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Neuroscience
利用磁脑学检测刺激前源级对物体感知的影响
利用磁脑学检测刺激前源级对物体感知的影响
JoVE Journal
Neuroscience
This content is Free Access.
JoVE Journal Neuroscience
Detecting Pre-Stimulus Source-Level Effects on Object Perception with Magnetoencephalography

利用磁脑学检测刺激前源级对物体感知的影响

Full Text
7,392 Views
09:25 min
July 26, 2019

DOI: 10.3791/60120-v

Elie Rassi1, Marco Fuscà1, Nathan Weisz1, Gianpaolo Demarchi1

1Center for Cognitive Neuroscience,Paris-Lodron Universität Salzburg

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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 article describes an experimental setup to detect pre-stimulus influences on object perception using magnetoencephalography (MEG). It details the methodology for stimulus material, experimental design, and data analysis to investigate brain connectivity changes before viewing objects.

Key Study Components

Area of Science

  • Neuroscience
  • Electrophysiology
  • Cognitive psychology

Background

  • MEG allows for the measurement of brain activity with high spatial resolution.
  • The influence of pre-stimulus brain connectivity on perception is poorly understood.
  • Understanding these processes can illuminate cognitive functions and neural mechanisms.

Purpose of Study

  • To assess the impact of transient connectivity changes on object perception.
  • To employ MEG for capturing source-level neural dynamics.
  • To develop a robust experimental protocol for MEG studies.

Methods Used

  • MEG was used to record brain activity while participants viewed visual stimuli.
  • Participants completed a series of trials involving face and vase recognition.
  • Data collection included resting-state measurements and task performance analytics.
  • Signal processing involved time-frequency analysis and connectivity assessments.
  • Detailed preparation and consent processes for participant safety were conducted.

Main Results

  • The experiment showed how pre-stimulus connectivity influences perceptual outcomes.
  • Data analysis revealed relevant coherence metrics across trial types.
  • Findings contribute to understanding cognitive mechanisms underlying perception.

Conclusions

  • This study enables a deeper understanding of the neural basis of perception.
  • Implementing MEG yields valuable insights into cognitive processing times.
  • These methods may inform future studies on brain connectivity and perception.

Frequently Asked Questions

What are the advantages of using MEG?
MEG provides high spatial resolution and is unaffected by the skull or scalp, making it superior in source localization compared to EEG.
How is the experimental design implemented?
Participants undergo a screening process for exclusions, followed by a structured series of visual tasks designed to measure perceptual responses.
What types of outcomes are measured?
The study collects behavioral responses and MEG data to analyze connectivity changes that influence perception based on visual stimuli.
How can the method be adapted for other experiments?
The protocol can be tailored to investigate various perceptual and cognitive functions by varying the stimuli and tasks performed by participants.
What critical steps should be considered for participant safety?
Ensure informed consent, confirm the absence of metallic objects, and use non-magnetic clothing during the MEG recording.
What limitations does the study have?
This method requires specific technical setups and trained staff, potentially limiting accessibility in some research environments.

本文介绍如何设置一个实验,允许使用磁脑成像 (MEG) 检测刺激前源级对物体感知的影响。它涵盖了刺激材料、实验设计、MEG 记录和数据分析。

此方法允许在查看对象之前捕获大脑连接的快速和瞬态变化,以及这些变化对对象感知的影响。MEG 比 EEG 的主要优点是大脑的磁场不受头部干扰,从而实现更高分辨率的源重建和更好的连接估计。首先以一千赫的录制一分钟的空室 MEG 数据。

通过实时可视化采集计算机上的所有信号,监控来自 102 磁力计和 204 个正交放置平面梯度计的信号。这些平面梯度计位于 102 个不同位置。你不起诉我们?接下来,根据赫尔辛基的声明,获得参与者的知情同意,并让他们签署表格,其中包括一份允许处理个人数据的声明。

你的身体有金属物体吗?但是,当你在里面的时候,你也可以这样做。接下来,为他们提供非磁性的衣服,并确保他们的身体内或身上没有金属物体。

要求他们填写匿名问卷,以确保这一点,并确保他们没有任何其他排除标准,并记录细节,如手和休息水平。好的,太好了,谢谢这里。将学员放在非铁磁椅上,然后用胶粘剂将五个头部位置指示器线圈连接到头部,两只眼睛上方,另一只眼睛上方,每只耳朵后面一只。

将数字化系统的跟踪器传感器牢固地放在参与者的头上,并固定在眼镜上,实现最大的稳定性。接下来,数字化解剖地标、左右前心点和鼻塞,并确保前心点是对称的。此外,使用 3D 数字化器手写笔对五个 HPI 线圈位置进行数字化。

现在,沿头皮数字化多达 300 点,并最大化头部形状的覆盖范围。覆盖 MR 图像上头皮的明确定义区域,背面的 inion 和正面的鼻腔上方,以及鼻桥上方。这些点将用于共同注册解剖图像。

此时,使用跟踪器传感器拆下眼镜,并连接右眼上方和下方的一次性电极,以监控垂直眼部运动。还要将电极连接到右眼右侧和左眼左侧,以监测水平眼的运动。在右锁骨下方和心脏下方附加电极,以监测心率。

这些区域的信号是健壮的,因此不需要检查阻抗。此外,将电极作为颈部下方的接地。请。现在,护送参与者到MEG屏蔽室,并指示他们坐在MEG的椅子上。

将 HPI 线束和一次性电极插入 MEG 系统中。然后抬起椅子,使参与者的头碰到头盔的顶部,并确保参与者感到舒适。现在可以吗?

是的, 完美. 开始指示参与者被动地盯着空屏幕看五分钟, 同时以一千赫的小时录制休息状态的 Meg 数据。在整个实验中,将采样速率保持在千赫以下。然后指导任务要求的参与者,让他们执行 20 次练习试验。

因此,现在我们将去有一个练习课,并确保一切正常。好。好吧?首先显示说明,告诉参与者看到脸时要按哪个按钮,看到花瓶时要按哪个按钮, 开始实验。

创建包含四个事件的单个试验,这些事件将应用于此顺序中的所有试验:固定交叉、鲁宾图像、掩码和响应提示。在每个块的开头,在任务开始前,开始测量 MEG 数据并记录学员头部位置与 MEG 的初始位置。在实验过程中,请务必通过视频监控参与者。

在 MEG 系统中,单击"转到开始"。当对话框询问是否省略 HPI 数据或将 HPI 数据添加到录制中时,检查 HPI 线圈信号,然后单击"接受"以记录初始头部位置。之后,单击"原始录制"以开始录制 MEG 数据。

在每个试验开始时,显示固定十字的可变时间段为 1 到 1.8 秒。然后,显示鲁宾图像 150 毫秒。接下来,删除 Rubin 图像并显示蒙版 200 毫秒,然后是提示参与者在两秒钟内响应的问题。

计划响应时间,这样如果参与者在两秒钟内做出响应,则下一次试验开始。否则,在两秒钟后开始下一次试验。保存所有四个事件的时间以及响应选择及其时间。

通过在采集计算机上实时可视化 MEG 信号来监控 MEG 信号。实验完成后,护送学员走出屏蔽室,帮助他们分离传感器。使用此处屏幕上显示的代码,分别对两个感兴趣的区域执行时间频率分析,与两种试验类型分开分析获取的数据。

首先,根据频域中的乘法实现多点时频变换。此外,将锥度选项设置为 dps 以使用离散的 prolate 球体序列函数锥度,并定义从 8 到 13 赫兹的兴趣频率。接下来,将时间窗口的宽度设置为 200 毫秒,将平滑参数设置为 4 赫兹。

将保留试验选项设置为"是"以返回单个试验的时间频率估计值。将输出设置为四位一体,以返回复杂的 Fourier 光谱。使用此处在屏幕上看到的代码对生成的时频数据执行连接分析,使用显示的设置返回一致性的虚部。

在跨频率和参与者平均一致性光谱并绘制生成的大平均虚想象一致性值作为时间函数之前,请重复每个参与者的过程。在这里,我们看到一个示例试用结构和原始数据。试用从显示固定交叉开始。

1 到 1.8 秒后,Rubin 刺激出现 150 毫秒,然后是掩码 200 毫秒。然后出现响应屏幕,提示参与者用脸或花瓶进行响应。上图,我们看到来自示例参与者的多渠道原始数据,时间锁定到刺激启动,并在整个试验中平均。

刺激前分析窗口中的此数据将是分析的目标间隔。在这里,我们看到来自源局部的 fusiform 面部区域信号的光谱功率估计,在面部和花瓶试验。此图显示了源局部视觉皮层和面和花瓶试验中的 fusiform 面部区域信号之间的一致性的假想部分,频率范围为 8 到 13 赫兹。

阴影区域表示主体内设计的均值的标准误差。MEG 是一种被动的方法,很像电吉他的拾取。与其他机器不同,该机器还具有被参与者损坏的风险。

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