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### EEGlab 使用说明详解 #### 引言 EEGLAB是一款功能强大的开源工具箱，用于处理脑电图（EEG）数据。它基于MATLAB环境，由加利福尼亚大学圣地亚哥分校的研究团队开发。EEGLAB支持一系列的数据处理功能，包括数据加载、预处理、独立成分分析(ICA)等高级分析技术。本篇文档将详细介绍EEGLAB的基本使用方法，特别是其中的ICA去噪方法。 #### 一、在EEGLAB中分析数据 ##### 1.1 加载数据与可视化数据信息 **1.1.1 开始使用** **1.1.1.1 学习MATLAB** 在使用EEGLAB之前，建议先熟悉MATLAB的基础操作。可以通过在线教程或官方文档来学习如何使用MATLAB进行基本的数据处理和图形绘制。 **1.1.1.2 安装EEGLAB和教程文件** 确保已经安装了最新版本的MATLAB，并从EEGLAB官方网站下载并安装EEGLAB。此外，还需要下载教程数据集，这些数据集通常用于演示EEGLAB的各项功能。 **1.1.1.3 启动MATLAB和EEGLAB** 启动MATLAB后，在命令窗口中键入`eeglab`命令即可启动EEGLAB。 **1.1.2 打开现有数据集** 打开EEGLAB后，选择“File”菜单下的“Load dataset...”，然后浏览到存储有教程数据集的位置，选择其中一个数据文件打开。 **1.1.3 编辑事件值** 在EEGLAB中，可以编辑数据中的事件标记。事件标记对于数据分割以及后续分析非常重要。通过“Event/Segment”菜单下的“Edit event values”选项，可以查看和修改事件标记。 **1.1.4 关于此数据集** 了解所使用的数据集是非常重要的，这有助于理解后续分析的意义。在EEGLAB中，可以通过“Dataset”菜单下的“Show dataset information”选项来查看数据集的相关信息，如采样率、通道数量等。 **1.1.5 滚动查看数据** 使用EEGLAB提供的可视化工具可以方便地查看数据。通过“Plot”菜单下的“Continuous data”选项，可以在时间轴上滚动查看数据波形。 ##### 1.2 使用通道位置 **1.2.1 导入通道位置** 为了更好地分析数据，了解每个通道在头皮上的具体位置至关重要。可以通过“Channel”菜单下的“Set channel locations”选项导入特定的通道位置信息。 **1.2.2 获取标准化通道位置** EEGLAB提供了多种标准化的通道位置模板，可以直接选择使用。通过“Channel”菜单下的“Get standard locations”选项，可以根据不同的国际系统（如10-20系统）获取标准化的通道位置。 **1.2.3 导入测量的3-D通道位置信息** 如果使用的是自定义的电极帽或者有特殊的通道布局需求，可以通过“Channel”菜单下的“Import 3-D channel locations”选项导入具体的3-D通道位置信息。 ##### 1.3 绘制通道频谱和地图使用EEGLAB的绘图功能可以直观地显示通道的频谱特性。通过“Plot”菜单下的“Spectrum”选项，可以选择单个或多个通道绘制其频谱图。此外，还可以使用“Topographic map”选项来绘制通道的地理位置分布图。 ##### 1.4 预处理工具 **1.4.1 更改数据采样率** 根据研究需求，可能需要调整原始数据的采样率。在EEGLAB中，可以通过“Preprocessing”菜单下的“Resample data”选项实现这一点。 **1.4.2 过滤数据** 过滤是去除噪声的重要手段之一。EEGLAB提供了多种过滤器类型，例如低通、高通和带通过滤器。通过“Preprocessing”菜单下的“Filter data”选项，可以根据需要选择合适的过滤器进行数据过滤。 **1.4.3 重新参考数据** 重新参考是指改变数据的参考点。这对于某些类型的分析非常有用，因为它可以帮助减少伪迹的影响。通过“Preprocessing”菜单下的“Re-reference data”选项，可以选择新的参考点进行重新参考。 ##### 1.5 提取数据片段提取数据片段（epoch）是数据分析的关键步骤之一，它允许对特定事件相关的数据进行集中分析。 **1.5.1 提取片段** 通过“Epoch”菜单下的“Create epochs”选项，可以根据预设的时间窗口自动提取事件相关的数据片段。 **1.5.2 去除基线值** 在提取的数据片段中，去除基线值可以帮助减少噪声的影响。通过“Epoch”菜单下的“Remove baseline”选项，可以选择合适的方法去除基线值。 ##### 1.6 数据平均 **1.6.1 在单个轴上绘制ERP数据及其头皮图** 事件相关电位（ERP）是重要的分析结果之一。通过“Plot”菜单下的“ERP topographies”选项，可以同时绘制ERP数据及其对应的头皮图。 **1.6.2 在拓扑数组中绘制ERP轨迹** 通过“Plot”菜单下的“ERP topographic array”选项，可以将多个ERP轨迹按照通道的拓扑结构进行排列展示。 **1.6.3 在双列数组中绘制ERPs** 使用“Plot”菜单下的“ERP 2-column array”选项，可以将多个ERP数据以双列形式展示出来，便于对比分析。 **1.6.4 将ERP绘制为一系列头皮图** 通过“Plot”菜单下的“ERP topographies over time”选项，可以将ERP随时间变化的特征以一系列头皮图的形式展示出来。 **1.6.4.1 绘制一系列2-D ERP头皮图** 选择“Plot”菜单下的“ERP topographies over time”选项，然后选择2-D模式，可以观察ERP随时间的变化趋势。 **1.6.4.2 绘制ERP数据为一系列3-D地图** 通过“Plot”菜单下的“ERP topographies over time”选项，选择3-D模式，可以更直观地观察ERP随时间的变化趋势。 ##### 1.7 选择数据片段和绘制数据平均 **1.7.1 选择两种条件下的事件和片段** 为了比较不同条件下的ERP差异，需要先选择两种条件下的事件和数据片段。通过“Select”菜单下的“Select events”选项，可以指定选择哪些事件对应的数据片段。 **1.7.2 计算大样本ERP** 通过“Plot”菜单下的“Plot grand average”选项，可以计算并绘制多个数据片段的平均ERP。 **1.7.3 查找ERP峰值延迟** ERP峰值延迟是指ERP波形中最大值出现的时间点。通过“Tools”菜单下的“Find ERP peak latencies”选项，可以自动查找并标注出ERP峰值的时间位置。 **1.7.4 比较两种条件下ERP** 通过“Plot”菜单下的“Compare ERPs”选项，可以对比两种条件下的ERP数据，以评估不同条件之间的差异。 ##### 1.8 绘制ERP图像 **1.8.1 选择通道进行绘制** 通过“Plot”菜单下的“Plot channel selection”选项，可以选择特定的通道绘制ERP图像。 **1.8.2 使用pop_erpimage()函数绘制ERP图像** 通过调用`pop_erpimage()`函数，可以绘制ERP图像。此函数提供了一系列的参数选项，用于定制图像的表现形式。 **1.8.3 按试次排序ERP图像** 通过“Plot”菜单下的“Sort trials in ERP images”选项，可以根据不同的标准（如反应时间、刺激强度等）对ERP图像中的试次进行排序。 **1.8.4 使用光谱选项绘制ERP图像** 通过“Plot”菜单下的“Plot ERP images with spectral options”选项，可以添加光谱分析的结果到ERP图像中，以更全面地了解数据的频率特性。 **1.8.5 绘制单个试次和附加选项的光谱幅度** 通过“Plot”菜单下的“Plot spectral amplitude in single trials”选项，可以在单个试次的基础上绘制光谱幅度图。此外，还可以选择其他附加选项来进一步定制图像。 ##### 1.9 独立成分分析(ICA)的EEG数据 **1.9.1 运行ICA分解** 独立成分分析是一种用于盲源分离的技术，广泛应用于EEG数据的降噪处理。通过“Tools”菜单下的“Run ICA decomposition”选项，可以运行ICA算法对数据进行分解。 **1.9.2 绘制2-D组件头皮图** 通过“Plot”菜单下的“Plot component scalp maps”选项，可以绘制每个独立成分的头皮图，帮助识别哪些成分代表真实的脑电信号，哪些可能是噪声。 **1.9.3 绘制组件头部图** 通过“Plot”菜单下的“Plot component head plots”选项，可以绘制每个独立成分的空间分布情况，有助于更深入地理解每个成分的物理含义。 **1.9.4 研究和去除ICA组件** 通过对ICA组件的分析，可以识别哪些成分是噪声，哪些是真实的脑电信号。通过“Tools”菜单下的“Reject components”选项，可以选择去除那些代表噪声的ICA组件。 **1.9.5 从数据中减去ICA组件** 一旦确定了哪些ICA组件代表噪声，可以通过“Tools”菜单下的“Subtract components from data”选项将其从原始数据中减去，从而达到去噪的目的。 **1.9.6 在数据集中保留多个ICA权重** 有时候，可能需要保留多次ICA分解的结果。通过“Tools”菜单下的“Retain multiple ICA weights”选项，可以实现在一个数据集中保存多组ICA权重。 **1.9.7 滚动查看组件** 通过“Tools”菜单下的“Scroll through components”选项，可以逐一查看每个ICA组件的特征，这对于理解数据中的复杂结构非常有帮助。总结：EEGLAB是一款功能强大且易用的EEG数据分析工具。通过上述介绍，读者可以了解到EEGLAB的基本操作流程，包括数据加载、预处理、数据分割、数据平均、图像绘制以及ICA分析等方面。熟练掌握EEGLAB不仅可以提高数据分析效率，还能帮助研究人员深入理解复杂的EEG数据。

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EEGLAB Tutorial

Arnaud Delorme, Toby Fernsler, Hilit Serby, and Scott Makeig, April 12, 2006

Table of Contents

Introduction.....................................................................................................................................................................1

I. Analyzing Data in EEGLAB.........................................................................................................................................4

I.1. Loading data and visualizing data information..............................................................................................4

I.1.1. Getting started......................................................................................................................................4

I.1.1.1. Learning Matlab..........................................................................................................................4

I.1.1.2. Installing EEGLAB and tutorial files............................................................................................4

I.1.1.3. Starting Matlab and EEGLAB.....................................................................................................5

I.1.2. Opening an existing dataset.................................................................................................................7

I.1.3. Editing event values.............................................................................................................................8

I.1.4. About this dataset................................................................................................................................9

I.1.5. Scrolling through the data....................................................................................................................9

I.2. Using channel locations...............................................................................................................................14

I.2.1. Importing channel location for the tutorial dataset.............................................................................14

I.2.2. Retrieving standardized channel locations.........................................................................................19

I.2.3. Importing measured 3-D channel locations information.....................................................................20

I.3. Plotting channel spectra and maps.............................................................................................................23

I.4. Preprocessing tools.....................................................................................................................................24

I.4.1. Changing the data sampling rate.......................................................................................................24

I.4.2. Filtering the data................................................................................................................................24

I.4.3. Re-referencing the data....................................................................................................................25

I.5. Extracting data epochs................................................................................................................................28

I.5.1. Extracting epochs...............................................................................................................................28

I.5.2. Removing baseline values................................................................................................................29

I.6. Data averaging............................................................................................................................................31

I.6.1. Plotting the ERP data on a single axis with scalp maps....................................................................31

I.6.2. Plotting ERP traces in a topographic array........................................................................................32

I.6.3. Plotting ERPs in a two column array..................................................................................................33

I.6.4. Plotting an ERP as a series of scalp maps........................................................................................34

I.6.4.1. Plotting a series of 2-D ERP scalp maps..................................................................................34

I.6.4.2. Plotting ERP data as a series of 3-D maps............................................................................35

I.7. Selecting data epochs and plotting data averages......................................................................................38

I.7.1. Selecting events and epochs for two conditions................................................................................38

I.7.2. Computing Grand Mean ERPs...........................................................................................................40

I.7.3. Finding ERP peak latencies...............................................................................................................42

I.7.4. Comparing ERPs in two conditions....................................................................................................42

I.8. Plotting ERP images....................................................................................................................................44

I.8.1. Selecting a channel to plot.................................................................................................................45

I.8.2. Plotting ERP images using pop_erpimage()......................................................................................46

I.8.3. Sorting trials in ERP images..............................................................................................................48

I.8.4. Plotting ERP images with spectral options.........................................................................................51

I.8.5. Plotting spectral amplitude in single trials and additional options......................................................56

I.9. Independent Component Analysis of EEG data.........................................................................................57

I.9.1. Running ICA decompositions.............................................................................................................59

I.9.2. Plotting 2-D Component Scalp Maps.................................................................................................61

I.9.3. Plotting component headplots............................................................................................................64

I.9.4. Studying and removing ICA components...........................................................................................64

I.9.5. Subtracting ICA components from data.............................................................................................68

I.9.6. Retaining multiple ICA weights in a dataset.......................................................................................69

I.9.7. Scrolling through component activations...........................................................................................70

I.10. Working with ICA components...................................................................................................................70

I.10.1. Rejecting data epochs by inspection using ICA...............................................................................70

I.10.2. Plotting component spectra and maps.............................................................................................72

I.10.3. Plotting component ERPs................................................................................................................74

I.10.4. Plotting component ERP contributions.............................................................................................75

I.10.5. Component ERP-image plotting.......................................................................................................77

I.11. Time/frequency decomposition..................................................................................................................79

Table of Contents

I. Analyzing Data in EEGLAB

I.11.1. Decomposing channel data..............................................................................................................79

I.11.2. Computing component time/frequency transforms..........................................................................81

I.11.3. Computing component cross-coherences........................................................................................82

I.11.4. Plotting ERSP time course and topography.....................................................................................83

I.12. Processing multiple datasets.....................................................................................................................83

II. Importing/exporting data and event or epoch information into EEGLAB...........................................................87

II.1. Importing continuous data..........................................................................................................................87

II.1.1. Importing a Matlab array...................................................................................................................87

II.1.2. Importing Biosemi .BDF files.............................................................................................................88

II.1.3. Importing European data format .EDF files.......................................................................................89

II.1.4. Importing EGI .RAW continuous files................................................................................................89

II.1.5. Importing Neuroscan .CNT continuous files......................................................................................89

II.1.6. Importing Neuroscan .DAT information files.....................................................................................91

II.1.7. Importing Snapmaster .SMA files......................................................................................................92

II.1.8. Importing ERPSS .RAW or .RDF data files.......................................................................................92

II.1.9. Importing Brain Vision Analyser Matlab files.....................................................................................92

II.1.10. Importing data in other data formats...............................................................................................92

II.2. Importing event information for a continuous EEG dataset........................................................................93

II.2.1. Importing events from a data channel...............................................................................................93

II.2.2. Importing events from a Matlab array or text file...............................................................................94

II.2.3. Importing events from a Presentation file..........................................................................................95

II.3. Importing sets of single-trial EEG epochs into EEGLAB............................................................................96

II.3.1. Importing .RAW EGI data epoch files...............................................................................................96

II.3.2. Importing Neuroscan .EEG data epoch files.....................................................................................96

II.3.3. Importing epoch info Matlab array or text file into EEGLAB..............................................................97

II.4. Importing sets of data averages into EEGLAB...........................................................................................99

II.4.1. Importing data into Matlab.................................................................................................................99

II.4.2. Concatenating data averages.........................................................................................................100

II.4.3. Importing concatenated data averages in EEGLAB........................................................................100

II.5. Exporting data and ICA matrices..............................................................................................................101

II.5.1. Exporting data to an ASCII text file.................................................................................................101

II.5.2. Exporting ICA weights and inverse weight matrices.......................................................................102

III. Rejecting artifacts in continuous and epoched data.........................................................................................104

III.1. Rejecting artifacts in continuous data......................................................................................................104

III.1.1. Rejecting data by visual inspection................................................................................................104

III.1.2. Rejecting data channels based on channel statistics.....................................................................106

III.2. Rejecting artifacts in epoched data.........................................................................................................108

III.2.1. Rejecting epochs by visual inspection...........................................................................................109

III.2.2. Rejecting extreme values...............................................................................................................110

III.2.3. Rejecting abnormal trends.............................................................................................................111

III.2.4. Rejecting improbable data.............................................................................................................112

III.2.5. Rejecting abnormally distributed data............................................................................................114

III.2.6. Rejecting abnormal spectra...........................................................................................................115

III.2.7. Inspecting current versus previously proposed rejections.............................................................117

III.2.8. Inspecting results of all rejection measures...................................................................................118

III.2.9. Notes and strategy.........................................................................................................................119

III.3. Rejection based on independent data components................................................................................119

IV. Writing EEGLAB Matlab Scripts..........................................................................................................................121

IV.1. Why write EEGLAB Matlab scripts?........................................................................................................121

IV.2. Using dataset history to write EEGLAB scripts.......................................................................................121

IV.2.1. Dataset history: the EEG.history field............................................................................................122

IV.2.2. EEGLAB pop_ functions................................................................................................................123

IV.2.3. Script examples using dataset history...........................................................................................124

Table of Contents

IV. Writing EEGLAB Matlab Scripts

IV.2.4. Updating the EEGLAB window......................................................................................................125

IV.3. Using EEGLAB session history to perform basic EEGLAB script writing................................................126

IV.3.1. The h command.............................................................................................................................126

IV.3.2. Script example using session history.............................................................................................127

IV.3.3. Scripting at the EEGLAB structure level........................................................................................129

IV.4. Basic scripting examples.........................................................................................................................130

IV.5. Low level scripting...................................................................................................................................132

IV.5.1. Example script for processing multiple datasets............................................................................132

IV.5.2. Example script performing time-frequency decompositions on all electrodes...............................134

IV.5.3. Creating a scalp map animation....................................................................................................135

V. Event processing...................................................................................................................................................136

V.1. Event processing in the EEGLAB GUI.....................................................................................................136

V.1.1. Event fields.....................................................................................................................................136

V.1.2. Importing, adding, and modifying events........................................................................................137

V.1.3. Selecting events.............................................................................................................................139

V.1.4. Using events for data processing...................................................................................................139

V.2. Event processing from the Matlab command line....................................................................................141

V.2.1. Accessing events from the commandline.......................................................................................141

V.2.1.1. Event types............................................................................................................................141

V.2.1.2. Event latencies......................................................................................................................143

V.2.1.3. Urevents................................................................................................................................144

V.2.1.4. Boundary events...................................................................................................................145

V.2.1.5. 'Hard' boundaries between datasets.....................................................................................146

V.2.2. The 'epoch' structure......................................................................................................................146

V.2.3. Writing scripts using events............................................................................................................147

VI. EEGLAB Studysets and Independent Component Clustering.........................................................................150

VI.1. Component Clustering............................................................................................................................151

VI.1.1. Why cluster?..................................................................................................................................151

VI.1.2. Before clustering............................................................................................................................152

VI.1.3. Clustering outline...........................................................................................................................152

VI.2. The STUDY creation and ICA clustering interfaces................................................................................152

VI.2.1. Creating a new STUDY structure and studyset.............................................................................153

VI.2.2. Loading an existing studyset.........................................................................................................155

VI.2.3. Preparing to cluster (Pre-clustering)..............................................................................................157

VI.2.4. Finding clusters..............................................................................................................................160

VI.2.5. Viewing component clusters..........................................................................................................161

VI.2.6. Editing clusters.............................................................................................................................166

VI.2.7. Hierarchic sub-clustering...............................................................................................................168

VI.2.8. Editing STUDY datasets................................................................................................................171

VI.3. STUDY data visualization tools...............................................................................................................171

VI.4. Study statistics and visualization options................................................................................................174

VI.4.1. Parametric and non-parametric statistics......................................................................................174

VI.4.2. Options for computing statistics on and plotting results for scalp channel ERPs..........................175

VI.4.3. Computing statistics for studies with multiple groups and conditions............................................178

VI.5. EEGLAB study data structures...............................................................................................................179

VI.5.1. The STUDY structure....................................................................................................................179

VI.5.2. The STUDY.datasetinfo sub-structure...........................................................................................180

VI.5.3. The STUDY.cluster sub-structure..................................................................................................181

VI.5.4. The STUDY.changrp sub-structure...............................................................................................184

VI.6. Command line STUDY functions.............................................................................................................185

VI.6.1. Creating a STUDY.........................................................................................................................185

VI.6.2. Component clustering and pre-clustering......................................................................................186

VI.6.3. visualizing component clusters......................................................................................................186

VI.6.4. Computing and plotting channel measures...................................................................................187

Table of Contents

VI. EEGLAB Studysets and Independent Component Clustering

VI.6.5. Plotting statistics and retrieving statistical results.........................................................................187

VI.6.6. Modeling condition ERP differences using std_envtopo()............................................................188

A1. EEGLAB Data Structures....................................................................................................................................190

A1.1. EEG and ALLEEG..................................................................................................................................190

A1.2. EEG.chanlocs........................................................................................................................................191

A1.3. EEG.event..............................................................................................................................................192

A1.4. EEG.epoch.............................................................................................................................................193

A2. Options to Maximize Memory and Disk Space..................................................................................................195

A2.1. Maximize memory menu........................................................................................................................195

A2.2. The icadefs.m file...................................................................................................................................196

A3. Adding capabilities to EEGLAB..........................................................................................................................197

A3.1. Open source policy................................................................................................................................197

A3.2. How to write EEGLAB functions.............................................................................................................197

A3.2.1. The signal processing function.....................................................................................................197

A3.2.2. The associated pop_ function.......................................................................................................197

A3.3. How to write an EEGLAB plugin............................................................................................................198

A3.3.1. The plugin function.......................................................................................................................198

A3.3.2. Adding a sub-menu.......................................................................................................................198

A3.3.3. Plugins and EEGLAB history........................................................................................................199

A3.3.4. Plugin examples...........................................................................................................................199

A4. DIPFIT plug-in: Equivalent dipole source localization of independent components....................................201

A4.1. Dipole fitting with DIPFIT2......................................................................................................................202

A4.2. Setting up DIPFIT model and preferences.............................................................................................203

A4.3. Initial fitting - Scanning on a coarse-grained grid...................................................................................208

A4.4. Interactive fine-grained fitting.................................................................................................................210

A4.5. Automated dipole fitting..........................................................................................................................212

A4.6. Visualizing dipole models.......................................................................................................................213

A4.6. Plotting dipole locations on scalp maps.................................................................................................216

A4.7 Using DIPFIT to fit independent MEG components................................................................................217

A4.8 Using DIPFIT to fit EEG or ERP scalp maps...........................................................................................219

A4.9. DIPFIT structure and functions..............................................................................................................220

A4.10. DIPFIT validation study using the spherical head model.....................................................................221

A4.11. Literature references............................................................................................................................222

A5. The MI-clust plug-in: Clustering independent components using mutual information................................223