Campus Units

Statistics

Document Type

Article

Publication Version

Submitted Manuscript

Publication Date

2017

Journal or Book Title

arXiv

Abstract

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.

Comments

This is a pre-print of the article Almodóvar-Rivera, Israel, and Ranjan Maitra. "FAST adaptive smoothing and thresholding for improved activation detection in low-signal fMRI." arXiv preprint arXiv:1702.00111 (2017). Posted with permission.

Copyright Owner

The Authors

Language

en

File Format

application/pdf

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