Decoding, encoding, and general machine learning examples.
Motor imagery decoding from EEG data using the Common Spatial Pattern (CSP)
Decoding in time-frequency space using Common Spatial Patterns (CSP)
Representational Similarity Analysis
Continuous Target Decoding with SPoC
Decoding sensor space data with generalization across time and conditions
Analysis of evoked response using ICA and PCA reduction techniques
Compute effect-matched-spatial filtering (EMS)
Linear classifier on sensor data with plot patterns and filters
Receptive Field Estimation and Prediction
Compute Spectro-Spatial Decomposition (SSD) spatial filters