基于功能近红外的群体脑网络成像与建模技术
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- 英文论文题名：Multi-brain network imaging and modeling based on functional near-infrared spectroscopy
- 论文作者：段炼 ; 戴瑞娜 ; 朱朝喆
- 英文论文作者：Lian Duan ; Rui-Na Dai ; Chao-Zhe Zhu ; State Key Laboratory of Cognitive Neuroscience and Learning ; Beijing Normal University
- 年：2015
- 作者机构：北京师范大学认知神经科学与学习国家重点实验室;
- 论文关键词：功能近红外 ; 超扫描 ; 社会交互 ; 群体脑网络 ; 图论
- 英文论文关键词：fNIRS ; hyperscanning ; social interaction ; multi-brain network ; graph theory
- 会议召开时间：2015-10-16
- 会议录名称：第十八届全国心理学学术会议摘要集——心理学与社会发展
- 英文会议录名称：Proceedings of the 18th National Academic Congress of Psychology
- 语种：中文
- 分类号：B845.1
- 学会代码：ZGXG
- 会议名称：第十八届全国心理学学术会议
- 会议地点：中国天津
- 主办单位：中国心理学会
- 学会名称：中国心理学会
- 页数：2
- 文件大小：741k
- 原文格式：D
- 会议级别：全国
摘要
社会交互对人类的进化和个体的发展具有至关重要的意义。探索群体社会交互的神经机制有助于理解社会交互行为,并且可能对社会障碍的识别和干预提供帮助。近年来,脑成像超扫描(hyperscanning)技术的发展允许研究者同时扫描两名受试者的大脑活动并从单脑和双脑层次进行分析。但在应用hyperscanning技术研究更大规模的社会群体的交互行为时仍然面临两方面的挑战。一方面的挑战是如何在自然环境下对更大规模的群体进行同时成像。另一方面的挑战是如何对更大规模的群体交互神经数据进行分析与建模。针对这两方面的挑战,我们提出了基于功能近红外的群体脑网络成像技术。这一技术由两部分组成,一是基于功能近红外的高生态效度群体脑成像技术。通过结合多台近红外设备,可以对十几名甚至几十名受试者在接近日常的交互场景下进行扫描。二是基于图论的群体脑网络建模与分析技术。将群体中每个大脑作为网络的结点,将脑间连接作为网络的边,构建群体脑网络,通过分析网络的各项拓扑属性来研究群体的交互行为。利用这一技术,我们进行了一项群体合作敲鼓实验。实验在接近自然的场景中对由9名受试者构成的群体的合作敲鼓过程进行了成像并构建了群体脑网络。通过对网络平均连接强度、网络的效率进行分析,发现受试者群体脑网络结构在高、低交互条件下存在显著的差别,高交互条件下的网络连接强度和网络效率显著高于低交互条件。对交互过程的动态分析进一步发现群体脑网络拓扑属性的动态变化与群体信息交互动态过程存在显著关联。这些结果显示,基于功能近红外的群体脑网络成像与建模技术在研究群体交互行为神经机制方面拥有巨大潜力,为群体交互行为神经机制的研究提供了全新的研究框架。
Social interactions have critical significance in human evolution and individuals' development. Studying the neural basis of human social interactions can help to understand the social behaviors, and may improve the diagnosis and therapy of social disorders. In recent years, the developing of the hyperscanning technology allows simultaneously scanning the brain activities of two participants and then analyzing the data from both single-brain level and paired-brain level. However, as the participant number further increases, great difficulties raise. One challenge is how to simultaneously measure all the interacting brains of a much larger social group. The other challenge is how to model and analyze the data from the complex large group interaction. Confronting these challenges, we propose a new technology named as multi-brain network imaging and modeling based on functional near-infrared spectroscopy. This technology consists of two parts. The first part is a multi-brain imaging technique with high ecological validity based on multiple functional near-infrared spectroscopy(fNIRS) systems. The second part is a multi-brain network modeling method based on graph theory. By taking each brain as a network node and the relationship between any two brains as a network edge, one can construct a network model for a group of interacting brains. By analyzing the network's properties, the emergent group social behaviors can be studied. Using this technology, we conducted a group social drumming experiment. We studied the multi-brain network from groups of 9 participants during an interaction situation near daily life. It was found the multi-brain networks of two conditions(high interaction and low interaction) are significantly different, in both average connectivity strength and network efficiency. It was also found the dynamic of the network properties are related with the group interaction behavior changes. This new technology shows great potentials in studying the group social behaviors, and provides a new research framework for investigating the neural basis of group social interactions.
Social interactions have critical significance in human evolution and individuals' development. Studying the neural basis of human social interactions can help to understand the social behaviors, and may improve the diagnosis and therapy of social disorders. In recent years, the developing of the hyperscanning technology allows simultaneously scanning the brain activities of two participants and then analyzing the data from both single-brain level and paired-brain level. However, as the participant number further increases, great difficulties raise. One challenge is how to simultaneously measure all the interacting brains of a much larger social group. The other challenge is how to model and analyze the data from the complex large group interaction. Confronting these challenges, we propose a new technology named as multi-brain network imaging and modeling based on functional near-infrared spectroscopy. This technology consists of two parts. The first part is a multi-brain imaging technique with high ecological validity based on multiple functional near-infrared spectroscopy(fNIRS) systems. The second part is a multi-brain network modeling method based on graph theory. By taking each brain as a network node and the relationship between any two brains as a network edge, one can construct a network model for a group of interacting brains. By analyzing the network's properties, the emergent group social behaviors can be studied. Using this technology, we conducted a group social drumming experiment. We studied the multi-brain network from groups of 9 participants during an interaction situation near daily life. It was found the multi-brain networks of two conditions(high interaction and low interaction) are significantly different, in both average connectivity strength and network efficiency. It was also found the dynamic of the network properties are related with the group interaction behavior changes. This new technology shows great potentials in studying the group social behaviors, and provides a new research framework for investigating the neural basis of group social interactions.
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