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Automatic detection advantage of network information among Internet addicts: behavioral and ERP evidence
Converging evidence has proved the attentional bias of Internet addicts (IAs) on network information. However, previous studies have neither explained how characteristics of network information are detected by IAs with priority nor proved whether this advantage is in line with the unconscious and au...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5997741/ https://www.ncbi.nlm.nih.gov/pubmed/29895830 http://dx.doi.org/10.1038/s41598-018-25442-4 |
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author | He, Jinbo Zheng, Yang Nie, Yufeng Zhou, Zongkui |
author_facet | He, Jinbo Zheng, Yang Nie, Yufeng Zhou, Zongkui |
author_sort | He, Jinbo |
collection | PubMed |
description | Converging evidence has proved the attentional bias of Internet addicts (IAs) on network information. However, previous studies have neither explained how characteristics of network information are detected by IAs with priority nor proved whether this advantage is in line with the unconscious and automatic process. To answer the two questions, this study aims to investigate whether IAs prioritize automatic detection of network information from the behavior and cognitive neuroscience aspects. 15 severe IAs and 15 matching healthy controls were selected using Internet Addiction Test (IAT). Dot-probe task with mask was used in the behavioral experiment, while deviant-standard reverse oddball paradigm was used in the event-related potential (ERP) experiment to induce mismatch negativity (MMN). In the dot-probe task, when the probe location appeared on the Internet-related picture’s position, the IAs had significantly shorter reaction time than do the controls; in the ERP experiment, when Internet-related picture appeared, MMN was significantly induced in the IAs relative to the controls. Both experiments show that IAs can automatically detect network information. |
format | Online Article Text |
id | pubmed-5997741 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-59977412018-06-21 Automatic detection advantage of network information among Internet addicts: behavioral and ERP evidence He, Jinbo Zheng, Yang Nie, Yufeng Zhou, Zongkui Sci Rep Article Converging evidence has proved the attentional bias of Internet addicts (IAs) on network information. However, previous studies have neither explained how characteristics of network information are detected by IAs with priority nor proved whether this advantage is in line with the unconscious and automatic process. To answer the two questions, this study aims to investigate whether IAs prioritize automatic detection of network information from the behavior and cognitive neuroscience aspects. 15 severe IAs and 15 matching healthy controls were selected using Internet Addiction Test (IAT). Dot-probe task with mask was used in the behavioral experiment, while deviant-standard reverse oddball paradigm was used in the event-related potential (ERP) experiment to induce mismatch negativity (MMN). In the dot-probe task, when the probe location appeared on the Internet-related picture’s position, the IAs had significantly shorter reaction time than do the controls; in the ERP experiment, when Internet-related picture appeared, MMN was significantly induced in the IAs relative to the controls. Both experiments show that IAs can automatically detect network information. Nature Publishing Group UK 2018-06-12 /pmc/articles/PMC5997741/ /pubmed/29895830 http://dx.doi.org/10.1038/s41598-018-25442-4 Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article He, Jinbo Zheng, Yang Nie, Yufeng Zhou, Zongkui Automatic detection advantage of network information among Internet addicts: behavioral and ERP evidence |
title | Automatic detection advantage of network information among Internet addicts: behavioral and ERP evidence |
title_full | Automatic detection advantage of network information among Internet addicts: behavioral and ERP evidence |
title_fullStr | Automatic detection advantage of network information among Internet addicts: behavioral and ERP evidence |
title_full_unstemmed | Automatic detection advantage of network information among Internet addicts: behavioral and ERP evidence |
title_short | Automatic detection advantage of network information among Internet addicts: behavioral and ERP evidence |
title_sort | automatic detection advantage of network information among internet addicts: behavioral and erp evidence |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5997741/ https://www.ncbi.nlm.nih.gov/pubmed/29895830 http://dx.doi.org/10.1038/s41598-018-25442-4 |
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