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How to use ICA to decompose data

Shulou Source: shulou.com Published: 2022-06-02 00:32:57 10月02日 Update

How to use ICA to decompose data, I believe that many inexperienced people do not know what to do. Therefore, this paper summarizes the causes and solutions of the problem. Through this article, I hope you can solve this problem.

ICA decomposition data

Step 1: import data eeglab tutorial Series (1)-load and display data

Step 2: according to the tutorial eeglab tutorial series (2)-draw EEG scalp map import location information.

After completing the previous two steps, you can decompose the ICA data.

Step 3: decompose ICA data

Operation: Tools > Run ICA. Operate the following interface:

After the operation, the following interface appears:

Select the default algorithm runica and click "OK". The running speed will be slow, please wait patiently. Note: after clicking "OK", the following screen may appear. Do not click "Interrupt". This is because it takes a long time to run slowly, and if you click on it, you will "interrupt" the run.]

In the course of running, the

Step 4: draw 2merd Component Scalp Maps

Specific operations:

The following window pops up:

Since you want to draw 1:12 independent components here, you need to set the text box after "Component numbers" to 1:12, as follows:

After clicking "OK", the following interface pops up:

Through the picture above, we can understand the scalp distribution of each independent component. Click any of the scalp images in the above image to pop up a child window containing the scalp map.

Draw component headplots

Specific operation: Plot > Component maps > In 3murd. As follows:

When the following picture appears, indicate a warning message and click OK.

When drawing ERP 3murd scalp maps, you need to select use the spline file, as follows:

Click "OK" and the following interface appears:

After reading the above, have you mastered how to use ICA to decompose the data? If you want to learn more skills or want to know more about it, you are welcome to follow the industry information channel, thank you for reading!

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