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A review of visual sustained attention: neural mechanisms and computational models

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成果类型:
期刊论文
作者:
Huang, Huimin;Li, Rui;Zhang, Junsong
通讯作者:
Zhang, JS
作者机构:
[Huang, Huimin; Li, Rui] Cent China Normal Univ, Natl Engn Res Ctr Elearning, Wuhan, Hubei, Peoples R China.
[Zhang, Junsong] Xiamen Univ, Sch Informat, Dept Artificial Intelligence, Brain Cognit & Intelligent Comp Lab, Xiamen, Fujian, Peoples R China.
通讯机构:
[Zhang, JS ] X
Xiamen Univ, Sch Informat, Dept Artificial Intelligence, Brain Cognit & Intelligent Comp Lab, Xiamen, Fujian, Peoples R China.
语种:
英文
关键词:
Computational models;Evaluation;Neural mechanisms;Neural pathways;Sustained attention
期刊:
PEERJ
ISSN:
2167-8359
年:
2023
卷:
11
页码:
e15351
基金类别:
National Nature Science Foundation of China [2022HZZX002]; Fundamental Research Funds for the Central Universities [2022-P-028]; Collaborative Innovation Platform Project for Fuzhou-Xiamen-Quanzhou National Independent Innovation Demonstration Zone [61772440]; Joint Laboratory of Xiamen University; 2022 Hulunbuir City's Special Key Project for Revitalizing City by Science and Technology; Hejia Company for Intelligent Cognitive Assessment; [CCNU20XJ015]; [62007016]
机构署名:
本校为第一机构
院系归属:
国家数字化学习工程技术研究中心
摘要:
Sustained attention is one of the basic abilities of humans to maintain concentration on relevant information while ignoring irrelevant information over extended periods. The purpose of the review is to provide insight into how to integrate neural mechanisms of sustained attention with computational models to facilitate research and application. Although many studies have assessed attention, the evaluation of humans' sustained attention is not sufficiently comprehensive. Hence, this study provides a current review on both neural mechanisms and computational models of visual sustained attention...

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