کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6035560 | 1188767 | 2010 | 14 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Multi-level bootstrap analysis of stable clusters in resting-state fMRI
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کلمات کلیدی
Functional MRI - افامآرآی یا تصویرسازی تشدید مغناطیسی کارکردیBootstrap - بوت استرپStability analysis - تجزیه و تحلیل ثباتMulti-level analysis - تجزیه و تحلیل چند سطحClustering - خوشه بندیHierarchical clustering - خوشه بندی سلسله مراتبیResting-state networks - شبکه های دولت در حالت استراحتk-Means - میانگین ـ کی
موضوعات مرتبط
علوم زیستی و بیوفناوری
علم عصب شناسی
علوم اعصاب شناختی
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چکیده انگلیسی
A variety of methods have been developed to identify brain networks with spontaneous, coherent activity in resting-state functional magnetic resonance imaging (fMRI). We propose here a generic statistical framework to quantify the stability of such resting-state networks (RSNs), which was implemented with k-means clustering. The core of the method consists in bootstrapping the available datasets to replicate the clustering process a large number of times and quantify the stable features across all replications. This bootstrap analysis of stable clusters (BASC) has several benefits: (1) it can be implemented in a multi-level fashion to investigate stable RSNs at the level of individual subjects and at the level of a group; (2) it provides a principled measure of RSN stability; and (3) the maximization of the stability measure can be used as a natural criterion to select the number of RSNs. A simulation study validated the good performance of the multi-level BASC on purely synthetic data. Stable networks were also derived from a real resting-state study for 43 subjects. At the group level, seven RSNs were identified which exhibited a good agreement with the previous findings from the literature. The comparison between the individual and group-level stability maps demonstrated the capacity of BASC to establish successful correspondences between these two levels of analysis and at the same time retain some interesting subject-specific characteristics, e.g. the specific involvement of subcortical regions in the visual and fronto-parietal networks for some subjects.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: NeuroImage - Volume 51, Issue 3, 1 July 2010, Pages 1126-1139
Journal: NeuroImage - Volume 51, Issue 3, 1 July 2010, Pages 1126-1139
نویسندگان
Pierre Bellec, Pedro Rosa-Neto, Oliver C. Lyttelton, Habib Benali, Alan C. Evans,