Journal or Book Title
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 smoothing and thresholding (FAST) algorithm that uses smoothing and extreme value theory on correlated statistical parametric maps for thresholding. Performance on 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.
Almodovar-Rivera, Israel and Maitra, Ranjan, "FAST Adaptive Smoothing and Thresholding for Improved Activation Detection in Low-Signal fMRI" (2017). Statistics Publications. 176.