کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
505644 864526 2009 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Gaussian source model based iterative algorithm for EEG source imaging
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزارهای علوم کامپیوتر
پیش نمایش صفحه اول مقاله
Gaussian source model based iterative algorithm for EEG source imaging
چکیده انگلیسی

Estimation of the neural active sources from the scalp electroencephalogram (EEG) is an ill-posed inverse problem. In this paper, we propose a new source model: Gaussian distributed Source Model (GSM), to model the activations in brain. GSM may imitate an Isolated Source Model (ISM) or a Distributed Source Model (DSM) by adopting different supporting range parameter of the Gaussian function. Using GSM, an iterative Gaussian source Imaging Algorithm (GIA) is developed to detect the EEG sources. As GIA dynamically reduces the solution space, the solution may gradually converge to a desired distribution. A comparative evaluation among LORETA, FOCUSS and GIA was conducted for both isolated point sources and distributed sources, the results demonstrate that GIA is more flexible and efficient for various actual sources configurations. Finally, GSM was applied to real recordings obtained from a visual spatial attention task; the corresponding source activation areas of the early component are localized in contralateral occipital cortices, consistent with the retinotopic organization of early visual spatial attention effects.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers in Biology and Medicine - Volume 39, Issue 11, November 2009, Pages 978–988
نویسندگان
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