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The impact of musical experience on neural sound encoding performance

机译:音乐体验对神经声音编码性能的影响

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In this study, 64-channel single trial auditory brain oscillations (STABO) have been firstly analyzed by using complexity metrics to observe the effect of musical experience on brain functions. Experimental data was recorded from eyes-opened volunteers during listening the musical chords by piano. Complexity estimation methods were compared to each other for classification of groups (professional musicians and non-musicians) by using both classifiers (support vector machine (SVM), Naive Bayes (NB)) and statistical tests (one-way ANOVA) with respect to electrode locations. Permutation entropy (PermEn) is found to be the best metric (p 0.0001, 98.37% and 98.41% accuracies for tonal and atonal ensembles) at fronto-temporal regions which are responsible for cognitive task evaluation and perception of sound. PermEn also provides the meaningful results at the whole cortex (p 0.0001, 99.81% accuracy for both tonal and atonal ensembles) through SVM with Radial Basis kernels superior to Gaussians. Almost the similar performance is also obtained for temporal features. Although, performance improvements are observed for spectral methods with NB, the considerable better results are obtained with SVM. The results indicate that musical stimuli cause pattern variations instead of spectral variations on STABO due to relatively higher neuronal activities around auditory cortex. In conclusion, temporal regions produce response to auditory stimuli, while frontal area integrates the auditory task at the same time. As well, the parietal cortex produces neural information according to the degree of attention generated by environmental changes such as atonal stimuli. It can be clearly stated that musical experience enhances the neural encoding performance of sound tonality at mostly fronto-temporal regions.
机译:在本研究中,首先通过使用复杂度指标来观察音乐经验对大脑功能的影响,首先分析了64通道单试听觉脑振荡(stabo)。在通过钢琴聆听音乐和弦时,从眼睛开放的志愿者记录了实验数据。通过使用两个分类器(支持向量机(SVM),天真贝叶斯(NB))和统计测试(单向ANOVA)对组(专业音乐家和非音乐家)彼此进行比较进行复杂性估算方法。电极位置。发现置换熵(PEREN)是最佳的公制(P <0.0001,98.37%和98.37%和98.37%和98.37%和98.37%和98.41%),其负责认知任务评估和声音的感知。封闭还通过SVM提供了整个皮质(P <0.0001,20.0001,99.81,99.81%的精度)提供了有意义的结果,通过SVM具有优于高斯的径向基础核。对于时间特征,也可以获得几乎获得了类似的性能。虽然,对于具有Nb的光谱方法,观察到性能改进,但是通过SVM获得了相当大的结果。结果表明,由于围绕听觉皮质的相对较高的神经元活动,音乐刺激导致图案变异而不是稳定性的光谱变化。总之,临时区域对听觉刺激产生响应,而前置区域同时集成了听觉任务。同样,榫塔拉皮质根据环境变化如局部刺激产生的注意程度产生神经信息。可以清楚地说,音乐体验提高了声音单位的神经编码性能,主要是额颞区域。

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