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A Novel Method Based on ERP and Brain Graph for the Simultaneous Assessment of Various Types of Attention
Assessment of attention is of great importance as one of human cognitive abilities. Although neuropsychological tests have been developed and used to evaluate the ability to pay attention, their validity and reliability have been reduced due to some limitations such as the presence of intervention f...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9536935/ https://www.ncbi.nlm.nih.gov/pubmed/36210993 http://dx.doi.org/10.1155/2022/6318916 |
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author | Jami, Ali Esmaili Khalilzadeh, Mohammad Ali Ghoshuni, Majid Khalilzadeh, Mohammad Mahdi |
author_facet | Jami, Ali Esmaili Khalilzadeh, Mohammad Ali Ghoshuni, Majid Khalilzadeh, Mohammad Mahdi |
author_sort | Jami, Ali Esmaili |
collection | PubMed |
description | Assessment of attention is of great importance as one of human cognitive abilities. Although neuropsychological tests have been developed and used to evaluate the ability to pay attention, their validity and reliability have been reduced due to some limitations such as the presence of intervention factors, including human factors, limited range of languages, and cultural influences. Therefore, direct outputs of the brain system, represented by event-related potentials (ERPs), and the analysis of its function in cognitive activities have become very important as a complementary tool to assess various types of attention. This research tries to assess 4 types of attention including sustained, alternative, selective, and divided, using an integrated visual-auditory test and brain signals simultaneously. Thus, the electroencephalogram (EEG) data were recorded using 19 channels, and the integrated visual and auditory (IVA-AE) test was simultaneously performed on twenty-eight healthy volunteers including 22 male and 6 female subjects with the average age of 27 ± 5.3 years. Then ERPs related to auditory and visual stimuli with synchronous averaging technique were extracted. A topographic brain mapping (topo-map) was plotted for each frame of stimulation. Next, an optical flow method was implemented on different topo-maps to obtain motion vectors from one map to another. After obtaining the overall brain graph of an individual, some features were extracted and used as measures of local and global connectivity. The extracted features were consequently evaluated along with the parameters of the IVA test by support vector machine regression (SVM-R). The volume of attention was then quantified by combining the IVA parameters. Ultimately, estimation accuracy of each type of attention including focused attention (86.1%), sustained attention (83.4%), selective attention (80.9%), and divided attention (79.9%) was obtained. According to the present study, there is a significant relationship between response control and attention indicators of the IVA test as well as ERP brain signals. |
format | Online Article Text |
id | pubmed-9536935 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-95369352022-10-07 A Novel Method Based on ERP and Brain Graph for the Simultaneous Assessment of Various Types of Attention Jami, Ali Esmaili Khalilzadeh, Mohammad Ali Ghoshuni, Majid Khalilzadeh, Mohammad Mahdi Comput Intell Neurosci Research Article Assessment of attention is of great importance as one of human cognitive abilities. Although neuropsychological tests have been developed and used to evaluate the ability to pay attention, their validity and reliability have been reduced due to some limitations such as the presence of intervention factors, including human factors, limited range of languages, and cultural influences. Therefore, direct outputs of the brain system, represented by event-related potentials (ERPs), and the analysis of its function in cognitive activities have become very important as a complementary tool to assess various types of attention. This research tries to assess 4 types of attention including sustained, alternative, selective, and divided, using an integrated visual-auditory test and brain signals simultaneously. Thus, the electroencephalogram (EEG) data were recorded using 19 channels, and the integrated visual and auditory (IVA-AE) test was simultaneously performed on twenty-eight healthy volunteers including 22 male and 6 female subjects with the average age of 27 ± 5.3 years. Then ERPs related to auditory and visual stimuli with synchronous averaging technique were extracted. A topographic brain mapping (topo-map) was plotted for each frame of stimulation. Next, an optical flow method was implemented on different topo-maps to obtain motion vectors from one map to another. After obtaining the overall brain graph of an individual, some features were extracted and used as measures of local and global connectivity. The extracted features were consequently evaluated along with the parameters of the IVA test by support vector machine regression (SVM-R). The volume of attention was then quantified by combining the IVA parameters. Ultimately, estimation accuracy of each type of attention including focused attention (86.1%), sustained attention (83.4%), selective attention (80.9%), and divided attention (79.9%) was obtained. According to the present study, there is a significant relationship between response control and attention indicators of the IVA test as well as ERP brain signals. Hindawi 2022-09-29 /pmc/articles/PMC9536935/ /pubmed/36210993 http://dx.doi.org/10.1155/2022/6318916 Text en Copyright © 2022 Ali Esmaili Jami 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 Jami, Ali Esmaili Khalilzadeh, Mohammad Ali Ghoshuni, Majid Khalilzadeh, Mohammad Mahdi A Novel Method Based on ERP and Brain Graph for the Simultaneous Assessment of Various Types of Attention |
title | A Novel Method Based on ERP and Brain Graph for the Simultaneous Assessment of Various Types of Attention |
title_full | A Novel Method Based on ERP and Brain Graph for the Simultaneous Assessment of Various Types of Attention |
title_fullStr | A Novel Method Based on ERP and Brain Graph for the Simultaneous Assessment of Various Types of Attention |
title_full_unstemmed | A Novel Method Based on ERP and Brain Graph for the Simultaneous Assessment of Various Types of Attention |
title_short | A Novel Method Based on ERP and Brain Graph for the Simultaneous Assessment of Various Types of Attention |
title_sort | novel method based on erp and brain graph for the simultaneous assessment of various types of attention |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9536935/ https://www.ncbi.nlm.nih.gov/pubmed/36210993 http://dx.doi.org/10.1155/2022/6318916 |
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