کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4335456 1295155 2011 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Default network correlations analyzed on native surfaces
موضوعات مرتبط
علوم زیستی و بیوفناوری علم عصب شناسی علوم اعصاب (عمومی)
پیش نمایش صفحه اول مقاله
Default network correlations analyzed on native surfaces
چکیده انگلیسی

Disruptions of interregional correlations in the blood oxygenation level dependent fMRI signal have been reported in multiple diseases, including Alzheimer's disease and mild cognitive impairment. “Default network” regions that overlap with areas of earliest amyloid deposition have been highlighted by these reports, and abnormal default network activity is also observed in unimpaired elderly subjects with high amyloid burden. However, one limitation of current methods for analysis of interregional correlations is that they rely on transformation of functional data to an atlas volume (e.g., Talairach-Tournoux or Montreal Neurological Institute atlases) and may not adequately account for anatomic variation between subjects, particularly in the presence of atrophy. We assessed the utility of the FreeSurfer cortical parcellation to analyze default network functional correlations on the native surfaces of individual subjects. Group-level quantitative analysis was accomplished by comparing correlations between equivalent structures in different subjects. The method was applied to resting-state fMRI data from young, healthy subjects; preliminary results were also obtained from cognitively unimpaired elderly subjects and patients with Alzheimer's disease, Parkinson's disease, Parkinson's disease dementia, and dementia with Lewy bodies.


► Automated method using FreeSurfer for analyzing BOLD correlations on native surfaces.
► Surface parcellation allows comparisons of native-surface analyses across subjects.
► Method highlights default network regions in data from individual subjects.
► Results presented for young, elderly, Alzheimer's, Parkinson-related dementias.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Neuroscience Methods - Volume 198, Issue 2, 15 June 2011, Pages 301–311
نویسندگان
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