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      Activity or connectivity? A randomized controlled feasibility study evaluating neurofeedback training in Huntington’s disease

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          Abstract

          Non-invasive methods, such as neurofeedback training, could support cognitive symptom management in Huntington’s disease by targeting brain regions whose function is impaired. The aim of our single-blind, sham-controlled study was to collect rigorous evidence regarding the feasibility of neurofeedback training in Huntington’s disease by examining two different methods, activity and connectivity real-time functional MRI neurofeedback training. Thirty-two Huntington’s disease gene-carriers completed 16 runs of neurofeedback training, using an optimized real-time functional MRI protocol. Participants were randomized into four groups, two treatment groups, one receiving neurofeedback derived from the activity of the supplementary motor area, and another receiving neurofeedback based on the correlation of supplementary motor area and left striatum activity (connectivity neurofeedback training), and two sham control groups, matched to each of the treatment groups. We examined differences between the groups during neurofeedback training sessions and after training at follow-up sessions. Transfer of training was measured by measuring the participants’ ability to upregulate neurofeedback training target levels without feedback (near transfer), as well as by examining change in objective, a priori defined, behavioural measures of cognitive and psychomotor function (far transfer) before and at 2 months after training. We found that the treatment group had significantly higher neurofeedback training target levels during the training sessions compared to the control group. However, we did not find robust evidence of better transfer in the treatment group compared to controls, or a difference between the two neurofeedback training methods. We also did not find evidence in support of a relationship between change in cognitive and psychomotor function and learning success. We conclude that although there is evidence that neurofeedback training can be used to guide participants to regulate the activity and connectivity of specific regions in the brain, evidence regarding transfer of learning and clinical benefit was not robust.

          Abstract

          We evaluated feasibility of real-time functional magnetic resonance imaging neurofeedback training in Huntington’s disease. The treatment group learned to regulate the neurofeedback target, activity or connectivity, compared to sham neurofeedback. However, evidence of transfer was weak. The treatment group did not self-regulate the target without neurofeedback better than controls; there was no improvement in behaviour.

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          Most cited references37

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          SENSE: Sensitivity encoding for fast MRI

          New theoretical and practical concepts are presented for considerably enhancing the performance of magnetic resonance imaging (MRI) by means of arrays of multiple receiver coils. Sensitivity encoding (SENSE) is based on the fact that receiver sensitivity generally has an encoding effect complementary to Fourier preparation by linear field gradients. Thus, by using multiple receiver coils in parallel scan time in Fourier imaging can be considerably reduced. The problem of image reconstruction from sensitivity encoded data is formulated in a general fashion and solved for arbitrary coil configurations and k-space sampling patterns. Special attention is given to the currently most practical case, namely, sampling a common Cartesian grid with reduced density. For this case the feasibility of the proposed methods was verified both in vitro and in vivo. Scan time was reduced to one-half using a two-coil array in brain imaging. With an array of five coils double-oblique heart images were obtained in one-third of conventional scan time. Magn Reson Med 42:952-962, 1999. Copyright 1999 Wiley-Liss, Inc.
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            Benchmarking of participant-level confound regression strategies for the control of motion artifact in studies of functional connectivity.

            Since initial reports regarding the impact of motion artifact on measures of functional connectivity, there has been a proliferation of participant-level confound regression methods to limit its impact. However, many of the most commonly used techniques have not been systematically evaluated using a broad range of outcome measures. Here, we provide a systematic evaluation of 14 participant-level confound regression methods in 393 youths. Specifically, we compare methods according to four benchmarks, including the residual relationship between motion and connectivity, distance-dependent effects of motion on connectivity, network identifiability, and additional degrees of freedom lost in confound regression. Our results delineate two clear trade-offs among methods. First, methods that include global signal regression minimize the relationship between connectivity and motion, but result in distance-dependent artifact. In contrast, censoring methods mitigate both motion artifact and distance-dependence, but use additional degrees of freedom. Importantly, less effective de-noising methods are also unable to identify modular network structure in the connectome. Taken together, these results emphasize the heterogeneous efficacy of existing methods, and suggest that different confound regression strategies may be appropriate in the context of specific scientific goals.
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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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                Author and article information

                Journal
                Brain Commun
                Brain Commun
                braincomms
                Brain Communications
                Oxford University Press
                2632-1297
                2020
                23 April 2020
                23 April 2020
                : 2
                : 1
                : fcaa049
                Affiliations
                [f1 ] UCL Huntington’s Disease Centre, Queen Square Institute of Neurology, University College London , London WC1B 5EH, UK
                [f2 ] Birkbeck-UCL Centre for Neuroimaging, University College London , London WC1H 0AP, UK
                [f3 ] Wellcome Centre for Human Neuroimaging, Queen Square Institute of Neurology, University College London , London WC1N 3AR, UK
                [f4 ] University of Oxford, Harris Manchester College , Oxford OX1 3TD, UK
                [f5 ] George Huntington Institute , 48149 Münster, Germany
                [f6 ] Department of Radiology, University of Muenster , 48149 Münster, Germany
                [f7 ] Section for Neurodegeneration and Hertie Institute for Clinical Brain Research, University of Tuebingen , 72076 Tübingen, Germany
                [f8 ] Eastman Dental Institute, University College London , London WC1X 8LD, UK
                [f9 ] Max Planck Institute for Human Cognitive and Brain Sciences , D-04103 Leipzig, Germany
                [f10 ] Carver College of Medicine, University of Iowa , Iowa City, IA 52242, USA
                [f11 ] Institute of Cognitive Neuroscience, University College London , London WC1N 3AZ, UK
                [f12 ] UK Dementia Research Institute at University College London , London WC1E 6BT, UK
                Author notes

                Geraint Rees and Sarah J. Tabrizi Equal senior authors.

                Correspondence to: Marina Papoutsi, PhD UCL Huntington’s Disease Centre, Queen Square Institute of Neurology University College London, Russell Square House, 10–12 Russell Square London WC1B 5EH, UK E-mail: m.papoutsi@ 123456ucl.ac.uk
                Author information
                http://orcid.org/0000-0003-0971-8361
                Article
                fcaa049
                10.1093/braincomms/fcaa049
                7425518
                32954301
                0875d9ab-089a-40cd-9378-6c1ad60bfae8
                © The Author(s) (2020). Published by Oxford University Press on behalf of the Guarantors of Brain.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 23 September 2019
                : 11 February 2020
                : 27 March 2020
                Page count
                Pages: 14
                Funding
                Funded by: Medical Research Council Developmental Pathway Funding Scheme;
                Award ID: MR-L012936-1
                Funded by: Wellcome Trust Senior Research Fellowship;
                Funded by: Dementia Research Institute Ltd;
                Funded by: UK Medical Research Council, Alzheimer’s Society and Alzheimer’s Research UK;
                Categories
                Original Article

                neurofeedback training,neuroplasticity,huntington’s disease,real-time fmri

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