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» Sources of Variability in MEG
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MBEC
2011
117views more  MBEC 2011»
14 years 16 days ago
Face activated neurodynamic cortical networks
Previous neuroimaging studies have shown that complex visual stimuli, such as faces, activate multiple brain regions, yet little is known on the dynamics and complexity of the acti...
Ana Susac, Risto J. Ilmoniemi, Douglas Ranken, Sel...
62
Voted
ISBI
2009
IEEE
15 years 4 months ago
Improving M/EEG Source Localization with an Inter-Condition Sparse Prior
The inverse problem with distributed dipoles models in M/EEG is strongly ill-posed requiring to set priors on the solution. Most common priors are based on a convenient ℓ2 norm....
Alexandre Gramfort, Matthieu Kowalski
76
Voted
IJCNN
2000
IEEE
15 years 2 months ago
ICA for Noisy Neurobiological Data
ICA (Independent Component Analysis) is a new technique for analyzing multi-variant data. Lots of results are reported in the field of neurobiological data analysis such as EEG (...
Shiro Ikeda, Keisuke Toyama
ICASSP
2011
IEEE
14 years 1 months ago
Topographic phase maps using iterative independent component analysis
In this study, we employed our recently developed iterative independent component analysis (iICA) procedure to measure single-trial EPs from auditory N100 recordings of 21 normal ...
Darshan Iyer, George Zouridakis
MICCAI
2008
Springer
15 years 10 months ago
A Distributed Spatio-temporal EEG/MEG Inverse Solver
We propose a novel 1 2-norm inverse solver for estimating the sources of EEG/MEG signals. Based on the standard 1-norm inverse solver, the proposed sparse distributed inverse solve...
Wanmei Ou, Polina Golland, Matti Hämäl&a...