Exercises

Contents:

• Dataset basics
• Split-half correlation-based MVPA with group analysis
• Classification with Naive Bayes classifier
• Write your own Nearest-neighbor classifier
• Build wrapper for Matlab’s SVM classifier
• Cross-validation part 1: N-Fold Partitioner
• Cross-validation part 2: using multiple classifiers
• Cross-validation part 3: using a dataset measure
• Visualization of DSMs
• Representational similarity analysis
• Define voxel selection for a searchlight
• Reading material
• Write a searchlight function that computes a generic dataset measure
• Use the searchlight with a neighborhood and a measure