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      A little elastic for a better performance: kinesiotaping of the motor effector modulates neural mechanisms for rhythmic movements

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          Abstract

          A rhythmic motor performance is brought about by an integration of timing information with movements. Investigations on the millisecond time scale distinguish two forms of time control, event-based timing and emergent timing. While event-based timing asserts the existence of a central internal timekeeper for the control of repetitive movements, the emergent timing perspective claims that timing emerges from dynamic control of nontemporal movements parameters. We have recently demonstrated that the precision of an isochronous performance, defined as performance of repeated movements having a uniform duration, was insensible to auditory stimuli of various characteristics (Bravi et al., 2014). Such finding has led us to investigate whether the application of an elastic therapeutic tape (Kinesio® Tex taping; KTT) used for treating athletic injuries and a variety of physical disorders, is able to reduce the timing variability of repetitive rhythmic movement. Young healthy subjects, tested with and without KTT, have participated in sessions in which sets of repeated isochronous wrist's flexion-extensions (IWFEs) were performed under various auditory conditions and during their recall. Kinematics was recorded and temporal parameters were extracted and analyzed. Our results show that the application of KTT decreases the variability of rhythmic movements by a 2-fold effect: on the one hand KTT provides extra proprioceptive information activating cutaneous mechanoreceptors, on the other KTT biases toward the emergent timing thus modulating the processes for rhythmic movements. Therefore, KTT appears able to render movements less audio dependent by relieving, at least partially, the central structures from time control and making available more resources for an augmented performance.

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          Most cited references53

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          Identifying true brain interaction from EEG data using the imaginary part of coherency.

          The main obstacle in interpreting EEG/MEG data in terms of brain connectivity is the fact that because of volume conduction, the activity of a single brain source can be observed in many channels. Here, we present an approach which is insensitive to false connectivity arising from volume conduction. We show that the (complex) coherency of non-interacting sources is necessarily real and, hence, the imaginary part of coherency provides an excellent candidate to study brain interactions. Although the usual magnitude and phase of coherency contain the same information as the real and imaginary parts, we argue that the Cartesian representation is far superior for studying brain interactions. The method is demonstrated for EEG measurements of voluntary finger movement. We found: (a) from 5 s before to movement onset a relatively weak interaction around 20 Hz between left and right motor areas where the contralateral side leads the ipsilateral side; and (b) approximately 2-4 s after movement, a stronger interaction also at 20 Hz in the opposite direction. It is possible to reliably detect brain interaction during movement from EEG data. The method allows unambiguous detection of brain interaction from rhythmic EEG/MEG data.
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            The neural representation of time.

            This review summarizes recent investigations of temporal processing. We focus on motor and perceptual tasks in which crucial events span hundreds of milliseconds. One key question concerns whether the representation of temporal information is dependent on a specialized system, distributed across a network of neural regions, or computed in a local task-dependent manner. Consistent with the specialized system framework, the cerebellum is associated with various tasks that require precise timing. Computational models of timing mechanisms within the cerebellar cortex are beginning to motivate physiological studies. Emphasis has also been placed on the basal ganglia as a specialized timing system, particularly for longer intervals. We outline an alternative hypothesis in which this structure is associated with decision processes.
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              The evolution of brain activation during temporal processing.

              Timing is crucial to many aspects of human performance. To better understand its neural underpinnings, we used event-related fMRI to examine the time course of activation associated with different components of a time perception task. We distinguished systems associated with encoding time intervals from those related to comparing intervals and implementing a response. Activation in the basal ganglia occurred early, and was uniquely associated with encoding time intervals, whereas cerebellar activation unfolded late, suggesting an involvement in processes other than explicit timing. Early cortical activation associated with encoding of time intervals was observed in the right inferior parietal cortex and bilateral premotor cortex, implicating these systems in attention and temporary maintenance of intervals. Late activation in the right dorsolateral prefrontal cortex emerged during comparison of time intervals. Our results illustrate a dynamic network of cortical-subcortical activation associated with different components of temporal information processing.
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                Author and article information

                Contributors
                Journal
                Front Syst Neurosci
                Front Syst Neurosci
                Front. Syst. Neurosci.
                Frontiers in Systems Neuroscience
                Frontiers Media S.A.
                1662-5137
                25 September 2014
                2014
                : 8
                : 181
                Affiliations
                [1] 1Department of Experimental and Clinical Medicine, University of Florence Florence, Italy
                [2] 2Department of Statistics, Informatics, Applications, University of Florence Florence, Italy
                Author notes

                Edited by: Mikhail Lebedev, Duke University, USA

                Reviewed by: Peter Praamstra, Radboud University Nijmegen, Netherlands; Yuri P. Ivanenko, IRCCS Fondazione Santa Lucia, Italy

                *Correspondence: Diego Minciacchi, Department of Experimental and Clinical Medicine, University of Florence, Viale Morgagni 63, Florence I-50134, Italy e-mail: diego@ 123456unifi.it

                This article was submitted to the journal Frontiers in Systems Neuroscience.

                Article
                10.3389/fnsys.2014.00181
                4174732
                5a0c0cbd-6a3a-46ae-a67a-5814d0595288
                Copyright © 2014 Bravi, Quarta, Cohen, Gottard and Minciacchi.

                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) or licensor 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
                : 30 June 2014
                : 08 September 2014
                Page count
                Figures: 5, Tables: 4, Equations: 0, References: 68, Pages: 13, Words: 11096
                Categories
                Neuroscience
                Original Research Article

                Neurosciences
                sensory-motor integration,timing,isochronous movements,auditory imagery,music
                Neurosciences
                sensory-motor integration, timing, isochronous movements, auditory imagery, music

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