M
Monique Maurice
Researcher at RIKEN Brain Science Institute
Publications - 11
Citations - 1123
Monique Maurice is an academic researcher from RIKEN Brain Science Institute. The author has contributed to research in topics: Concatenation & Electroencephalography. The author has an hindex of 8, co-authored 11 publications receiving 992 citations.
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Journal ArticleDOI
Steady-state visually evoked potentials: focus on essential paradigms and future perspectives.
TL;DR: The steady-state evoked activity, its properties, and the mechanisms behind SSVEP generation are investigated and future research directions related to basic and applied aspects of SSVEPs are outlined.
Journal ArticleDOI
Multiway array decomposition analysis of EEGs in Alzheimer's disease
Charles-Francois Vincent Latchoumane,Francois-Benois Vialatte,Jordi Solé-Casals,Monique Maurice,S. Wimalaratna,N. R. Hudson,Jaeseung Jeong,Andrzej Cichocki +7 more
TL;DR: This study applied two state of the art multiway array decomposition methods to extract unique features from electroencephalograms (EEGs) of AD patients obtained from multiple sites and demonstrated that features extracted from MAD outperformed features obtained from SSFs AMUSE and reaching up to 100% of accuracy in test condition.
Bump time-frequency toolbox: a toolbox for time-frequency oscillatory bursts extraction in electrophysiological signals
TL;DR: A user-friendly stand-alone toolbox, which models in a reasonable time a bump time-frequency model from the wavelet representations of a set of signals, is proposed.
Book ChapterDOI
Improving the Quality of EEG Data in Patients with Alzheimer's Disease Using ICA
François-Benoît Vialatte,Jordi Solé-Casals,Monique Maurice,Charles Latchoumane,N. R. Hudson,S. Wimalaratna,Jaeseung Jeong,Andrzej Cichocki +7 more
TL;DR: Findings suggest the novel usefulness of ICA in clinical EEG in Alzheimer's disease for reduction of subject variability and a method to limit the impact of human error during ICA cleaning and reduce human bias.
Journal ArticleDOI
Bump time-frequency toolbox: a toolbox for time-frequency oscillatory bursts extraction in electrophysiological signals
TL;DR: In this paper, the authors proposed a method to extract oscillatory burst events in single trials, with a reliable and consistent method, is not a simple task, but it can be done in a single trial.