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Matlab implementation of regularization techniques for the SPoC algorithm

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regularized_SPoC

This repository contains the Matlab implementation of different regularization strategies for the SPoC algorithm:

A. Meinel, J.S. Castaño-C., B. Blankertz, F. Lotte, M. Tangermann, "Characterizing Regularization Techniques for Spatial Filter Optimization in Oscillatory EEG Regression Problems", Springer Neuroinformatics, 2018 - link

The original publication of the SPoC algorithm without regularization can be found here:

S. Dähne, F. C. Meinecke, S. Haufe, J. Höhne, M. Tangermann, K. R. Müller, V. V. Nikulin, "SPoC: a novel framework for relating the amplitude of neuronal oscillations to behaviorally relevant parameters", NeuroImage, 86:111-122, 2014

The original implementation can be found here: matlab_SPoC

Getting started

  1. Download the following toolboxes and save them under ./external:
  • bbci_toolbox - Matlab toolbox for BCI experimenting
  • Post-HocLabeling - Framework to generate labeled data sets from arbitrary, pre-recoreded EEG files
  1. Download EEG data available at https://zenodo.org/record/1065107#.WhaCX3XyvCI and place the .mat files under ./data
  2. Run the script "test_regularizedSPoC.m" to get familiar with the usage in an example decoding scenario.

@Andreas Meinel, 06.08.2018. Contact: [email protected]

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Matlab implementation of regularization techniques for the SPoC algorithm

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