Journal ArticleDOI
Automatic correction of ocular artifacts in the EEG: a comparison of regression-based and component-based methods*1
TLDR
A modified regression approach using Bayesian adaptive regression splines to filter the electrooculogram (EOG) before computing correction factors supported the use of regression-based and PCA-based ocular artifact correction and suggested a need for further studies examining possible spectral distortion from ICA-based corrections.About:
This article is published in Radiotherapy and Oncology.The article was published on 2004-05-01. It has received 221 citations till now. The article focuses on the topics: Component (UML).read more
Citations
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Journal ArticleDOI
Brain Computer Interfaces, a Review
TL;DR: The state-of-the-art of BCIs are reviewed, looking at the different steps that form a standard BCI: signal acquisition, preprocessing or signal enhancement, feature extraction, classification and the control interface.
Journal ArticleDOI
Inter-brain synchronization during social interaction.
Guillaume Dumas,Guillaume Dumas,Guillaume Dumas,Jacqueline Nadel,Robert Soussignan,Jacques Martinerie,Jacques Martinerie,Jacques Martinerie,Line Garnero,Line Garnero,Line Garnero +10 more
TL;DR: It is discovered by the use of nonlinear techniques that states of interactional synchrony correlate with the emergence of an interbrain synchronizing network in the alpha-mu band between the right centroparietal regions, which have been suggested to play a pivotal role in social interaction.
Journal ArticleDOI
Good practice for conducting and reporting MEG research
Joachim Gross,Sylvain Baillet,Gareth R. Barnes,Richard N. Henson,Arjan Hillebrand,Ole Jensen,Karim Jerbi,Vladimir Litvak,Burkhard Maess,Robert Oostenveld,Lauri Parkkonen,Jason R. Taylor,Virginie van Wassenhove,Virginie van Wassenhove,Michael Wibral,Jan-Mathijs Schoffelen +15 more
TL;DR: This manuscript aims at making recommendations for a number of important data acquisition and data analysis steps and suggests details that should be specified in manuscripts reporting MEG studies, in order to facilitate interpretation and reproduction of the results.
Journal ArticleDOI
A practical guide to the selection of independent components of the electroencephalogram for artifact correction
TL;DR: SASICA is a didactic tool that allows users to quickly understand what signal features captured by ICs make them likely to reflect artifacts, and constitutes a helpful guide for human users for making final decisions.
Journal ArticleDOI
A fully automated correction method of EOG artifacts in EEG recordings.
Alois Schlögl,Claudia Keinrath,Doris Zimmermann,Reinhold Scherer,Robert Leeb,Gert Pfurtscheller +5 more
TL;DR: The proposed method was able to reduce EOG artifacts by 80% and has been implemented for offline and online analysis and is available through BioSig, an open source software library for biomedical signal processing.
References
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Journal ArticleDOI
An information-maximization approach to blind separation and blind deconvolution
TL;DR: It is suggested that information maximization provides a unifying framework for problems in "blind" signal processing and dependencies of information transfer on time delays are derived.
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Independent component analysis, a new concept?
TL;DR: An efficient algorithm is proposed, which allows the computation of the ICA of a data matrix within a polynomial time and may actually be seen as an extension of the principal component analysis (PCA).
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Fast and robust fixed-point algorithms for independent component analysis
TL;DR: Using maximum entropy approximations of differential entropy, a family of new contrast (objective) functions for ICA enable both the estimation of the whole decomposition by minimizing mutual information, and estimation of individual independent components as projection pursuit directions.
Journal ArticleDOI
A new method for off-line removal of ocular artifact.
TL;DR: EMCP permits retention of all trials in an ERP experiment, irrespective of ocular artifact, and has the advantage that separate correction factors are computed for blinks and movements and that these factors are based on data from the experimental session itself rather than from a separate calibration session.
Journal ArticleDOI
Removing electroencephalographic artifacts by blind source separation.
Tzyy-Ping Jung,Tzyy-Ping Jung,Scott Makeig,Colin Humphries,Te-Won Lee,Te-Won Lee,Martin J. McKeown,Vicente J. Iragui,Terrence J. Sejnowski,Terrence J. Sejnowski +9 more
TL;DR: The results on EEG data collected from normal and autistic subjects show that ICA can effectively detect, separate, and remove contamination from a wide variety of artifactual sources in EEG records with results comparing favorably with those obtained using regression and PCA methods.