کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6039653 | 1188824 | 2008 | 9 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Detecting change in BOLD signal between sessions for atlas-based anatomical ROIs
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موضوعات مرتبط
علوم زیستی و بیوفناوری
علم عصب شناسی
علوم اعصاب شناختی
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
An algorithm using pre-defined regions of interest (ROIs) to detect differences between sessions in Blood Oxygen-Level Dependent (BOLD) signal is proposed and results from a reproducibility study are reported here. It is important to know whether tests for change have the desired statistical properties, e.g., low variability between sessions and unbiased false-positive rates, under null conditions so one is confident in any conclusions based on the metric and test used. This study examined three cognitive tasks: Stroop, response inhibition, Sternberg digits, and a visually-cued finger tapping task, in 20 healthy subjects. Each subject had two fMRI sessions, one week apart. A series of ROI summaries was constructed by choosing different proportions of voxels from the ROI and calculating the mean of t values for the selected voxels. The choice of voxels was based on the magnitude of the t values, selecting the maximum value, then the top 1%, and so on until all voxels in the ROI were included. No ROIs were found to have significant differences between sessions based on paired comparison t tests. Generally, the observed false-positive rates were near the expected rates for all summaries and tasks, although the Sternberg and Response Inhibition tasks did have higher false-positive rates when α â¥Â 0.1 for some ROI summaries. This study indicates results are reproducible and also have the desired statistical properties under null conditions.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: NeuroImage - Volume 40, Issue 3, 15 April 2008, Pages 1157-1165
Journal: NeuroImage - Volume 40, Issue 3, 15 April 2008, Pages 1157-1165
نویسندگان
Robert Buck, Harsh Singhal, Jagriti Arora, Heidi Schlitt, R. Todd Constable,