Neural Dynamics of Creative Movements During the Rehearsal and Performance of "LiveWire".

IF 5.8 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES Scientific Data Pub Date : 2024-11-09 DOI:10.1038/s41597-024-04010-8
Maxine Annel Pacheco-Ramírez, Mauricio A Ramírez-Moreno, Komal Kukkar, Nishant Rao, Derek Huber, Anthony K Brandt, Andy Noble, Dionne Noble, Bryan Ealey, Jose L Contreras-Vidal
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Abstract

This report contains a description of physiological and motion data, recorded simultaneously and in synchrony using the hyperscanning method from two professional dancers using wireless mobile brain-body imaging (MoBI) technology during rehearsals and public performances of "LiveWire" - a new composition comprised of five choreographed music and dance sections inspired by neuroscience principles. Brain and ocular activity were measured using 28-channel scalp electroencephalography (EEG), and 4-channel electrooculography (EOG), respectively; and head motion was recorded using an inertial measurement unit (IMU) placed on the forehead of each dancer. Video recordings were obtained for each session to allow for tagging of physiological and motion signals and for behavioral analysis. Data recordings were collected from 10 sessions over a 4-month period, in which the dancers rehearsed or performed (in front of an audience) choreographed expressive movements. A detailed explanation of the experimental set-up, the steps carried out for data collection, and an explanation on the usage are provided in this report.

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排练和表演 "LiveWire "时创意动作的神经动力学。
本报告描述了两位专业舞者在排练和公开演出 "LiveWire"(由五个受神经科学原理启发而编排的音乐和舞蹈部分组成的新作品)期间,使用无线移动脑体成像(MoBI)技术,通过超扫描方法同步记录的生理和运动数据。分别使用 28 通道头皮脑电图(EEG)和 4 通道眼电图(EOG)测量大脑和眼部活动;使用放置在每位舞者前额的惯性测量单元(IMU)记录头部运动。每次训练都有视频记录,以便对生理和运动信号进行标记和行为分析。在为期 4 个月的 10 次训练中,舞者们排练或(在观众面前)表演了编排好的富有表现力的动作。本报告详细介绍了实验装置、数据收集步骤和使用方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Scientific Data
Scientific Data Social Sciences-Education
CiteScore
11.20
自引率
4.10%
发文量
689
审稿时长
16 weeks
期刊介绍: Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data. The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.
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