In this module, you will work with human EEG data recorded during a steady-state visual evoked potential study (SSVEP, aka flicker). You will learn about spectral analysis, alpha activity, and topographical mapping. The MATLAB code introduces functions, sorting, and correlation analysis.
Module 2: EEG
Course Features
Tutorials
Exercises
Code / Datasets
Lessons of this Course
1
1
Duration:
8:51
Speaker:
In this lesson, users will learn about human brain signals as measured by electroencephalography (EEG), as well as associated neural signatures such as steady state visually evoked potentials (SSVEPs) and alpha oscillations.
2
2
Duration:
12:16
Speaker:
This lecture describes the principles of EEG electrode placement in both 2- and 3-dimensional formats.
3
3
Duration:
13:39
Speaker:
This tutorial walks users through performing Fourier Transform (FFT) spectral analysis of a single EEG channel using MATLAB.
4
4
Duration:
12:34
Speaker:
This tutorial builds on the previous lesson's demonstration of spectral analysis of one EEG channel. Here, users will learn how to compute and visualize spectral power from all EEG channels using MATLAB.
5
5
Duration:
9:10
Speaker:
In this lesson, users will learn more about the steady-state visually evoked potential (SSEVP), as well as how to create and interpret topographical maps derived from such studies.
6
6
Duration:
13:23
Speaker:
This lesson teaches users how to extract edogenous brain waves from EEG data, specifically oscillations constrained to the 8-12 Hz frequency band, conventionally named alpha.
7
7
Duration:
12:36
Speaker:
In the final lesson of this module, users will learn how to correlate endogenous alpha power with SSVEP amplitude from EEG data using MATLAB.
