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      Gait improvement via rhythmic stimulation in Parkinson’s disease is linked to rhythmic skills

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          Abstract

          Training based on rhythmic auditory stimulation (RAS) can improve gait in patients with idiopathic Parkinson’s disease (IPD). Patients typically walk faster and exhibit greater stride length after RAS. However, this effect is highly variable among patients, with some exhibiting little or no response to the intervention. These individual differences may depend on patients’ ability to synchronize their movements to a beat. To test this possibility, 14 IPD patients were submitted to RAS for four weeks, in which they walked to music with an embedded metronome. Before and after the training, patients’ synchronization was assessed with auditory paced hand tapping and walking to auditory cues. Patients increased gait speed and stride length in non-cued gait after training. However, individual differences were apparent as some patients showed a positive response to RAS and others, either no response, or a negative response. A positive response to RAS was predicted by the synchronization performance in hand tapping and gait tasks. More severe gait impairment, low synchronization variability, and a prompt response to a stimulation change foster a positive response to RAS training. Thus, sensorimotor timing skills underpinning the synchronization of steps to an auditory cue may allow predicting the success of RAS in IPD.

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          Most cited references59

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          Neuroanatomical and neurochemical substrates of timing.

          We all have a sense of time. Yet, there are no sensory receptors specifically dedicated for perceiving time. It is an almost uniquely intangible sensation: we cannot see time in the way that we see color, shape, or even location. So how is time represented in the brain? We explore the neural substrates of metrical representations of time such as duration estimation (explicit timing) or temporal expectation (implicit timing). Basal ganglia (BG), supplementary motor area, cerebellum, and prefrontal cortex have all been linked to the explicit estimation of duration. However, each region may have a functionally discrete role and will be differentially implicated depending upon task context. Among these, the dorsal striatum of the BG and, more specifically, its ascending nigrostriatal dopaminergic pathway seems to be the most crucial of these regions, as shown by converging functional neuroimaging, neuropsychological, and psychopharmacological investigations in humans, as well as lesion and pharmacological studies in animals. Moreover, neuronal firing rates in both striatal and interconnected frontal areas vary as a function of duration, suggesting a neurophysiological mechanism for the representation of time in the brain, with the excitatory-inhibitory balance of interactions among distinct subtypes of striatal neuron serving to fine-tune temporal accuracy and precision.
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            Automatic detection of gait events using kinematic data.

            The timing of heel strike (HS) and toe off (TO), the events that mark the transitions between stance and swing phase of gait, is essential when analysing gait. Force plate recordings are routinely used to identify these events. Additional instrumentation, such as force sensitive resistors, can also been used. These approaches, however, include restrictions on the number of steps that can be analyzed and further encumbrance of the subject. We developed an algorithm which automatically determines these times from kinematic data recorded by a motion capture system, which is routinely used in gait analysis laboratories. The foot velocity algorithm (FVA) uses data from the heel and toe markers and identifies features in the vertical velocity of the foot which correspond to the gait events. We verified the performance of the FVA using a large data set of 54 normal children that contained both force plate recordings and kinematic data and found errors of (mean+/-standard deviation) 16+/-15 ms for HS and 9+/-15 ms for TO. The algorithm also worked well when tested on a small number of children with spastic diplegia. We compared the performance of the FVA with another kinematic method previously described. Our foot velocity algorithm offered more accurate results and was easier to implement than the previously described one, and should be applicable in a variety of gait analysis settings.
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              Time, our lost dimension: Toward a new theory of perception, attention, and memory.

              Mari Jones (1976)
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                Author and article information

                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group
                2045-2322
                24 February 2017
                2017
                : 7
                : 42005
                Affiliations
                [1 ]EuroMov, University of Montpellier , Montpellier, 34090, France
                [2 ]WSFiZ in Warsaw, Department of Cognitive Psychology , Warsaw, 01-030, Poland
                [3 ]Institut Universitaire de France (IUF) , Paris, 75005, France
                [4 ]Max Planck Institute for Human Cognitive and Brain Sciences, Department of Neuropsychology , Leipzig, 04103, Germany
                [5 ]Télécom Bretagne, Lab-STICC , Brest, France
                [6 ]MARCS Institute, Western Sydney University , Sidney, Australia
                [7 ]Clinic for Cognitive Neurology, University Hospital and University Leipzig , Leipzig, 04103, Germany
                [8 ]Neurologisches Fachkrankenhaus für Bewegungsstörungen / Parkinson , Beelitz-Heilstätten, 14547, Germany
                [9 ]Faculty of Psychology and Neuroscience, Maastricht University, Dept. of Neuropsychology and Psychopharmacology , Maastricht, The Netherlands
                Author notes
                [*]

                These authors contributed equally to this work.

                Article
                srep42005
                10.1038/srep42005
                5324039
                28233776
                8cab3302-eb7d-442d-9756-6047f9e0ff80
                Copyright © 2017, The Author(s)

                This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

                History
                : 14 October 2015
                : 05 January 2017
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