Automatic physiological waveform processing for fMRI noise correction and analysis

Abstract

Functional MRI resting state and connectivity studies of brain focus on neural fluctutions at low frequencies which share power with physiological fluctuatons originating from lung and heart. Due to the lack of automated software to process physilogical signals collected at high magnetic fields, a gap exists in the processing pathway between the acquisition of physiological data and its use in fMRI software for both physiological noise correction and functional analyses of brain activation and connectivity. To fill this gap, we developed an open source, physiological signal processing program, called PhysioNoise in the phyton language. We tested is automated processing algorithms and dynamic signal visualization on resting monkey cardiac and respiratory waveforms. PhysioNoise consistantly identifies physiological fluctuation for fMRI noise correction and also generates covariates for subsequent analyses of brain activation and connectivity. © 2008 Kelley et al.