Tutorial 10: Power spectrum and frequency filters

Authors: Francois Tadel, Elizabeth Bock, John C Mosher, Richard Leahy, Sylvain Baillet

We are now going to process our continuous recordings to remove the main sources of noise. Typically, we can expect contaminations coming from the environment (power lines, stimulation equipment, building vibrations) and from the subject (movements, blinks, heartbeats, breathing, teeth clenching, muscle tension, metal in the mouth or the body). In this tutorial, we will focus first on the noise patterns that occur continuously, at specific frequencies.

We can correct for these artifacts using frequency filters. Usually we prefer to run these notch and band-pass filters before any other type of correction, on the continuous files. They can be applied to the recordings without much supervision, but they may create important artifacts at the beginning and the end of the signals. Processing the entire continuous recordings at once instead of the imported epochs avoids adding these edge effects to all the trials.

Evaluation of the noise level

Before running any type of cleaning procedure on MEG/EEG recordings, we always recommend to start with a quick evaluation of the noise level. An easy way to do this is to estimate the power spectrum of all the signals over the entire recordings.

Interpretation of the PSD

File: AEF#01

File: AEF#02

File: Noise recordings

X Log-scale

Elekta-Neuromag and EEG users

The Elekta-Neuromag MEG systems combine different types of sensors with very different amplitude ranges, therefore you would not observe the same types of figures. Same thing for EEG users, this might not look like what you observe on your recordings.

For now, keep on following these tutorials with the example dataset to learn how to use all the Brainstorm basic features. Once you're done, read additional tutorials in the section "Other analysis scenarios" to learn about the specificities related with your own acquisition system.

Apply a notch filter

For illustration purposes, we will now run a frequency filter to remove the 60Hz+harmonics from the continuous files. Notch filters are adapted for removing well identified contaminations from systems oscillating at very stable frequencies.

Evaluation of the filter

Some cleaning

To avoid any confusion later, delete the links to the original files:

Note for beginners

Everything below is advanced documentation, you can skip it for now.


What filters to apply?

The frequency filters you should apply depend on the noise present in your recordings, but also on the type of analysis you are planning to use them for. This sections provides some general recommendations.

High-pass filter

Low-pass filter

Band-pass filter

Notch filter

When to apply these filters?

Filter specifications: Low-pass, high-pass, band-pass

Filter specifications: Notch [TODO]

Filter specifications: Band-stop [TODO]


On the hard drive

The names of the files generated by the process "Power spectrum density" start with the tag timefreq_psd, they share the same structure as all the files that include a frequency dimension.

To explore the contents of a PSD file created in this tutorial, right-click on it and use the popup menus
File > View file contents or File > Export to Matlab.

Structure of the time-frequency files: timefreq_psd_*.mat

Useful functions

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Tutorials/ArtifactsFilter (last edited 2017-03-16 19:27:23 by ?MartinCousineau)