Object-oriented analysis walkthroughs

This series of walkthroughs is designed to illustrate the CANlab interactive analysis tools, and some analysis principles as well. Code to run each walkthrough is included in the CANlab core toolbox or on Neurovault. See the main CANlab intro page for more on the philosophy behind the interactive analysis approach.

Getting started
1.1. installing tools
1.2. load a sample dataset
1.3. basic image visualization
1.4. Loading some datasets used in tutorials
1.5. Publishing results reports
Basic analyses
2.1. group t-test
2.2. atlases and ROI analysis
2.3. Masking and writing Nifti image files
2.4. 3-D visualization on brain surfaces
2.5. Create and explore 1st-level design matrices
2.6. regression, interactive analysis
2.7. Interpreting maps with Neurosynth topic similarity and wedge plots
Multivariate predictive models
3.1. multivariate prediction with continuous outcomes
3.2 Effect sizes with SVMs
3.3. Apply a Multivariate Pattern of Interest
3.4. Bayes Factor Maps
3.5. Interpreting maps with riverplots
Mediation analysis
4.1. mediation analysis
4.2. additional output report from publish_mediation_report.m
Coordinate-based Meta-analysis
5.1. MKDA meta-analysis 1

Other tutorials

13. more visualization

14. CANLab single trials demo

Behavioral data and Plots

15. the canlab_dataset object

16. time series and bar plots

17. mixed effects models in Matlab and CANLab glmfit_multilevel

Tutorials in progress

Please note that the tutorials which follow are works in progress and of primary interest to advanced users.

Interpreting within and between subject components of PCR models