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A New Method for Computing Attention Network Scores and Relationships between Attention Networks

The attention network test (ANT) is a reliable tool to detect the efficiency of alerting, orienting, and executive control networks. However, studies using the ANT obtained inconsistent relationships between attention networks due to two reasons: on the one hand, the inter-network relationships of a...

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Autores principales: Wang, Yi-Feng, Cui, Qian, Liu, Feng, Huo, Ya-Jun, Lu, Feng-Mei, Chen, Heng, Chen, Hua-Fu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3940671/
https://www.ncbi.nlm.nih.gov/pubmed/24594693
http://dx.doi.org/10.1371/journal.pone.0089733
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author Wang, Yi-Feng
Cui, Qian
Liu, Feng
Huo, Ya-Jun
Lu, Feng-Mei
Chen, Heng
Chen, Hua-Fu
author_facet Wang, Yi-Feng
Cui, Qian
Liu, Feng
Huo, Ya-Jun
Lu, Feng-Mei
Chen, Heng
Chen, Hua-Fu
author_sort Wang, Yi-Feng
collection PubMed
description The attention network test (ANT) is a reliable tool to detect the efficiency of alerting, orienting, and executive control networks. However, studies using the ANT obtained inconsistent relationships between attention networks due to two reasons: on the one hand, the inter-network relationships of attention subsystems were far from clear; on the other hand, ANT scores in previous studies were disturbed by possible inter-network interactions. Here we proposed a new computing method by dissecting cue-target conditions to estimate ANT scores and relationships between attention networks as pure as possible. The method was tested in 36 participants. Comparing to the original method, the new method showed a larger alerting score and a smaller executive control score, and revealed interactions between alerting and executive control and between orienting and executive control. More interestingly, the new method revealed unidirectional influences from alerting to executive control and from executive control to orienting. These findings provided useful information for better understanding attention networks and their relationships in the ANT. Finally, the relationships of attention networks should be considered with more experimental paradigms and techniques.
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spelling pubmed-39406712014-03-06 A New Method for Computing Attention Network Scores and Relationships between Attention Networks Wang, Yi-Feng Cui, Qian Liu, Feng Huo, Ya-Jun Lu, Feng-Mei Chen, Heng Chen, Hua-Fu PLoS One Research Article The attention network test (ANT) is a reliable tool to detect the efficiency of alerting, orienting, and executive control networks. However, studies using the ANT obtained inconsistent relationships between attention networks due to two reasons: on the one hand, the inter-network relationships of attention subsystems were far from clear; on the other hand, ANT scores in previous studies were disturbed by possible inter-network interactions. Here we proposed a new computing method by dissecting cue-target conditions to estimate ANT scores and relationships between attention networks as pure as possible. The method was tested in 36 participants. Comparing to the original method, the new method showed a larger alerting score and a smaller executive control score, and revealed interactions between alerting and executive control and between orienting and executive control. More interestingly, the new method revealed unidirectional influences from alerting to executive control and from executive control to orienting. These findings provided useful information for better understanding attention networks and their relationships in the ANT. Finally, the relationships of attention networks should be considered with more experimental paradigms and techniques. Public Library of Science 2014-03-03 /pmc/articles/PMC3940671/ /pubmed/24594693 http://dx.doi.org/10.1371/journal.pone.0089733 Text en © 2014 Wang et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Wang, Yi-Feng
Cui, Qian
Liu, Feng
Huo, Ya-Jun
Lu, Feng-Mei
Chen, Heng
Chen, Hua-Fu
A New Method for Computing Attention Network Scores and Relationships between Attention Networks
title A New Method for Computing Attention Network Scores and Relationships between Attention Networks
title_full A New Method for Computing Attention Network Scores and Relationships between Attention Networks
title_fullStr A New Method for Computing Attention Network Scores and Relationships between Attention Networks
title_full_unstemmed A New Method for Computing Attention Network Scores and Relationships between Attention Networks
title_short A New Method for Computing Attention Network Scores and Relationships between Attention Networks
title_sort new method for computing attention network scores and relationships between attention networks
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3940671/
https://www.ncbi.nlm.nih.gov/pubmed/24594693
http://dx.doi.org/10.1371/journal.pone.0089733
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