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神经振荡的稳定性支持听觉-运动同步。

Stability of Neural Oscillations Supports Auditory-Motor Synchronization.

作者信息

Scheurich Rebecca, Bégel Valentin, Sahlas Ella, Palmer Caroline

机构信息

Department of Psychology, McGill University, Montreal, Quebec, Canada.

出版信息

Eur J Neurosci. 2025 May;61(9):e70127. doi: 10.1111/ejn.70127.

DOI:10.1111/ejn.70127
PMID:40320823
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12050907/
Abstract

Previous findings suggest that auditory-motor synchronization is supported by increased coactivation of auditory and motor brain networks. Here, we compare synchronization accuracy and consistency with the temporal dynamics of neural signals during auditory-motor synchronization. Recurrence quantification analysis, a nonlinear technique for characterizing the temporal dynamics of complex systems, was applied to participants' neurophysiological activity recorded via electroencephalography (EEG) during an auditory-motor synchronization task. Changes in participants' neural predictability and stability were compared with their behavioral synchronization accuracy and consistency. EEG was recorded while participants produced a familiar melody at a comfortable rate as a measure of optimal temporal stability. Then, participants synchronized their taps with an auditory metronome presented at each participant's optimal rate and at rates 15% and 30% slower. EEG-based outcomes of determinism (predictability) and meanline (stability) were compared with behavioral synchronization measures. Participants showed decreased synchronization accuracy and higher EEG-based determinism at slower rates, consistent with lower flexibility. Furthermore, neural stability measures correlated with synchronization consistency across stimulus rates; as neural stability increased, so did behavioral synchronization consistency. Recurrence-based measures of neural stability may indicate a general mechanism supporting the maintenance of auditory-motor synchronization.

摘要

先前的研究结果表明,听觉-运动同步受到听觉和运动脑网络共同激活增加的支持。在此,我们将同步准确性和一致性与听觉-运动同步期间神经信号的时间动态进行比较。递归量化分析是一种用于表征复杂系统时间动态的非线性技术,应用于在听觉-运动同步任务期间通过脑电图(EEG)记录的参与者神经生理活动。将参与者神经可预测性和稳定性的变化与其行为同步准确性和一致性进行比较。在参与者以舒适的速度演奏熟悉的旋律时记录脑电图,以此作为最佳时间稳定性的衡量指标。然后,参与者以每个参与者的最佳速度以及慢15%和30%的速度与听觉节拍器同步敲击。将基于脑电图的确定性(可预测性)和平均线(稳定性)结果与行为同步测量进行比较。参与者在较慢速度下表现出同步准确性下降以及基于脑电图的确定性更高,这与较低的灵活性一致。此外,神经稳定性测量与不同刺激速率下的同步一致性相关;随着神经稳定性增加,行为同步一致性也增加。基于递归的神经稳定性测量可能表明一种支持维持听觉-运动同步的一般机制。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6807/12050907/12c783e262a5/EJN-61-0-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6807/12050907/55ca26f61698/EJN-61-0-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6807/12050907/e242da66becb/EJN-61-0-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6807/12050907/6fbdde8900c3/EJN-61-0-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6807/12050907/12c783e262a5/EJN-61-0-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6807/12050907/55ca26f61698/EJN-61-0-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6807/12050907/e242da66becb/EJN-61-0-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6807/12050907/6fbdde8900c3/EJN-61-0-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6807/12050907/12c783e262a5/EJN-61-0-g002.jpg

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