Related Experiment Video
Updated: Jul 10, 2026
15:18
Making MR Imaging Child's Play - Pediatric Neuroimaging Protocol, Guidelines and Procedure
Published on: July 30, 2009
Physiological noise modelling for spinal functional magnetic resonance imaging studies
Jonathan C W Brooks1, Christian F Beckmann, Karla L Miller
1PaIN Group, Department of Physiology Anatomy and Genetics, Le Gros Clark Building, South Parks Road, Oxford OX1 3QX, UK. jonathan.brooks@dpag.ox.ac.uk
Neuroimage
|October 24, 2007
Summary
This study introduces a new physiological noise model (PNM) to improve spinal cord functional imaging. By correcting for physiological noise, the PNM enhances the accuracy of spinal cord activation detection during sensory stimulation.
Area of Science:
- Neuroimaging
- Spinal Cord Physiology
- Functional MRI
Background:
- Spinal cord functional imaging assesses sensory neuron activity but faces challenges with inconsistent human data.
- Physiological noise, often uncorrected, significantly contributes to variability in gradient-echo based functional MRI (fMRI) of the spinal cord.
Purpose of the Study:
- To characterize sources of physiological noise in spinal cord fMRI.
- To develop and validate a physiological noise model (PNM) for improved spinal cord activation detection.
Main Methods:
- Acquired single-slice resting-state spinal cord data using gradient-echo EPI at different repetition times (TR).
- Utilized probabilistic independent component analysis (PICA) to identify physiologically dependent signal components.
- Developed a PNM based on retrospective image correction (RETROICOR) incorporating cardiac, respiratory, and low-frequency noise regressors.
- Assessed PNM effectiveness by comparing spinal cord activation during thermal stimulation with and without the PNM.
Main Results:
- PICA identified key sources of physiological noise in spinal cord fMRI.
- The optimal PNM included cardiac, respiratory, interaction, and low-frequency regressors, validated by F-tests.
- Applying the PNM significantly reduced false-positive activation in the cerebrospinal fluid (CSF) space compared to conventional GLM without noise correction.
Conclusions:
- A novel physiological noise model (PNM) effectively corrects for noise in spinal cord fMRI.
- The PNM enhances the reliability and accuracy of detecting spinal cord activation patterns.
- This approach offers a significant improvement for human spinal cord functional imaging studies.
