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Neuroscience
事件相关电位 (ERPs) 和其他基于脑电图的提取大脑功能障碍生物标志物的方法:从小儿注意力缺陷/多动障...
事件相关电位 (ERPs) 和其他基于脑电图的提取大脑功能障碍生物标志物的方法:从小儿注意力缺陷/多动障...
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JoVE Journal Neuroscience
Event Related Potentials (ERPs) and other EEG Based Methods for Extracting Biomarkers of Brain Dysfunction: Examples from Pediatric Attention Deficit/Hyperactivity Disorder (ADHD)

事件相关电位 (ERPs) 和其他基于脑电图的提取大脑功能障碍生物标志物的方法:从小儿注意力缺陷/多动障碍 (ADHD) 中的例子

Full Text
16,872 Views
10:02 min
March 12, 2020

DOI: 10.3791/60710-v

Geir Ogrim1,2,3, Juri D. Kropotov4,5

1Neuropsychiatric Team, Åsebråten Outpatient Clinic,Østfold Hospital Trust, 2Institute of Psychology,Norwegian University of Science and Technology, 3Gillberg Neuropsychiatry Centre,University of Gothenburg, 4P. Bechtereva Institute of the Human Brain,Russian Academy of Sciences, 5Department of Neuropsychology,Andrzej Frycz-Modrzewski Krakow University

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Please note that some of the translations on this page are AI generated. Click here for the English version.

Overview

This study focuses on the application of EEG methods to extract biomarkers related to brain dysfunctions, emphasizing multi-channel event-related potentials (ERPs) collected during a cued GO/NOGO task. Non-brain artifacts are corrected, and ERPs are compared to normative databases, with particular examples illustrating potential biomarkers for ADHD diagnosis and prediction of medication response.

Key Study Components

Area of Science

  • Neuroscience
  • Electrophysiology
  • Psychology

Background

  • Event-related potentials (ERPs) provide insights into brain function.
  • EEG is a noninvasive and affordable technique.
  • Technique relates well to existing scientific studies on brain dysfunction.
  • Focus on specific ERPs associated with cognitive tasks.

Purpose of Study

  • To assess brain function through EEG spectra and ERPs.
  • To identify biomarkers for ADHD diagnosis.
  • To predict responses to medication based on brain activity.

Methods Used

  • EEG monitoring is performed during a GO/NOGO task.
  • The study employs a structured procedure for electrode placement and data acquisition.
  • Independent component analysis is used to correct for artifacts like eye movements.
  • EEG data is analyzed and compared with normative databases to identify significant deviations.

Main Results

  • Demonstration of ERP measurement techniques and their relevance to understanding ADHD.
  • Identification of significant deviations in brain activity patterns compared to normative data.
  • Potential link established between ERP features and clinical diagnosis/medication response.

Conclusions

  • This study demonstrates a methodology for utilizing EEG to derive biomarkers for brain dysfunctions.
  • It aids in understanding the neural correlates of ADHD and the potential for personalized treatment strategies.
  • Findings contribute to the broader understanding of neuronal mechanisms related to cognitive control.

Frequently Asked Questions

What are the advantages of using EEG for this study?
EEG is noninvasive and affordable, allowing for repeated measures and broad applicability in research settings.
How is the GO/NOGO task implemented in this study?
Subjects are trained to respond to specific animal image pairs while ignoring distractors, which helps in studying cognitive control.
What types of data are obtained from ERP analysis?
Data includes information on omission and commission errors, mean reaction times, and variability in responses related to the cognitive task.
How can this methodology be adapted for other studies?
The EEG setup and analysis techniques can be modified to fit various cognitive tasks or clinical populations based on the research need.
What limitations should be considered when interpreting EEG results?
Factors such as individual differences in anatomy and the influence of artifacts must be accounted for to ensure accurate data interpretation.

脑电图方法用于提取脑功能障碍的生物标志物。重点是在 CUed GO/NOGO 任务中记录的多通道事件相关电位 (ERP)。非脑伪影得到纠正,ERP与规范数据进行比较。示例涉及多动症诊断和药物反应预测的生物标志物。

将脑电图光谱和事件相关电位(ERPS)与数据库进行比较,可以提供有关大脑功能的重要信息。这些技术的优点是,它们是无创的,负担得起的,可以与大量的科学研究有关。展示这些技术的将是玛丽亚·丹尼尔森,一位心理学候选人,她在我们的诊所当了两年的技术员。

若要创建相应的 EEG 数据文件,请在软件中单击"文件"和"新"。主体的卡片将显示在屏幕上。填写所有适当信息后,测量主体头部的鼻位距离。

前极电极的中心应落在水平线上,距离在鼻孔上方 10% 。将皮肤准备凝胶涂抹在耳垂上,用导电电极凝胶填充耳电极杯。连接耳电极,将盖子对称地放在头部,前极电极放置在前极的中心。

尽可能向下拉盖,将其固定在头部附近,并将腰带放在胸前。将连接到盖的按钮固定到此频带,以防止盖和电极在测试期间移动,并连接盖电缆和耳缆到放大器。接下来,单击阻抗图标的 WinEEG 菜单控制,用凝胶填充注射器。

使用注射器填充所有电极孔。当黑圆圈为黄色时,阻抗正常。当所有 20 个孔的颜色为黄色且各个孔之间的颜色差异较小时,设备已准备就绪。

设备正确放置后,单击启动按钮以启动 EEG 监控,并通知主体测试需要大约一个小时。请对象在舒适的椅子上闭着眼睛放松,然后单击红色圆圈获取 EEG。单击"下一步"后,选择闭眼以开始注册。

三分钟后,点击暂停,并要求主题睁开眼睛,同时放松,看着屏幕在他们面前。然后单击红色圆圈以继续注册。再过三分钟,单击"停止"并保存。

在开始 EEG 录制之前,让主体在右手上按住按钮开关并打开任务菜单。在主题前面的辅助计算机上选择 VCPT。告知主体图片将成对显示,第一张图片后跟第二张照片,一秒后,三秒钟后,将按相同的模式出现一对新图片。

每次出现两个动物完全相同的 AA 组合时,指示主体尽快单击鼠标按钮。指示主题不要按 AP、PP 或 AH 组合上的鼠标按钮。告诉主题忽略 PH 组合中的随机声音。

传递说明后,按 Enter 运行任务约两到五分钟,以训练任务执行 go/nogo 任务。在训练任务结束时,选择切换到从属模式选项。要开始实验,请从主计算机上的录制菜单中选择 EEG 采集选项。

在录制菜单上,选择刺激演示程序。刺激显示程序选项将突出显示。选择 VCPT 并在辅助计算机上启动刺激演示文稿。

完成所有 400 个试用后,在结束注册之前推送暂停、停止和保存。要从数据中删除眼动伪影,请左键单击片段开头的时间栏以选择感兴趣的 EEG 片段,右键单击片段末尾的时间栏。整个片段将突出显示为黄色。

要与 HBI 参考数据库比较单个光谱和事件相关电位,请选择独立的分量分析方法,并选择与眼动和水平眼动相关的地形图。然后单击"确定"以接受选择,并实现分析菜单中的标记工件过程。要计算 EEG 光谱,请在分析菜单中选择闭眼或睁开眼睛,以选择感兴趣的 EEG 光谱和片段,然后单击"确定"。然后在分析菜单中,选择比较以比较单个光谱与数据库。

要计算与事件相关的潜在电位,请在常见蒙太奇中选择 EEG VCPT 文件,然后从分析菜单中单击计算 ERP。单击"确定"。将显示一个窗口,描述 ERP 计算的参数。从图形上方的四个小窗口中,选择一个窗口、二个窗口、三个窗口和四个窗口中感兴趣的组件,另一个窗口中的"无"选项。

在右侧垂直菜单中,选择感兴趣的时间间隔。要绘制与事件相关的电位波图,请沿任何图形的 x 轴在所选时间右键单击。然后释放并选择"添加地图"。

相应的地图将显示在页面底部。要查看遗漏、佣金、a-a GO 的均次反应时间以及实时可变性,请在事件相关潜在窗口右键单击并选择组信息。A-a GO 线显示遗漏错误、反应时间和反应时间变异数。

a-p NoGO 行显示佣金错误数。在分析中,选择比较。然后在右侧窗口中选择主体的文件和比较文件,然后单击"确定"。要将事件相关电位与参考数据库进行比较,请从分析菜单中选择结果比较,然后选择主体的文件和 HBI 数据库。

然后右键单击时间点和感兴趣通道,获取偏差与参考的显著性水平。要选择用于评估事件相关电位差异的组,请单击箭头。有关引用事件相关电位,请单击两个。

要查看差异,请单击三。对于活动组四,选择"无"。要定义兴趣的时间间隔,请输入从 的时间间隔和持续时间(以毫秒为单位)。

然后将光标定位在时间点和感兴趣通道的位置,右键单击以选择"添加"地图。将显示显示与引用偏离的地图。可以选择其他文件而不是 HBI 数据库进行比较。

在这里,在代表性的多动症组中,主动认知控制功能障碍的事件相关潜在相关相关。与本分析中的健康对照组相比,ADHD组的主动认知控制的两个指标都降低了。在这个图中,可以观察到多动症组反应性认知控制功能障碍的事件相关潜在相关。

与健康对照组相比,多动症受试者的两个反应性认知控制指标也降低了。要获得高质量的注册,请尽可能减少肌肉和运动伪影。任务和 WinEEG 计算机之间的安全连接至关重要。

虽然这些方法是生成假说的总临床检查的一部分,但它们不能取代临床访谈、医学检查、神经心理学测试或观察等方法。

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