Share This Author
EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis
Analysis of fMRI data by blind separation into independent spatial components
This work decomposed eight fMRI data sets from 4 normal subjects performing Stroop color‐naming, the Brown and Peterson word/number task, and control tasks into spatially independent components, and found the ICA algorithm was superior to principal component analysis (PCA) in determining the spatial and temporal extent of task‐related activation.
Removing electroencephalographic artifacts by blind source separation.
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.
Mining event-related brain dynamics
Dynamic Brain Sources of Visual Evoked Responses
It is shown that nontarget event-related potentials were mainly generated by partial stimulus-induced phase resetting of multiple electroencephalographic processes in a human visual selective attention task.
Independent Component Analysis of Electroencephalographic Data
First results of applying the ICA algorithm to EEG and event-related potential (ERP) data collected during a sustained auditory detection task show that ICA training is insensitive to different random seeds and ICA may be used to segregate obvious artifactual EEG components from other sources.
Auditory event-related dynamics of the EEG spectrum and effects of exposure to tones.
- S. Makeig
- Psychology, PhysicsElectroencephalography and Clinical…
- 1 April 1993
A 40-Hz auditory potential recorded from the human scalp.
- R. Galamboš, S. Makeig, P. J. Talmachoff
- Biology, PhysicsProceedings of the National Academy of Sciences…
- 1 April 1981
It is shown that these waves combined to form a single, stable, composite wave when the sounds are repeated at rates around 40 per sec, which suggests that adequate processing of sensory information may require cyclical brain events in the 30- to 50-Hz range.
Removal of eye activity artifacts from visual event-related potentials in normal and clinical subjects