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This article mainly introduces how to use the preprocessing tools in eeglab, which has a certain reference value, interested friends can refer to, I hope you can learn a lot after reading this article, the following let the editor take you to understand.

1. Filter the data

In order to eliminate the linear trend, it is usually necessary to perform high-pass filtering on the data.

In practice, we recommend filtering continuous EEG data before epoching (difficult to translate, just keep this) or removing artifacts, although epoched data is filtered by this feature (each epoch is filtered separately). Filtering continuous data can minimize the introduction of filtering artifacts at epoch boundaries.

On the eeglab interface, select Tools > Filter the data > Basic FIR filter, enter 10 (Hz) as the lower edge frequency, 50 (Hz) as the upper edge frequency, and then click "OK".

At the end of the above steps, a pop_newset.m window pops up asking for the name of the new dataset. We chose to modify the dataset name and overwrite the parent dataset. Finally, click "OK"

After doing the above, the following effect occurs:

two。 Re-reference data (Re-referencing the data)

The reference electrode used to record EEG data is often referred to as a "universal" reference (common reference) of data. A typical recording reference in EEG recording is a mastoid (such as TP10 in the system 10-20 below, the red electrode in the below), connected mastoid (usually digitally connected mastoid, computed post hoc, vertex electrode (Cz), single or connected earlobe or nasal tip, and systems with active electrodes (such as BioSemi activity level II) can record non-referenced data. In this case, reference is made when selecting during the data import process, otherwise 40 dB of unnecessary noise will be left in the data. [note: there is no "best" public reference site, and some researchers claim that a non-scalp reference (earlobe, nose) introduces more noise than a scalp channel reference, but to the best of our knowledge it has not been confirmed.

Some researchers advocate converting data from a fixed or (common reference) general reference (for example, from a general earlobe or other channel reference) to an "average reference (average reference)" before analysis, especially when the electrode splicing covers almost the entire head (for some high-density recording systems). The advantage of the average reference point is that the sum of the outward positive and negative currents on the entire sphere is 0 (according to Ohm's law). For example, in the following illustration, the power supply in the tangent direction is associated with the positive inward positive current on the left (blue here) and the reverse outward negative current on the right (red). If the current through the base of the skull to the neck and the body is negligible (for example, due to the low conductivity of the skull base at the base of the brain), it can be assumed that the sum of electric fields recorded by all scalp electrodes (dense enough and evenly distributed) is always 0 (average reference hypothesis).

However, there is a problem with this assumption, which is that the real average reference data requires a uniform distribution of electrodes. In fact, this is not usually the case, because researchers usually place more electrodes in some areas of the scalp and fewer electrodes, if any, in the lower half of the head surface. Therefore, the average reference result using one stitching cannot be directly compared with the average reference result obtained by using another splicing.

Next, the process of converting data into an average reference (average reference) is described in detail. Note that in this process, the implicit activity time process at the previous reference electrode can be calculated from the rest of the data (therefore, the data obtains an additional channel-though not an additional degree of freedom!). Also note that if the data is recorded using the tip of the nose or earlobe electrodes, these reference electrodes should not be included when calculating the average reference values in (1) (as shown in the following example). The division factor {in (3)} will be 64 instead of 65. Note that when you use the EEGLAB dipfit plug-in to localize the source code, the average reference is used internally (no user input is required).

The selection of data references shades the drawing results of the data analysis (literally). For example, even if there is actually an alpha source just below the reference channel and facing the reference channel, the average alpha power map on the scalp must have a minimum at the reference channel! Then, no (valid) references can be said to be wrong-on the contrary, it can be said that each reference provides another view of the data. However, the nature of the reference must be taken into account when evaluating (or especially comparing) EEG results.

Re-referencing the data operation

On the eeglab interface, do the following: Tools > Re-reference, and convert the dataset to an average reference (average reference, temporarily translated to average reference) by calling the pop_reref.m function. The following window pops up the first time this menu item is called for a given dataset.

Since the above sample data is recorded using a mastoid reference, we do not want to include the reference channel (neither in the data center nor in the average reference), so do not click the "Add current reference channel in data" check box. Click this check box when the record reference is on the scalp.

Click "OK" in the above dialog box and the following re-reference window will appear:

Press the OK button to calculate the average reference value. This step will be recorded in the main eeglab window (not shown). As in the previous step, a dialog box appears asking for the name of the new dataset. Save the rereferenced data to the new dataset, or click cancel because the new reference is not used in the following sections.

After the data average reference (average referenced), calling the Tools > Re-reference menu still allows you to re-reference the data to any channel or channel group (or undo the average reference conversion, as long as you choose to include the initial reference channel in the data when converting to average reference).

Re-reference the data (I do not know whether the reference here can be translated into a quote, I am not talented and knowledgeable, if anyone knows, you are welcome to leave a message on the official account or Wechat) may be more complicated. For example, if you record the data referenced to the Cz and want to rereference the data to the connected papillae. Now, you want to add Cz back to the data under the average reference assumption (assuming the average of all electrodes is 0). The first step is to calculate the average reference and declare the Cz as a reference in the channel editor. In the channel editor, references are placed after all data channels (note that for references, the check box "data channel" is not selected because they are not actual data channels). To declare a reference, go to the last channel and press the "Append" button, which creates an empty channel.

In the newly created empty channel, fill in the information: Channel label, channel location (if any). Here is an example, fill in as follows:

Click the Set reference button (such as the button in the red box above) and set the reference of all channels to Cz (Cz needs to enter the check box, and the channel range needs to be entered manually). Click OK.

Thank you for reading this article carefully. I hope the article "how to use preprocessing tools in eeglab" shared by the editor will be helpful to everyone. At the same time, I also hope you will support us and pay attention to the industry information channel. More related knowledge is waiting for you to learn!

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