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      Activating and Relaxing Music Entrains the Speed of Beat Synchronized Walking

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          Abstract

          Inspired by a theory of embodied music cognition, we investigate whether music can entrain the speed of beat synchronized walking. If human walking is in synchrony with the beat and all musical stimuli have the same duration and the same tempo, then differences in walking speed can only be the result of music-induced differences in stride length, thus reflecting the vigor or physical strength of the movement. Participants walked in an open field in synchrony with the beat of 52 different musical stimuli all having a tempo of 130 beats per minute and a meter of 4 beats. The walking speed was measured as the walked distance during a time interval of 30 seconds. The results reveal that some music is ‘activating’ in the sense that it increases the speed, and some music is ‘relaxing’ in the sense that it decreases the speed, compared to the spontaneous walked speed in response to metronome stimuli. Participants are consistent in their observation of qualitative differences between the relaxing and activating musical stimuli. Using regression analysis, it was possible to set up a predictive model using only four sonic features that explain 60% of the variance. The sonic features capture variation in loudness and pitch patterns at periods of three, four and six beats, suggesting that expressive patterns in music are responsible for the effect. The mechanism may be attributed to an attentional shift, a subliminal audio-motor entrainment mechanism, or an arousal effect, but further study is needed to figure this out. Overall, the study supports the hypothesis that recurrent patterns of fluctuation affecting the binary meter strength of the music may entrain the vigor of the movement. The study opens up new perspectives for understanding the relationship between entrainment and expressiveness, with the possibility to develop applications that can be used in domains such as sports and physical rehabilitation.

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          Most cited references24

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          Bias in error estimation when using cross-validation for model selection

          Background Cross-validation (CV) is an effective method for estimating the prediction error of a classifier. Some recent articles have proposed methods for optimizing classifiers by choosing classifier parameter values that minimize the CV error estimate. We have evaluated the validity of using the CV error estimate of the optimized classifier as an estimate of the true error expected on independent data. Results We used CV to optimize the classification parameters for two kinds of classifiers; Shrunken Centroids and Support Vector Machines (SVM). Random training datasets were created, with no difference in the distribution of the features between the two classes. Using these "null" datasets, we selected classifier parameter values that minimized the CV error estimate. 10-fold CV was used for Shrunken Centroids while Leave-One-Out-CV (LOOCV) was used for the SVM. Independent test data was created to estimate the true error. With "null" and "non null" (with differential expression between the classes) data, we also tested a nested CV procedure, where an inner CV loop is used to perform the tuning of the parameters while an outer CV is used to compute an estimate of the error. The CV error estimate for the classifier with the optimal parameters was found to be a substantially biased estimate of the true error that the classifier would incur on independent data. Even though there is no real difference between the two classes for the "null" datasets, the CV error estimate for the Shrunken Centroid with the optimal parameters was less than 30% on 18.5% of simulated training data-sets. For SVM with optimal parameters the estimated error rate was less than 30% on 38% of "null" data-sets. Performance of the optimized classifiers on the independent test set was no better than chance. The nested CV procedure reduces the bias considerably and gives an estimate of the error that is very close to that obtained on the independent testing set for both Shrunken Centroids and SVM classifiers for "null" and "non-null" data distributions. Conclusion We show that using CV to compute an error estimate for a classifier that has itself been tuned using CV gives a significantly biased estimate of the true error. Proper use of CV for estimating true error of a classifier developed using a well defined algorithm requires that all steps of the algorithm, including classifier parameter tuning, be repeated in each CV loop. A nested CV procedure provides an almost unbiased estimate of the true error.
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            Tagging the neuronal entrainment to beat and meter.

            Feeling the beat and meter is fundamental to the experience of music. However, how these periodicities are represented in the brain remains largely unknown. Here, we test whether this function emerges from the entrainment of neurons resonating to the beat and meter. We recorded the electroencephalogram while participants listened to a musical beat and imagined a binary or a ternary meter on this beat (i.e., a march or a waltz). We found that the beat elicits a sustained periodic EEG response tuned to the beat frequency. Most importantly, we found that meter imagery elicits an additional frequency tuned to the corresponding metric interpretation of this beat. These results provide compelling evidence that neural entrainment to beat and meter can be captured directly in the electroencephalogram. More generally, our results suggest that music constitutes a unique context to explore entrainment phenomena in dynamic cognitive processing at the level of neural networks.
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              Listening to rhythms activates motor and premotor cortices.

              We used functional magnetic resonance imaging (fMRI) to identify brain areas involved in auditory rhythm perception. Participants listened to three rhythm sequences that varied in temporal predictability. The most predictable sequence was an isochronous rhythm sequence of a single interval (ISO). The other two sequences had nine intervals with unequal durations. One of these had interval durations of integer ratios relative to the shortest interval (METRIC). The other had interval durations of non-integer ratios relative to the shortest interval (NON-METRIC), and was thus perceptually more complex than the other two. In addition, we presented unpredictable sequences with randomly distributed intervals (RAN). We tested two hypotheses. Firstly, that areas involved in motor timing control would also process the temporal predictability of sensory cues. Therefore, there was no active task included in the experiment that could influence the participant perception or induce motor preparation. We found that dorsal premotor cortex (PMD), SMA, preSMA, and lateral cerebellum were more active when participants listen to rhythm sequences compared to random sequences. The activity pattern in supplementary motor area (SMA) and preSMA suggested a modulation dependent on sequence predictability, strongly suggesting a role in temporal sensory prediction. Secondly, we hypothesized that the more complex the rhythm sequence, the more it would engage short-term memory processes of the prefrontal cortex. We found that the superior prefrontal cortex was more active when listening to METRIC and NON-METRIC compared to ISO. We argue that the complexity of rhythm sequences is an important factor in modulating activity in many of the rhythm areas. However, the difference in complexity of our stimuli should be regarded as continuous.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2013
                10 July 2013
                : 8
                : 7
                : e67932
                Affiliations
                [1 ]Institute for Psychoacoustics and Electronic Music, Department of Musicology, Ghent University, Ghent, Belgium
                [2 ]Department of Electronics and Information Systems, Ghent University, Ghent, Belgium
                UNLV, United States of America
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: ML DM FS LvN. Performed the experiments: FS. Analyzed the data: DM MV J-PM. Wrote the paper: ML J-PM.

                Article
                PONE-D-12-39395
                10.1371/journal.pone.0067932
                3707869
                23874469
                25254273-07d2-41b4-9bce-369d58acf4f8
                Copyright @ 2013

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 13 December 2012
                : 20 May 2013
                Page count
                Pages: 11
                Funding
                Funding by a Methusalem grant from the Flemish Government, Belgium, and a BOF grant from Ghent University. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Computer Science
                Computer Modeling
                Medicine
                Mental Health
                Psychology
                Behavior
                Attention (Behavior)
                Experimental Psychology
                Sports and Exercise Medicine
                Social and Behavioral Sciences
                Psychology
                Behavior
                Attention (Behavior)
                Experimental Psychology
                Sensory Perception

                Uncategorized
                Uncategorized

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