherlands
                [8] 8Department of Psychiatry and Psychotherapy, Charité Universitätsmedizin Berlin , Berlin, Germany
                [9] 9Department of Neuroscience, Imaging and Clinical Sciences, Institute for Advanced Biomedical Technologies, D'Annunzio University of Chieti–Pescara , Chieti, Italy
                [10] 10Neurology Department, University Hospital of Wales , Cardiff, United Kingdom
                [11] 11School of Health, Sport and Bioscience, University of East London , London, United Kingdom
                [12] 12Faculty of Health, Medicine and Life Sciences, School for Mental Health and Neuroscience, Maastricht University , Maastricht, Netherlands
                Author notes

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

                Reviewed by: Christian Paret, Heidelberg University, Germany; Dustin Scheinost, Yale University, United States

                *Correspondence: David M. A. Mehler mehlerdma@ 123456gmail.com

                This article was submitted to Brain-Computer Interfaces, a section of the journal Frontiers in Human Neuroscience

                Article
                10.3389/fnhum.2020.00226
                7373077
                32760259
                00bc4ec3-4fe3-4b11-8807-cbd38c800675
                Copyright © 2020 Mehler, Williams, Whittaker, Krause, Lührs, Kunas, Wise, Shetty, Turner and Linden.

                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
                : 02 February 2020
                : 20 May 2020
                Page count
                Figures: 6, Tables: 6, Equations: 3, References: 92, Pages: 17, Words: 12014
                Categories
                Human Neuroscience
                Original Research

                Neurosciences
                fmri,neurofeedback,stroke,preregistration,rehabilitation
                Neurosciences
                fmri, neurofeedback, stroke, preregistration, rehabilitation

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