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大脑网络灵活性可预测熟练的音乐演奏表现。

Brain network flexibility as a predictor of skilled musical performance.

机构信息

Neural Information Dynamics Laboratory, Department of Computer Science and Engineering, Toyohashi University of Technology, Toyohashi, Japan.

Sony Computer Science Laboratories Inc, Tokyo 1410022, Japan.

出版信息

Cereb Cortex. 2023 Oct 9;33(20):10492-10503. doi: 10.1093/cercor/bhad298.

Abstract

Interactions between the body and the environment are dynamically modulated by upcoming sensory information and motor execution. To adapt to this behavioral state-shift, brain activity must also be flexible and possess a large repertoire of brain networks so as to switch them flexibly. Recently, flexible internal brain communications, i.e. brain network flexibility, have come to be recognized as playing a vital role in integrating various sensorimotor information. Therefore, brain network flexibility is one of the key factors that define sensorimotor skill. However, little is known about how flexible communications within the brain characterize the interindividual variation of sensorimotor skill and trial-by-trial variability within individuals. To address this, we recruited skilled musical performers and used a novel approach that combined multichannel-scalp electroencephalography, behavioral measurements of musical performance, and mathematical approaches to extract brain network flexibility. We found that brain network flexibility immediately before initiating the musical performance predicted interindividual differences in the precision of tone timbre when required for feedback control, but not for feedforward control. Furthermore, brain network flexibility in broad cortical regions predicted skilled musical performance. Our results provide novel evidence that brain network flexibility plays an important role in building skilled sensorimotor performance.

摘要

身体和环境之间的相互作用是由即将到来的感觉信息和运动执行动态调节的。为了适应这种行为状态的转变,大脑活动也必须具有灵活性,并拥有大量的大脑网络,以便灵活地切换它们。最近,灵活的内部大脑通信,即大脑网络灵活性,已被认为在整合各种感觉运动信息方面起着至关重要的作用。因此,大脑网络灵活性是定义感觉运动技能的关键因素之一。然而,对于大脑内部的灵活通信如何描述个体间感觉运动技能的差异以及个体内的试验间可变性,我们知之甚少。为了解决这个问题,我们招募了熟练的音乐演奏者,并使用了一种新的方法,该方法结合了多通道头皮脑电图、音乐演奏行为测量和数学方法来提取大脑网络灵活性。我们发现,在开始演奏音乐之前,大脑网络灵活性可以预测在需要反馈控制时音色调的精度的个体间差异,但在需要前馈控制时则不行。此外,广泛的皮质区域的大脑网络灵活性可以预测熟练的音乐演奏。我们的研究结果提供了新的证据,表明大脑网络灵活性在构建熟练的感觉运动表现中起着重要作用。

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