TESA example data
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https://bridges.monash.edu/articles/dataset/TESA_example_data_and_scripts/3188800
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The TMS-EEG signal analyser (TESA) is an open source extension for EEGLAB that includes functions necessary for cleaning and analysing TMS-EEG data. Both EEGLAB and TESA run in Matlab (r2015b or later). The attached files are example data files which can be used with TESA. To download TESA, visit here: http://nigelrogasch.github.io/TESA/ To read the TESA user manual, visit here: https://www.gitbook.com/book/nigelrogasch/tesa-user-manual/details<br> <b>File info:</b> <i>example_data.set</i> WARNING: file size = 1.1 GB. A raw data set for trialling TESA. Load the data file in to EEGLAB using the existing EEGLAB data set functions. Note that both the .fdt and .set files are required. <i>example_data_epoch_demean.set</i> File size = 340 MB. A partially processed data file of smaller size corresponding to step 8 of the analysis pipeline in the TESA user manual. Channel locations were loaded, unused electrodes removed, bad electrodes removed, epoched (-1000 to 1000 ms) and demeaned (baseline correct -1000 to 1000). Load the data file in to EEGLAB using the existing EEGLAB data set functions. Note that both the .fdt and .set files are required. <i>example_data_epoch_demean_cut_int_ds.set</i> File size = 69 MB. A further processed data file even smaller in size corresponding to step 11 of the analysis pipeline in the TESA user manual. In addition to the above steps, data around the TMS pulse artifact was removed (-2 to 10 ms), replaced using linear interpolation, and downsampled to 1,000 Hz. Load the data file in to EEGLAB using the existing EEGLAB data set functions. Note that both the .fdt and .set files are required. <b><br></b><b>Example data info:</b> Monophasic TMS pulses (current flow = posterior-anterior in brain) were given through a figure-of-eight coil (external diameter = 90 mm) connected to a Magstim 200<sup>2</sup> unit (Magstim company, UK). 150 TMS pulses were delivered over the left superior parietal cortex (MNI coordinates: -20, -65, 65) at a rate of 0.2 Hz ± 25% jitter. TMS coil position was determined using frameless stereotaxic neuronavigation (Localite TMS Navigator, Localite, Germany) and intensity was set at resting motor threshold of the first dorsal interosseous muscle (68% maximum stimulator output). EEG was recorded from 62 TMS-specialised, c-ring slit electrodes (EASYCAP, Germany) using a TMS-compatible EEG amplifier (BrainAmp DC, BrainProducts GmbH, Germany). Data from all channels were referenced to the FCz electrode online with the AFz electrode serving as the common ground. EEG signals were digitised at 5 kHz (filtering: DC-1000 Hz) and EEG electrode impedance was kept below 5 kΩ. <br>
经颅磁刺激-脑电图(TMS-EEG)信号分析仪(TESA)是一款面向EEGLAB的开源扩展工具,内置了用于清理与分析TMS-EEG数据的必要功能。EEGLAB与TESA均需运行于Matlab(r2015b及以上版本)环境中。本次附带的文件为可配合TESA使用的示例数据文件。如需下载TESA,请访问:http://nigelrogasch.github.io/TESA/;若需查阅TESA用户手册,请访问:https://www.gitbook.com/book/nigelrogasch/tesa-user-manual/details<br> <b>文件说明:</b> <i>example_data.set</i> 警告:文件大小为1.1 GB,为用于测试TESA的原始数据集。请通过EEGLAB自带的数据集加载函数将该数据文件导入至EEGLAB中。请注意,加载时需同时提供.fdt与.set两类文件。 <i>example_data_epoch_demean.set</i> 文件大小为340 MB,为体积更小的半处理数据集,对应TESA用户手册中分析流程的第8步。该文件已完成通道位置加载、无效电极移除、坏通道剔除、分段(-1000 ms至1000 ms)以及去均值(基线校正范围为-1000 ms至1000 ms)处理。请通过EEGLAB自带的数据集加载函数将该数据文件导入至EEGLAB中。请注意,加载时需同时提供.fdt与.set两类文件。 <i>example_data_epoch_demean_cut_int_ds.set</i> 文件大小为69 MB,为体积进一步缩小的深度处理数据集,对应TESA用户手册中分析流程的第11步。除上述预处理步骤外,该数据集还移除了TMS脉冲伪影周边(-2 ms至10 ms)的数据,并通过线性插值完成替换,最终下采样至1000 Hz。请通过EEGLAB自带的数据集加载函数将该数据文件导入至EEGLAB中。请注意,加载时需同时提供.fdt与.set两类文件。 <b><br></b><b>示例数据采集说明:</b> 实验采用连接至Magstim 200²刺激器(英国Magstim公司)的8字形线圈(外径90 mm),向受试者脑内施加单相TMS脉冲(电流流向为后至前)。共向左侧顶上小叶(蒙特利尔神经研究所(MNI)坐标:-20, -65, 65)递送150个TMS脉冲,刺激频率为0.2 Hz,附带±25%的抖动。TMS线圈的位置通过无框架立体定向神经导航系统(德国Localite公司的Localite TMS Navigator)确定,刺激强度设置为第一骨间背侧肌的静息运动阈值(对应刺激器最大输出的68%)。采用兼容TMS的脑电图放大器(德国BrainProducts GmbH公司的BrainAmp DC),通过62个TMS专用C形狭缝电极(德国EASYCAP公司)采集脑电信号。所有通道的在线参考电极均为FCz,公共接地电极为AFz。脑电信号以5 kHz的采样率进行数字化(滤波范围:直流至1000 Hz),且所有脑电电极的阻抗均控制在5 kΩ以下。
提供机构:
Monash University
创建时间:
2016-04-22
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