舞蹈大脑的脑电图:解码双联舞中的感觉、运动和社会过程。

IF 4.4 2区 医学 Q1 NEUROSCIENCES
Félix Bigand, Roberta Bianco, Sara F Abalde, Trinh Nguyen, Giacomo Novembre
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引用次数: 0

摘要

现实世界的社会认知需要处理和适应多种动态信息流。在这样的生态条件下解释神经活动仍然是神经科学的一个关键挑战。本研究利用先进的去噪技术和多变量建模技术,从参与自发二元舞蹈的成对参与者(男性-男性、女性-女性和男性-女性)中提取可解释的脑电图信号。利用多变量时间响应函数(mTRFs),我们研究了音乐声学、自生成运动学、他人生成运动学和社会协调如何独特地影响脑电图活动。眼、面部和颈部肌肉的肌电图记录也被建模以控制伪影。mTRFs有效地解开了与四个过程相关的神经信号:(I)音乐的听觉跟踪,(II)自我生成动作的控制,(III)伙伴动作的视觉监控,以及(IV)社会协调的视觉跟踪。我们发现,前三个神经信号是由事件相关电位驱动的:由声音事件触发的P50-N100-P200,由运动启动触发的中央侧化运动相关皮层电位,以及由运动观察触发的枕部N170。值得注意的是,(以前未知的)社会协调的神经标记编码舞者之间的时空对齐,超越了单独编码自我或伴侣相关的运动学。当伴侣可以看到对方时,这个标记就会出现,在枕区呈现地形分布,并且是由运动观察而不是初始化驱动的。利用数据驱动的运动学分解,我们进一步证明了垂直弹跳运动最能驱动观察者的脑电活动。这些发现突出了现实世界神经成像与多元建模相结合的潜力,揭示了复杂而自然的社会行为背后的机制。现实世界的大脑功能包括同时整合多个信息流。然而,由于计算方法的不足,以实验室为基础的神经科学经常孤立地检查神经过程。利用对参与者随音乐自由跳舞的脑电图数据的多元建模,我们证明了有可能梳理出与音乐感知、运动控制和观察伴侣运动相关的生理上建立的神经过程。至关重要的是,我们发现了一个以前未知的社会协调神经标记,它编码舞者之间的时空对齐,而不仅仅是自我或伴侣相关的运动学。这些发现突出了计算神经科学在揭示现实世界社会和运动行为背后的生物机制方面的潜力,促进了我们对大脑如何支持动态和互动活动的理解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
EEG of the Dancing Brain: Decoding Sensory, Motor, and Social Processes during Dyadic Dance.

Real-world social cognition requires processing and adapting to multiple dynamic information streams. Interpreting neural activity in such ecological conditions remains a key challenge for neuroscience. This study leverages advancements in denoising techniques and multivariate modeling to extract interpretable EEG signals from pairs of (male and/or female) participants engaged in spontaneous dyadic dance. Using multivariate temporal response functions (mTRFs), we investigated how music acoustics, self-generated kinematics, other-generated kinematics, and social coordination uniquely contributed to EEG activity. Electromyogram recordings from ocular, face, and neck muscles were also modeled to control for artifacts. The mTRFs effectively disentangled neural signals associated with four processes: (I) auditory tracking of music, (II) control of self-generated movements, (III) visual monitoring of partner movements, and (IV) visual tracking of social coordination. We show that the first three neural signals are driven by event-related potentials: the P50-N100-P200 triggered by acoustic events, the central lateralized movement-related cortical potentials triggered by movement initiation, and the occipital N170 triggered by movement observation. Notably, the (previously unknown) neural marker of social coordination encodes the spatiotemporal alignment between dancers, surpassing the encoding of self- or partner-related kinematics taken alone. This marker emerges when partners can see each other, exhibits a topographical distribution over occipital areas, and is specifically driven by movement observation rather than initiation. Using data-driven kinematic decomposition, we further show that vertical bounce movements best drive observers' EEG activity. These findings highlight the potential of real-world neuroimaging, combined with multivariate modeling, to uncover the mechanisms underlying complex yet natural social behaviors.

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来源期刊
Journal of Neuroscience
Journal of Neuroscience 医学-神经科学
CiteScore
9.30
自引率
3.80%
发文量
1164
审稿时长
12 months
期刊介绍: JNeurosci (ISSN 0270-6474) is an official journal of the Society for Neuroscience. It is published weekly by the Society, fifty weeks a year, one volume a year. JNeurosci publishes papers on a broad range of topics of general interest to those working on the nervous system. Authors now have an Open Choice option for their published articles
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