Re-referencing, Filtering, Bad Channels and Baseline Correction
Overview: This class is designed to introduce re-referencing, filtering, bad channels and baseline correction.
Topics Covered:
- Overview of pre-processing
- DC offset
- Filters and why we need them
- Frequency Filters
- Time domain filters
- Bad Channels
- Re-referencing
Pre-Processing Lab: Filtering EEG/ERP Data
The purpose of this lab is to understand the effects of filtering in processing electrophysiological data. Students will learn to open a file and filter the data.
Epoching and Baseline Correction
Overview: This short class introduces epoching and baseline correction and why we do them.
Topics Covered:
- Categorizing or “binning” the trials into conditions
- Epoching the Data
- Baseline Correction
Pre-Processing Lab: Bad Channels through Epoching
The purpose of this lab is to learn to identify bad channels in their data and process the data through the epoching stage of analysis. This lab includes learning to identify bad channels, re-referencing the data, and epoching.
Artifact Rejection
Overview: This class introduces the different kinds of artifacts seen in EEG/ERP data and the two major methods to detect and address them, rejection and correction.
Topics Covered:
- Artifacts and How to Spot Them
- Artifact Detection and Rejection
- Artifact Correction
- Coming soon: Independent Components Module + Lab
Pre-Processing Lab: Artifact Rejection
In this lab students will learn to do artifact rejection by hand which will also give them a better sense of what artifacts look like. Students will also learn the impact of artifact rejection choices. Finally, they will learn the impact of artifact rejection choices.
Pre-Processing Lab: Artifact Correction
In this lab students will learn to do artifact correction using ICA. Students will learn how to identify classic artifact components, how to remove the components, and the impact of component removal choices.