کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6037584 | 1188789 | 2010 | 15 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Independent component analysis of short-time Fourier transforms for spontaneous EEG/MEG analysis
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کلمات کلیدی
موضوعات مرتبط
علوم زیستی و بیوفناوری
علم عصب شناسی
علوم اعصاب شناختی
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چکیده انگلیسی
Analysis of spontaneous EEG/MEG needs unsupervised learning methods. While independent component analysis (ICA) has been successfully applied on spontaneous fMRI, it seems to be too sensitive to technical artifacts in EEG/MEG. We propose to apply ICA on short-time Fourier transforms of EEG/MEG signals, in order to find more “interesting” sources than with time-domain ICA, and to more meaningfully sort the obtained components. The method is especially useful for finding sources of rhythmic activity. Furthermore, we propose to use a complex mixing matrix to model sources which are spatially extended and have different phases in different EEG/MEG channels. Simulations with artificial data and experiments on resting-state MEG demonstrate the utility of the method.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: NeuroImage - Volume 49, Issue 1, 1 January 2010, Pages 257-271
Journal: NeuroImage - Volume 49, Issue 1, 1 January 2010, Pages 257-271
نویسندگان
Aapo Hyvärinen, Pavan Ramkumar, Lauri Parkkonen, Riitta Hari,