Dept. of Statistics
Iowa State University
FAST Adaptive Smoothed Thresholding for Improved Activation Detection in Low-Signal fMRI
Functional Magnetic Resonance Imaging is a noninvasive tool used to study brain function. Detecting activation is challenged by many factors, and even more so in low-signal scenarios that arise in the performance of high-level cognitive tasks. We provide a fully automated and fast adaptive smoothed thresholding (FAST) algorithm that uses smoothing and extreme value theory on correlated statistical parametric maps for thresholding. Performance on simulation experiments spanning a range of low-signal settings is very encouraging. The methodology also performs well in a study to identify the cerebral regions that perceive only-auditory-reliable and only-visual-reliable speech stimuli as well as those that perceive one but not the other.
This research is joint with Israel Almodóvar-Rivera of the University of Puerto Rico and was supported in part by the National Institute of Biomedical Imaging and Bioengineering (NIBIB) of the National Institutes of Health (NIH) under its Award No. R21EB016212.
Refreshments at 3:45 pm in Snedecor 2101.