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

刘再生; 倪霏; 李荣鹏; 张宏纲; 刘畅; 张解放; 谢松云

doi:10.11959/j.issn.1000-0801.2021124

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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

研究与开发 | 更新时间：2024-06-05

- 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
- Persistent homology based topological analysis on the gestalt patterns during human brain cognition process
- 电信科学 2021年37卷第7期页码：77-85
- 作者机构：
  
  1. 浙江大学信息与电子工程学院，浙江杭州 310027
  2. 浙江传媒学院，浙江杭州 310018
  3. 西北工业大学，陕西西安 710129
- 作者简介：
  
  [ "刘再生（1997- ），男，浙江大学信息与电子工程学院硕士生，主要研究方向为代数拓扑、人工智能、脑电分析、脑对脑通信" ]
  [ "倪霏（1997- ），女，浙江大学信息与电子工程学院博士生，主要研究方向为代数拓扑、群体智能、深度学习" ]
  [ "李荣鹏（1989- ），男，博士，浙江大学信息与电子工程学院副教授，主要研究方向为智能通信网络、网络智能、网络切片" ]
  [ "张宏纲（1967- ），男，博士，浙江大学信息与电子工程学院教授，主要研究方向为智能通信网络、认知无线电、绿色通信和下一代异构蜂窝网络架构" ]
  [ "刘畅（1990- ），女，博士，浙江传媒学院助理研究员，主要研究方向为面向智能媒体的脑科学技术、计算神经科学等" ]
  [ "张解放（1959- ），男，博士，浙江传媒学院教授，智能媒体技术研究院院长，主要研究方向为非线性物理、怪波理论等" ]
  [ "谢松云（1968- ），女，博士，西北工业大学教授，陕西省脑机一体化及其无人系统应用国际联合研究中心主任，主要研究方向为脑科学、机器学习方法及应用等" ]
- 基金信息：
  
  国家重点研发计划项目;The National Key Research and Development Program of China(2018YFB0803702);国家自然科学基金资助项目;The National Natural Science Foundation of China(61731002);国家自然科学基金资助项目;The National Natural Science Foundation of China(62071425);浙江省重点研发计划项目;Zhejiang Key Research and Development Plan(2019C01002);浙江省重点研发计划项目;Zhejiang Key Research and Development Plan(2019C03131);华为合作项目：之江实验室资助项目;Huawei Cooperation Project, The Project sponsored by Zhejiang Lab(2019LC0AB01);浙江省自然科学基金资助项目;The Natural Science Foundation of Zhejiang Provincial of China(LY20F010016)
- DOI：10.11959/j.issn.1000-0801.2021124
  中图分类号： TP393
- 网络出版日期：2021-07，
  
  纸质出版日期：2021-07-20
- 稿件说明：
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刘再生, 倪霏, 李荣鹏, 等. 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.

Zaisheng LIU, Fei NI, Rongpeng LI, et al. Persistent homology based topological analysis on the gestalt patterns during human brain cognition process[J]. Telecommunications science, 2021, 37(7): 77-85.
刘再生, 倪霏, 李荣鹏, 等. 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. DOI： 10.11959/j.issn.1000-0801.2021124.

Zaisheng LIU, Fei NI, Rongpeng LI, et al. Persistent homology based topological analysis on the gestalt patterns during human brain cognition process[J]. Telecommunications science, 2021, 37(7): 77-85. DOI： 10.11959/j.issn.1000-0801.2021124.

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。

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.

关键词

Keywords

references

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