Max Planck - NYU Center for Language, Music and Emotion, New York, USA; Department of Psychology, New York University, New York, USA; Department of Clinical Psychology, Free University Amsterdam, Amsterdam, The Netherlands.
Max Planck Institute for Empirical Aesthetics, Frankfurt, Germany.
Neuroimage. 2021 Feb 15;227:117436. doi: 10.1016/j.neuroimage.2020.117436. Epub 2020 Oct 8.
When we feel connected or engaged during social behavior, are our brains in fact "in sync" in a formal, quantifiable sense? Most studies addressing this question use highly controlled tasks with homogenous subject pools. In an effort to take a more naturalistic approach, we collaborated with art institutions to crowdsource neuroscience data: Over the course of 5 years, we collected electroencephalogram (EEG) data from thousands of museum and festival visitors who volunteered to engage in a 10-min face-to-face interaction. Pairs of participants with various levels of familiarity sat inside the Mutual Wave Machine-an artistic neurofeedback installation that translates real-time correlations of each pair's EEG activity into light patterns. Because such inter-participant EEG correlations are prone to noise contamination, in subsequent offline analyses we computed inter-brain coupling using Imaginary Coherence and Projected Power Correlations, two synchrony metrics that are largely immune to instantaneous, noise-driven correlations. When applying these methods to two subsets of recorded data with the most consistent protocols, we found that pairs' trait empathy, social closeness, engagement, and social behavior (joint action and eye contact) consistently predicted the extent to which their brain activity became synchronized, most prominently in low alpha (7-10 Hz) and beta (20-22 Hz) oscillations. These findings support an account where shared engagement and joint action drive coupled neural activity and behavior during dynamic, naturalistic social interactions. To our knowledge, this work constitutes a first demonstration that an interdisciplinary, real-world, crowdsourcing neuroscience approach may provide a promising method to collect large, rich datasets pertaining to real-life face-to-face interactions. Additionally, it is a demonstration of how the general public can participate and engage in the scientific process outside of the laboratory. Institutions such as museums, galleries, or any other organization where the public actively engages out of self-motivation, can help facilitate this type of citizen science research, and support the collection of large datasets under scientifically controlled experimental conditions. To further enhance the public interest for the out-of-the-lab experimental approach, the data and results of this study are disseminated through a website tailored to the general public (wp.nyu.edu/mutualwavemachine).
当我们在社交行为中感到联系或参与时,我们的大脑实际上是否在正式的、可量化的意义上“同步”?大多数解决这个问题的研究都使用具有同质主体群体的高度受控任务。为了采取更自然的方法,我们与艺术机构合作,从人群中收集神经科学数据:在 5 年的时间里,我们从数千名自愿参与 10 分钟面对面互动的博物馆和节日参观者那里收集了脑电图 (EEG) 数据。具有不同熟悉程度的参与者对坐在 Mutual Wave Machine 中-一种将实时实时相关性转化为光模式的艺术神经反馈装置。由于这种参与者间 EEG 相关性容易受到噪声污染,因此在随后的离线分析中,我们使用想象相干性和投影功率相关性计算了大脑间耦合,这两种同步度量主要不受瞬时噪声驱动的相关性的影响。当将这些方法应用于具有最一致协议的两个记录数据集子集时,我们发现,参与者的特质同理心、社交亲密程度、参与度和社交行为(共同行动和眼神交流)一致地预测了他们的大脑活动变得同步的程度,在低 alpha(7-10 Hz)和 beta(20-22 Hz)振荡中最为明显。这些发现支持了一种解释,即共同参与和共同行动驱动动态、自然社交互动中的耦合神经活动和行为。据我们所知,这项工作首次证明了跨学科、现实世界、众包神经科学方法可以提供一种有前途的方法来收集与现实生活中的面对面互动相关的大型、丰富数据集。此外,它还展示了普通公众如何在实验室之外参与和参与科学过程。博物馆、画廊或任何其他公众出于自我激励而积极参与的组织,可以帮助促进这种类型的公民科学研究,并支持在科学控制的实验条件下收集大型数据集。为了进一步提高公众对实验室外实验方法的兴趣,本研究的数据和结果通过一个针对公众的网站(wp.nyu.edu/mutualwavemachine)进行传播。