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This article will explain in detail how to use spectral options to draw ERP images in eeglab. The editor thinks it is very practical, so I share it for you as a reference. I hope you can get something after reading this article.

1. Sort Trials by Phase Value in ERP

The eeglab is arranged by default in the order in which the trial appears during the experiment. On the pop_erpimage.m interface, clear Epoch-sorting field, Event type, Align, and Event time range. Enter 10 (Hz) in Frequency in Sort trials by phase section and 0. 0 in Window Center.

After clicking "OK", the following interface appears:

two。 Sort Trials by Phase Value in ERP

Draw the ITC in ERP image figure, as shown in the following figure, set the following parameters in pop_erpimage.

[9 / 11] Hz is set here, and significance test is carried out. Click "OK".

Parsing: the ERP image of the uppermost subgraph of the above figure. The penultimate subgraph is ERSP (Event Related Spectral Power), which represents the average change in power (in dB). In this subgraph, the curve does not exceed the blue area, indicating that there is no significant change in power at the selected frequency 10.13Hz (see lower right corner) relative to the baseline level (25.93dB). The ITC of the bottom subgraph. It represents the degree of phase synchronization in terms of relative stimulus presentation. 10.13Hz means to select the frequency band for analysis. It can be seen that the phase synchronization is significantly enhanced near the 300Hz.

The eeglab is arranged by default in the order in which the trial appears during the experiment. On the pop_erpimage.m interface, click the Epoch-sorting field button and select Latency, and click Event type to select rt. Enter 10 (Hz) in Frequency in Sort trials by phase section and 0. 0 in Window Center.

Click "OK" and the following interface pops up.

This is the end of the article on "how to draw ERP images with spectral options in eeglab". I hope the above content can be of some help to you, so that you can learn more knowledge. if you think the article is good, please share it out for more people to see.

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