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      Upregulation of Supplementary Motor Area Activation with fMRI Neurofeedback during Motor Imagery

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          Abstract

          Functional magnetic resonance imaging (fMRI) neurofeedback (NF) is a promising tool to study the relationship between behavior and brain activity. It enables people to self-regulate their brain signal. Here, we applied fMRI NF to train healthy participants to increase activity in their supplementary motor area (SMA) during a motor imagery (MI) task of complex body movements while they received a continuous visual feedback signal. This signal represented the activity of participants’ localized SMA regions in the NF group and a prerecorded signal in the control group (sham feedback). In the NF group only, results showed a gradual increase in SMA-related activity across runs. This upregulation was largely restricted to the SMA, while other regions of the motor network showed no, or only marginal NF effects. In addition, we found behavioral changes, i.e., shorter reaction times in a Go/No-go task after the NF training only. These results suggest that NF can assist participants to develop greater control over a specifically targeted motor region involved in motor skill learning. The results contribute to a better understanding of the underlying mechanisms of SMA NF based on MI with a direct implication for rehabilitation of motor dysfunctions.

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          The assessment and analysis of handedness: The Edinburgh inventory

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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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              The influence of head motion on intrinsic functional connectivity MRI.

              Functional connectivity MRI (fcMRI) has been widely applied to explore group and individual differences. A confounding factor is head motion. Children move more than adults, older adults more than younger adults, and patients more than controls. Head motion varies considerably among individuals within the same population. Here we explored the influence of head motion on fcMRI estimates. Mean head displacement, maximum head displacement, the number of micro movements (>0.1 mm), and head rotation were estimated in 1000 healthy, young adult subjects each scanned for two resting-state runs on matched 3T scanners. The majority of fcMRI variation across subjects was not linked to head motion. However, head motion had significant, systematic effects on fcMRI network measures. Head motion was associated with decreased functional coupling in the default and frontoparietal control networks--two networks characterized by coupling among distributed regions of association cortex. Other network measures increased with motion including estimates of local functional coupling and coupling between left and right motor regions--a region pair sometimes used as a control in studies to establish specificity. Comparisons between groups of individuals with subtly different levels of head motion yielded difference maps that could be mistaken for neuronal effects in other contexts. These effects are important to consider when interpreting variation between groups and across individuals. Copyright © 2011 Elsevier Inc. All rights reserved.
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                Author and article information

                Journal
                eNeuro
                eNeuro
                eneuro
                eneuro
                eNeuro
                eNeuro
                Society for Neuroscience
                2373-2822
                29 December 2020
                22 January 2021
                Jan-Feb 2021
                : 8
                : 1
                : ENEURO.0377-18.2020
                Affiliations
                [1 ]School of Psychology, University of Glasgow , Glasgow G12 8QB, United Kingdom
                [2 ]School of Engineering, University of Glasgow , Glasgow G12 8QB, United Kingdom
                [3 ]College of Engineering, University of Wasit , Wasit 52001, Iraq
                [4 ]Department of Psychology, Lancaster University , Lancaster LA1 4YF, United Kingdom
                Author notes

                The authors declare no competing financial interests.

                Author contributions: S.A.-W. and F.E.P. designed research; S.A.-W. performed research; S.A.-W. and S.V. analyzed data; S.A.-W., S.V., A.V., and F.E.P. wrote the paper.

                S.A.-W. was supported by the Higher Committee for Education Development in Iraq.

                Correspondence should be addressed to Salim Al-Wasity at salim_alwasity@ 123456yahoo.com
                Article
                eN-MNT-0377-18
                10.1523/ENEURO.0377-18.2020
                7877466
                33376115
                68f30065-15b0-4f43-b684-c5a5759339d0
                Copyright © 2021 Al-Wasity et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license, which permits unrestricted use, distribution and reproduction in any medium provided that the original work is properly attributed.

                History
                : 27 September 2018
                : 2 December 2020
                : 7 December 2020
                Page count
                Figures: 10, Tables: 6, Equations: 1, References: 68, Pages: 14, Words: 00
                Categories
                7
                Research Article: Methods/New Tools
                Novel Tools and Methods
                Custom metadata
                January/February 2021

                neurofeedback,fmri,motor imagery,supplementary motor area

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