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      The role of virtual reality in improving motor performance as revealed by EEG: a randomized clinical trial

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          Abstract

          Background

          Many studies have demonstrated the usefulness of repetitive task practice by using robotic-assisted gait training (RAGT) devices, including Lokomat, for the treatment of lower limb paresis. Virtual reality (VR) has proved to be a valuable tool to improve neurorehabilitation training. The aim of our pilot randomized clinical trial was to understand the neurophysiological basis of motor function recovery induced by the association between RAGT (by using Lokomat device) and VR (an animated avatar in a 2D VR) by studying electroencephalographic (EEG) oscillations.

          Methods

          Twenty-four patients suffering from a first unilateral ischemic stroke in the chronic phase were randomized into two groups. One group performed 40 sessions of Lokomat with VR (RAGT + VR), whereas the other group underwent Lokomat without VR (RAGT-VR). The outcomes (clinical, kinematic, and EEG) were measured before and after the robotic intervention.

          Results

          As compared to the RAGT-VR group, all the patients of the RAGT + VR group improved in the Rivermead Mobility Index and Tinetti Performance Oriented Mobility Assessment. Moreover, they showed stronger event-related spectral perturbations in the high-γ and β bands and larger fronto-central cortical activations in the affected hemisphere.

          Conclusions

          The robotic-based rehabilitation combined with VR in patients with chronic hemiparesis induced an improvement in gait and balance. EEG data suggest that the use of VR may entrain several brain areas (probably encompassing the mirror neuron system) involved in motor planning and learning, thus leading to an enhanced motor performance.

          Trial registration

          Retrospectively registered in Clinical Trials on 21-11-2016, n. NCT02971371.

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          Most cited references115

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          Low resolution electromagnetic tomography: a new method for localizing electrical activity in the brain.

          This paper presents a new method for localizing the electric activity in the brain based on multichannel surface EEG recordings. In contrast to the models presented up to now the new method does not assume a limited number of dipolar point sources nor a distribution on a given known surface, but directly computes a current distribution throughout the full brain volume. In order to find a unique solution for the 3-dimensional distribution among the infinite set of different possible solutions, the method assumes that neighboring neurons are simultaneously and synchronously activated. The basic assumption rests on evidence from single cell recordings in the brain that demonstrates strong synchronization of adjacent neurons. In view of this physiological consideration the computational task is to select the smoothest of all possible 3-dimensional current distributions, a task that is a common procedure in generalized signal processing. The result is a true 3-dimensional tomography with the characteristic that localization is preserved with a certain amount of dispersion, i.e., it has a relatively low spatial resolution. The new method, which we call Low Resolution Electromagnetic Tomography (LORETA) is illustrated with two different sets of evoked potential data, the first showing the tomography of the P100 component to checkerboard stimulation of the left, right, upper and lower hemiretina, and the second showing the results for the auditory N100 component and the two cognitive components CNV and P300. A direct comparison of the tomography results with those obtained from fitting one and two dipoles illustrates that the new method provides physiologically meaningful results while dipolar solutions fail in many situations. In the case of the cognitive components, the method offers new hypotheses on the location of higher cognitive functions in the brain.
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            A new neural framework for visuospatial processing.

            The division of cortical visual processing into distinct dorsal and ventral streams is a key framework that has guided visual neuroscience. The characterization of the ventral stream as a 'What' pathway is relatively uncontroversial, but the nature of dorsal stream processing is less clear. Originally proposed as mediating spatial perception ('Where'), more recent accounts suggest it primarily serves non-conscious visually guided action ('How'). Here, we identify three pathways emerging from the dorsal stream that consist of projections to the prefrontal and premotor cortices, and a major projection to the medial temporal lobe that courses both directly and indirectly through the posterior cingulate and retrosplenial cortices. These three pathways support both conscious and non-conscious visuospatial processing, including spatial working memory, visually guided action and navigation, respectively.
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              Mining event-related brain dynamics.

              This article provides a new, more comprehensive view of event-related brain dynamics founded on an information-based approach to modeling electroencephalographic (EEG) dynamics. Most EEG research focuses either on peaks 'evoked' in average event-related potentials (ERPs) or on changes 'induced' in the EEG power spectrum by experimental events. Although these measures are nearly complementary, they do not fully model the event-related dynamics in the data, and cannot isolate the signals of the contributing cortical areas. We propose that many ERPs and other EEG features are better viewed as time/frequency perturbations of underlying field potential processes. The new approach combines independent component analysis (ICA), time/frequency analysis, and trial-by-trial visualization that measures EEG source dynamics without requiring an explicit head model.
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                Author and article information

                Contributors
                +3909060128954 , salbro77@tiscali.it
                g.naro11@alice.it
                margheritarusso@virgilio.it
                anton.leo@libero.it
                dlucaros@yahoo.it
                baltina80@tiscali.it
                anton.buda@gmail.com
                gialucalarosa05@gmail.com
                alessia.bramanti@gmail.com
                bramanti.dino@gmail.com
                Journal
                J Neuroeng Rehabil
                J Neuroeng Rehabil
                Journal of NeuroEngineering and Rehabilitation
                BioMed Central (London )
                1743-0003
                7 June 2017
                7 June 2017
                2017
                : 14
                : 53
                Affiliations
                GRID grid.419419.0, , IRCCS Centro Neurolesi “Bonino-Pulejo”, ; Messina, Italy
                Article
                268
                10.1186/s12984-017-0268-4
                5463350
                28592282
                491eba6d-23fc-4582-be58-f1eaf6ae65d0
                © The Author(s). 2017

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 23 November 2016
                : 1 June 2017
                Categories
                Research
                Custom metadata
                © The Author(s) 2017

                Neurosciences
                lokomat,ersp,loreta,mirror neuron system,virtual reality
                Neurosciences
                lokomat, ersp, loreta, mirror neuron system, virtual reality

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