任务前静息脑电图α信息对情境意识的神经机制影响:一种功能连接方法

IF 2.2 3区 工程技术 Q3 ENGINEERING, MANUFACTURING
Ardaman Kaur, R. Chaujar, Vijayakumar Chinnadurai
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引用次数: 11

摘要

目的研究任务前静息神经机制对情境意识任务的影响。任务前脑电图(EEG)信息和Stroop效应分别对任务参与产生影响。然而,任务前静息绝对α (PRAA)和任务前静息α额叶不对称(PRAFA)影响Stroop效应的SA-task的神经机制尚不清楚。方法对18名健康人进行任务前静息脑电测量,并在任务时进行功能磁共振成像(fMRI)采集。为了了解任务前α信息和Stroop效应对SA的影响,我们评估了平均反应时间、SA指数、PRAA和PRAFA之间的显著相关性。此外,通过脑电图信息的fMRI方法分析了PRAA、PRAFA在sa任务中的神经基础和功能连接。结果反应时间与SA指数(Pearson: r = 0.50, pcorr = 0.05)和PRAFA (Pearson: r = 0.63;Pcorr = .01)。同样,SA指数与PRAFA显著相关(Pearson: r = 0.56, pcorr = 0.01;Spearman: r = .61, pcorr = .007)和PRAA (Pearson: r = .59, pcorr = .005;Spearman: r = 0.59, pcorr = 0.002)。sa任务的神经基础揭示了涉及视觉处理和高阶认知的区域。PRAA主要在额颞叶区得到支持,并在功能上与与情绪调节有关的sa任务区域相连。PRAFA与大脑边缘和顶叶区域相关,这些区域参与了sa任务的视觉、情绪和记忆信息的整合。结论反应时间与sa任务和PRAFA有较强的相关性,并支持PRAFA、PRAA及其相关神经机制显著影响sa任务结果的假设。研究任务前静息信息对认知能力任务的影响有助于提高认知能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Effects of Neural Mechanisms of Pretask Resting EEG Alpha Information on Situational Awareness: A Functional Connectivity Approach
Objective In this study, the influence of pretask resting neural mechanisms on situational awareness (SA)-task is studied. Background Pretask electroencephalography (EEG) information and Stroop effect are known to influence task engagement independently. However, neural mechanisms of pretask resting absolute alpha (PRAA) and pretask resting alpha frontal asymmetry (PRAFA) in influencing SA-task which is undergoing Stroop effect is still not understood. Method The study involved pretask resting EEG measurements from 18 healthy individuals followed by functional magnetic resonance imaging (fMRI) acquisition during SA-task. To understand the effect of pretask alpha information and Stroop effect on SA, a robust correlation between mean reaction time, SA Index, PRAA, and PRAFA were assessed. Furthermore, neural underpinnings of PRAA, PRAFA in SA-task, and functional connectivity were analyzed through the EEG-informed fMRI approach. Results Significant robust correlation of reaction time was observed with SA Index (Pearson: r = .50, pcorr = .05) and PRAFA (Pearson: r = .63; pcorr = .01), respectively. Similarly, SA Index significantly correlated with PRAFA (Pearson: r = .56, pcorr = .01; Spearman: r = .61, pcorr = .007), and PRAA (Pearson: r = .59, pcorr = .005; Spearman: r = .59, pcorr = .002). Neural underpinnings of SA-task revealed regions involved in visual-processing and higher-order cognition. PRAA was primarily underpinned at frontal-temporal areas and functionally connected to SA-task regions pertaining to the emotional regulation. PRAFA has correlated with limbic and parietal regions, which are involved in integration of visual, emotion, and memory information of SA-task. Conclusion The results suggest a strong association of reaction time with SA-task and PRAFA and strongly support the hypothesis that PRAFA, PRAA, and associated neural mechanisms significantly influence the outcome of SA-task. Application It is beneficial to study the effect of pretask resting information on SA-task to improve SA.
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来源期刊
CiteScore
5.20
自引率
8.30%
发文量
37
审稿时长
6.0 months
期刊介绍: The purpose of Human Factors and Ergonomics in Manufacturing & Service Industries is to facilitate discovery, integration, and application of scientific knowledge about human aspects of manufacturing, and to provide a forum for worldwide dissemination of such knowledge for its application and benefit to manufacturing industries. The journal covers a broad spectrum of ergonomics and human factors issues with a focus on the design, operation and management of contemporary manufacturing systems, both in the shop floor and office environments, in the quest for manufacturing agility, i.e. enhancement and integration of human skills with hardware performance for improved market competitiveness, management of change, product and process quality, and human-system reliability. The inter- and cross-disciplinary nature of the journal allows for a wide scope of issues relevant to manufacturing system design and engineering, human resource management, social, organizational, safety, and health issues. Examples of specific subject areas of interest include: implementation of advanced manufacturing technology, human aspects of computer-aided design and engineering, work design, compensation and appraisal, selection training and education, labor-management relations, agile manufacturing and virtual companies, human factors in total quality management, prevention of work-related musculoskeletal disorders, ergonomics of workplace, equipment and tool design, ergonomics programs, guides and standards for industry, automation safety and robot systems, human skills development and knowledge enhancing technologies, reliability, and safety and worker health issues.
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