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Mike Cohen进行EEG信号预处理的步骤

(2017-11-13 17:02:05)
分类: fMRI/EEG
Mike Cohen作为EEG信号处理界的大咖,这点我相信很多人不会质疑吧。而且他热衷于推广用时间-频率分析方法分析EEG信号,自己不仅写了几本适合心理学和神经科学背景的学生读的方法学书,还开了网站,把自己亲自讲课的视频放了上去。
大家一定很好奇,大牛自己实验室到底是指怎么进行EEG信号处理的呢?
他在自己作为创建人的Google group里分享了自己做预处理的步骤:

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1. Import raw data.

2. highpass filter at .5 Hz (we don't use a low-pass)

3. Import standard channel locations

4. Rereference EOG channels

5. Epoch data to one EEG structure (eeglab format) that contains ALL trials across all conditions.

6. Subtract a prestimulus baseline.

7. Adjust marker values as appropriate (for example, mark trials as error or posterror)

8. Task-based trial rejection (for example, remove trials with no response or really long responses)

9. Manual trial rejection based on visual inspection

10. Mark electrodes as bad if necessary. Electrodes are not marked as bad if they contain signal and noise; only if they are pure noise, for example if the electrode wasn't even plugged in during the recording.

11. Average reference. Note that you should re-reference the data only after marking electrodes as bad. You don't want the noise from a single bad electrode to infect the good data from other electrodes.

12. run ICA and mark components for removal.

13. Apply scalp Laplacian. In my book, I generally promote the use of the Laplacian. A recent special issue on the Laplacian in EEG research appeared in International Journal of Psychophysiology. After reading those papers, I became more convinced that basically all EEG research should use the Laplacian, and you should need a good reason not to use it.

14. Separate epochs according to experiment condition and start analyzing (i.e., the fun part)!

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