Added Belin Brain Computer Interface platforms to the full platforms section:
BBCI: a matlab toolbox for online & offline analysis.
Pyff : a python framework for stimulus & feedback presentation.
Mushu : a python toolbox for EEG acquisition.
Wyrm : a python framework for online & offline analysis.
Added 3 papers :
Single-Trial Analysis and Classification of ERP Components – a Tutorial : In this tutorial, the authors provide a comprehensive framework for decoding ERPs, elaborating on linear concepts, namely spatio-temporal patterns and filters as well as linear ERP classification. they also propose to use shrinkage estimators and show that appropriate regularization of linear discriminant analysis (LDA) by shrinkage
yields excellent results for single-trial ERP classification that are far superior to classical
LDA classification.
Interpretable Deep Neural Networks for Single-Trial EEG Classification: the authors propose the application of DNNs with LRP (Layer-wise relevance propagation) for the first time for EEG data analysis. Through LRP the single-trial DNN decisions are transformed into heatmaps indicating each data point's relevance for the outcome of the decision.
Large-Scale Assessment of a Fully Automatic Co-Adaptive Motor Imagery-Based Brain Computer Interface : In this study the authors evaluated for the first time a fully automatic co-adaptive BCI system on a large scale. A pool of 168 participants naive to BCIs operated the co-adaptive SMR-BCI in one single session.
Added Belin Brain Computer Interface platforms to the full platforms section:
Added 3 papers :
Single-Trial Analysis and Classification of ERP Components – a Tutorial : In this tutorial, the authors provide a comprehensive framework for decoding ERPs, elaborating on linear concepts, namely spatio-temporal patterns and filters as well as linear ERP classification. they also propose to use shrinkage estimators and show that appropriate regularization of linear discriminant analysis (LDA) by shrinkage yields excellent results for single-trial ERP classification that are far superior to classical LDA classification.
Interpretable Deep Neural Networks for Single-Trial EEG Classification: the authors propose the application of DNNs with LRP (Layer-wise relevance propagation) for the first time for EEG data analysis. Through LRP the single-trial DNN decisions are transformed into heatmaps indicating each data point's relevance for the outcome of the decision.
Large-Scale Assessment of a Fully Automatic Co-Adaptive Motor Imagery-Based Brain Computer Interface : In this study the authors evaluated for the first time a fully automatic co-adaptive BCI system on a large scale. A pool of 168 participants naive to BCIs operated the co-adaptive SMR-BCI in one single session.