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Persistent Homology-Based Topological Analysis on the Gestalt Patterns during Human Brain Cognition Process
The neuropsychological characteristics inside the brain are still not sufficiently understood in previous Gestalt psychological analyses. In particular, the extraction and analysis of human brain consciousness information itself have not received enough attention for the time being. In this paper, w...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8575602/ https://www.ncbi.nlm.nih.gov/pubmed/34760139 http://dx.doi.org/10.1155/2021/2334332 |
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author | Liu, Zaisheng Ni, Fei Li, Rongpeng Zhang, Honggang Liu, Chang Zhang, Jiefang Xie, Songyun |
author_facet | Liu, Zaisheng Ni, Fei Li, Rongpeng Zhang, Honggang Liu, Chang Zhang, Jiefang Xie, Songyun |
author_sort | Liu, Zaisheng |
collection | PubMed |
description | The neuropsychological characteristics inside the brain are still not sufficiently understood in previous Gestalt psychological analyses. In particular, the extraction and analysis of human brain consciousness information itself have not received enough attention for the time being. In this paper, we aim to investigate the features of EEG signals from different conscious thoughts. Specifically, we try to extract the physiologically meaningful features of the brain responding to different contours and shapes 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 are 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) is significantly different from that evoked by the ordered Gestalt (GST) images in several frequency bands, which indicate that the human cognition of the shape and contour of images can be separated to some extent through topological analysis. This implies the feasibility to digitize the neural signals while preserving the whole and local features of the original signals, which are further verified by our extensive experiments. In general, this paper evaluates and quantifies cognitively related neural correlates by persistent homology features of EEG signals, which provides an approach to realizing the digitization of neural signals. Preliminary verification of the analyzability of human consciousness signals provides reliable research ideas and directions for the realization of feature extraction and analysis of human brain consciousness cognition. |
format | Online Article Text |
id | pubmed-8575602 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-85756022021-11-09 Persistent Homology-Based Topological Analysis on the Gestalt Patterns during Human Brain Cognition Process Liu, Zaisheng Ni, Fei Li, Rongpeng Zhang, Honggang Liu, Chang Zhang, Jiefang Xie, Songyun J Healthc Eng Research Article The neuropsychological characteristics inside the brain are still not sufficiently understood in previous Gestalt psychological analyses. In particular, the extraction and analysis of human brain consciousness information itself have not received enough attention for the time being. In this paper, we aim to investigate the features of EEG signals from different conscious thoughts. Specifically, we try to extract the physiologically meaningful features of the brain responding to different contours and shapes 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 are 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) is significantly different from that evoked by the ordered Gestalt (GST) images in several frequency bands, which indicate that the human cognition of the shape and contour of images can be separated to some extent through topological analysis. This implies the feasibility to digitize the neural signals while preserving the whole and local features of the original signals, which are further verified by our extensive experiments. In general, this paper evaluates and quantifies cognitively related neural correlates by persistent homology features of EEG signals, which provides an approach to realizing the digitization of neural signals. Preliminary verification of the analyzability of human consciousness signals provides reliable research ideas and directions for the realization of feature extraction and analysis of human brain consciousness cognition. Hindawi 2021-11-01 /pmc/articles/PMC8575602/ /pubmed/34760139 http://dx.doi.org/10.1155/2021/2334332 Text en Copyright © 2021 Zaisheng Liu et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Liu, Zaisheng Ni, Fei Li, Rongpeng Zhang, Honggang Liu, Chang Zhang, Jiefang Xie, Songyun Persistent Homology-Based Topological Analysis on the Gestalt Patterns during Human Brain Cognition Process |
title | Persistent Homology-Based Topological Analysis on the Gestalt Patterns during Human Brain Cognition Process |
title_full | Persistent Homology-Based Topological Analysis on the Gestalt Patterns during Human Brain Cognition Process |
title_fullStr | Persistent Homology-Based Topological Analysis on the Gestalt Patterns during Human Brain Cognition Process |
title_full_unstemmed | Persistent Homology-Based Topological Analysis on the Gestalt Patterns during Human Brain Cognition Process |
title_short | Persistent Homology-Based Topological Analysis on the Gestalt Patterns during Human Brain Cognition Process |
title_sort | persistent homology-based topological analysis on the gestalt patterns during human brain cognition process |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8575602/ https://www.ncbi.nlm.nih.gov/pubmed/34760139 http://dx.doi.org/10.1155/2021/2334332 |
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