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EEG Pipeline

EEG stands for electroencephalography, which is a technique used to measure electrical activity in the brain. EEG is a non-invasive way to collect data from the brain. Follow this pipeline to collect and analyze EEG data.

1

Collect Data

The recorded data will be saved as a .mff file. This will need to be moved to the appropriate folder in Box.

2

Import Data

The data will need to be opened in BESA on one of the analysis computers.

3

Re-reference Data

You need to convert the data to an average reference.

4

Set Channel Locations

Select the files that specifies the channel locations.

5

Delete or Interpolate Bad Channels

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

6

Filtering

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.

7

Run ICA

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

8

Epoching

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

9

Baseline Removal

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.

10

Component Rejection

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.

11

Sorting by Stimulus Type

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

12

Averaging Trials

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

13

Check the Data

Head Plots

Plot the head maps for the time ranges of interest

Waveforms

Plot the waveforms of the averaged data

Grand Averaging

Averaging all of the data of one type together (such as all face data / scene data)

14

Analyze the Data

Average Amplitudes

Wavelet Analysis

Fourier Transforms

Phase Coherence

Resources

Filename Key
Automation Scripts
EEGLAB Scripts
Other
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