Tutorial 13: Decoding Conditions

Author: Seyed-Mahdi Khaligh-Razavi

These set of functions allow you to do support vector machine (SVM) and linear discriminant analysis (LDA) classification on your MEG data across time.

Input: the input is channel data from two conidtions (e.g. condA and condB) across time. Number of samples per condition should be the same for both condA and condB. Each of them should be at least contain two samples.

Output: the output is a decoding curve across time, showing your decoding accuracy (decoding condA vs. condB) at timepoint 't'.