There are hundreds of sites with free, downloadable EEG data that can be imported into BESA.

After choosing a dataset, isolate the raw EEG data from the metadata and other contextual information about the experiment.

You need to convert the data to an average reference.

Select the files that specifies the channel locations.

You may want to delete channels that are too noisy, such as the ones around the face.

We use filters to take out signals that are definitley not brain data. You need to filter out the very low (<0.01-0.1 Hz) and very high frequencies (>50-100 Hz), as well as the 60 Hz line noise from the ambient electrical wires.

ICA is used to separate out the data into its various signal sources, which are both neural and non-neural.

For each stimulus, we want to extract a segment of data just before and just after the stimulus.

The signal recorded just before the stimulus is considered the baseline. This is comprised of neural activity that is not in response to the stimulus as well as noise. This baseline is subtracted from the entire epoch, leaving the neural activity that occured in response to the stimulus.

Once you've run ICA on a dataset, it is possible to reject non-neural signal sources. This section explains how to do that and explains the Sasica plug in.

Separating the data for each stimulus type into its own file.

Separating the data for each stimulus type into its own file.