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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...

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Autores principales: He, Jinbo, Zheng, Yang, Nie, Yufeng, Zhou, Zongkui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
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.
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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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