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Module 4: fMRI

This module covers fMRI data, including creating and interpreting flatmaps, exploring variability and average responses, and visual eccenticity. You will learn about processing BOLD signals, trial-averaging, and t-tests. The MATLAB code introduces data animations, multicolor visualizations, and linear indexing.

Course Features
Tutorials
Code / Datasets
Exercises
Lessons of this Course
1
1
Duration:
7:15

This lecture introduces neuroscience concepts and methods such as fMRI, visual respones in BOLD data, and the eccentricity of visual receptive fields. 

2
2
Duration:
12:15

This tutorial walks users through the creation and visualization of activation flat maps from fMRI datasets. 

3
3
Duration:
12:05

This tutorial demonstrates to users the conventional preprocessing steps when working with BOLD signal datasets from fMRI. 

4
4
Duration:
20:12

In this tutorial, users will learn how to create a trial-averaged BOLD response and store it in a matrix in MATLAB. 

5
5
Duration:
12:52

This tutorial teaches users how to create animations of BOLD responses over time, to allow researchers and clinicians to visualize time-course activity patterns.

6
6
Duration:
13:39

This tutorial demonstrates how to use MATLAB to create event-related BOLD time courses from fMRI datasets. 

7
7
Duration:
17:54

In this tutorial, users learn how to compute and visualize a t-test on experimental condition differences.