低分辨率电磁断层成像技术在脑电图脑成像中的应用研究

IF 2.8 4区 管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE Data Base for Advances in Information Systems Pub Date : 2023-02-07 DOI:10.1145/3583581.3583586
G. Tejay, Zareef A. Mohammed
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引用次数: 1

摘要

NeuroIS为信息系统研究提供了新的机遇。常用的神经科学技术包括使用功能磁共振成像(fMRI)设备进行脑成像或使用脑电图(EEG)进行事件相关电位时域研究。脑电图的批评者认为脑电图的空间分辨率差是脑电图在脑图研究中不足的理由。然而,低分辨率电磁断层扫描(LORETA)技术提供了强大的估计参数,允许脑电图进行脑映射。本文介绍了EEG(较少通道数)和LORETA技术作为探索性调查的有效方法,特别是当研究人员受到资源缺乏的限制时(特别是在显著降低成本的情况下)。我们证明脑电图使用sLORETA相对于fMRI的有效性,作为研究IS现象的概念验证方法。这些研究的结果可以作为使用更复杂的神经科学设备进行进一步分析的初步步骤。这可以利用高时间和空间分辨率降低神经活动的估计误差,增强神经活动与特定任务之间的关联基础,从而加强IS研究。我们还提出了一套在IS研究中使用LORETA系列技术的指导方针。
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Examining the Low- Resolution Electromagnetic Tomography Technique for EEG Brain Mapping
NeuroIS presents a new opportunity for information systems research. Often used neuroscience techniques include brain mapping with the functional magnetic resonance imaging (fMRI) device or eventrelated potential time-domain studies with the electroencephalogram (EEG). The critics of EEG consider the poor spatial resolution as justification for EEG's inadequacy to brain mapping studies. However, the low-resolution electromagnetic tomography (LORETA) technique provides strong estimation parameters allowing EEG to perform brain mapping. This paper presents EEG (with lower number of channels) and LORETA techniques as an effective approach for exploratory investigation specially when researchers are constrained with lack of resources (specially at significantly lower costs). We demonstrate the effectiveness of EEG using sLORETA with respect to fMRI as proof-of-concept approach to study IS phenomenon. The results of such studies can serve as a preliminary step for further analysis with the use of more sophisticated neuroscience devices. This can enhance IS research by taking advantage of both high temporal and spatial resolution leading to reduced estimation errors of neural activity and stronger basis for correlating neural activity and specific tasks. We also present a set of guidelines for using the LORETA family of techniques in IS research.
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来源期刊
Data Base for Advances in Information Systems
Data Base for Advances in Information Systems INFORMATION SCIENCE & LIBRARY SCIENCE-
CiteScore
3.60
自引率
7.10%
发文量
18
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