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Abstract #4435

Automated data acquisition system for fMRI resting state de-noising

Grace Li Haug1, Domenic Cerri1, Yen-Yu Ian Shih1, and SungHo Lee1

1Biomedical Research Imaging Center and Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States

We have developed an automated system for collecting data from monitoring devices for animal functional MRI (fMRI) research to clean the effects of the physiological nuisance signal. Graphical user interface (GUI) is also provided to make a convenient environment for monitoring animal vital signs on one screen. To demonstrate the system’s usefulness, we perform CBV-based resting-state fMRI and compare the changes of temporal signal-to-noise ratio (tSNR) in the striatum between the before and after end-tidal CO2 (EtCO2) signal correction using RETROICOR algorithm. The software automates the time synchronization among the collected data and will be expanded to automate the noise filtering process.

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