Dissociating EEG sources linked to stimulus and response evaluation in numerical Stroop task using Independent Component Analysis.

@article{Beldzik2015DissociatingES,
  title={Dissociating EEG sources linked to stimulus and response evaluation in numerical Stroop task using Independent Component Analysis.},
  author={Ewa Beldzik and Aleksandra Domagalik and Wojciech Froncisz and Tadeusz Marek},
  journal={Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology},
  year={2015},
  volume={126 5},
  pages={914-26}
}
OBJECTIVES Independent Component Analysis (ICA) is a powerful data-driven technique, which separates EEG signals into functionally and physiologically distinct source activities. The aim of this study was to identify the neural sources, which contribute to scalp ERPs including N450. METHODS Dense-array EEG data were obtained from 20 participants performing numerical Stroop task. By applying ICA, artifacts were identified and removed. The remaining neural sources underwent clustering and… CONTINUE READING