کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
9197846 | 1188876 | 2005 | 13 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Removing the effects of task-related motion using independent-component 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
Task-related motion is a major source of noise in functional magnetic-resonance imaging (fMRI) time series. The motion effect usually persists even after perfect spatial realignment is achieved. Here, we propose a new method to remove a certain type of task-related motion effect that persists after realignment. The procedure consists of the following: the decomposition of the realigned time-series data into spatially-independent components using independent-component analysis (ICA); the automatic classification and rejection of the ICs of the task-related residual motion effects; and finally, a reconstruction without them. To classify the ICs, we utilized the associated task-related changes in signal intensity and variance. The effectiveness of the method was verified using an fMRI experiment that explicitly included head motion as a main effect. The results indicate that our ICA-based method removed the task-related motion effects more effectively than the conventional voxel-wise regression-based method.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: NeuroImage - Volume 25, Issue 3, 15 April 2005, Pages 802-814
Journal: NeuroImage - Volume 25, Issue 3, 15 April 2005, Pages 802-814
نویسندگان
Takanori Kochiyama, Tomoyo Morita, Tomohisa Okada, Yoshiharu Yonekura, Michikazu Matsumura, Norihiro Sadato,