Physiological Noise Modeling and Analysis for Spinal Cord fMRI

Spinal cord functional imaging offers new insights into normal sensorimotor processing and monitoring disease processes affecting the cord. However, all imaging-based techniques suffer from unwanted contributions to the measured signal from nonneuronal physiological sources. Broadly, these noise sources can be grouped into those arising from cardiac or respiratory processes, as well as from their interaction. Different techniques for estimating and removing physiological noise, their implication for functional magnetic resonance imaging (fMRI) analysis, and their implementation within the framework of the general linear model will be demonstrated. Recommendations for preprocessing spinal fMRI data will be given, such as how to avoid potential inflation of recorded T-statistics and whether prewhitening is appropriate for processing spinal fMRI data. Finally, techniques for the registration of spinal cord functional imaging data to a standard spinal cord, for the purpose of group analysis, will be presented along with techniques for estimating significance from group data.