| 基于持续同调性的人脑认知过程格式塔模式识别拓扑分析 |
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| 引用本文： | 刘再生,倪霏,李荣鹏,张宏纲,刘畅,张解放,谢松云.基于持续同调性的人脑认知过程格式塔模式识别拓扑分析[J].电信科学,2021,37(7):77-85. |
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| 作者姓名： | 刘再生 倪霏 李荣鹏 张宏纲 刘畅 张解放 谢松云 |
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| 作者单位： | 浙江大学信息与电子工程学院,浙江 杭州 310027;浙江传媒学院,浙江 杭州 310018;西北工业大学,陕西 西安 710129 |
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| 基金项目： | 国家重点研发计划项目(2018YFB0803702);国家自然科学基金资助项目(61731002);国家自然科学基金资助项目(62071425);浙江省重点研发计划项目(2019C01002);浙江省重点研发计划项目(2019C03131);华为合作项目；之江实验室资助项目(2019LC0AB01);浙江省自然科学基金资助项目(LY20F010016) |
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| 摘 要： | 信息通信技术和神经科学的融合发展预示了脑对脑无线通信的可能性与巨大潜力。将持续同调分析方法与脑电图（EEG）结合，提取了在格式塔完形（Gestalt）认知测试中大脑对不同轮廓和形状的神经反应的生理学特征。实验结果表明，当被试者观察随机序列图像（random sequence diagram，RSD）时，其大脑额叶涉及的活动区域多于其观察有序格式塔图像（Gestalt image，GST）。同时，RSD诱发的EEG信号在几个频带上与GST的持续同调熵（persistent entropy，PE）有着显著不同，这表明人类对形状和轮廓的认知过程，可以通过拓扑分析在一定程度上实现分类区分。该方法可以在保留原生信号的整体和局部特征的前提下实现神经信号的数字化。总的来说，通过对EEG信号的持续同源性特征评估量化了认知过程神经信号的相关性，提供了实现B2BC中神经信号数字化的可行方法。
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| 关 键 词： | 6G 脑对脑通信 格式塔 脑电图 持续同调熵 |
Persistent homology based topological analysis on the gestalt patterns during human brain cognition process |
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| Zaisheng LIU,Fei NI,Rongpeng LI,Honggang ZHANG,Chang LIU,Jiefang ZHANG,Songyun XIE.Persistent homology based topological analysis on the gestalt patterns during human brain cognition process[J].Telecommunications Science,2021,37(7):77-85. |
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| Authors: | Zaisheng LIU Fei NI Rongpeng LI Honggang ZHANG Chang LIU Jiefang ZHANG Songyun XIE |
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| Affiliation: | 1. College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou 310027, China;2. Communication University of Zhejiang, Hangzhou 310018, China;3. Northwestern Polytechnical University, Xi’an 710129, China |
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| Abstract: | The integrated development of information communication technology and neuroscience heralds the possibility and great potential of brain-to-brain wireless communication(B2BC).The physiologically meaningful features of brain responses were extracted to different contour and shape in images in Gestalt cognitive tests by combining persistent homology analysis with electroencephalogram (EEG).The experimental results show that more brain regions in the frontal lobe were involved when the subject perceives the random and disordered combination of images compared to the ordered Gestalt images.Meanwhile, the persistence entropy of EEG data evoked by random sequence diagram (RSD) was observed to be significantly different from that by the ordered Gestalt images(GST) in several frequency bands, which indicated that human cognition of shapes and contours, such as a preliminary advanced cognition process, could be separated to some extent through topological analysis.This method can digitize the neural signals while preserving the whole and local features of the original signals.In general, the cognitively related neural correlates by persistent homology features of EEG signal are revaluated and quantified, which provides an approach to realize the digitization of neural signals in brain-to-brain wireless communication. |
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| Keywords: | 6G brain-to-brain communication Gestalt electroencephalogram persistent entropy |
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