Introduction:
Functional MRI methods have been used to study sensorimotor processing in the brain and
the Spinal cord. However, these techniques confront unwanted contributions to the measured signal from physiological fluctuations. For the spinal cord imaging, most of the challenges are consequences of cardiac and respiratory movement artifacts that are considered as significant sources of noise. Spinal cord in Thoraco-Lumbar is close to lungs and diaphragms that influence cerebrospinal fluid-filled spaces and cause changes in thesusceptibility due to the change in the amount of air in the lung. In this study, we investigatedthe effect of each source of physiological noise and contribution of them to the outcome ofthe analysis of the BOLD signal in human spinal cord during a sensory stimulation of the foot.
 
Materials and Methods:
Fifteen young healthy male volunteers participated in the study. Sixty pressure pain stimuli
delivered on L5 dermatome between the two malleoli. All of functional data were collected
using a 3T Siemens Prisma scanner with 31 axial slices T2*-weighted ZOOMit (TR = 3000 ms;
TE = 30 ms; FA = 90°; FoV = 160 × 160 mm; matrix size = 64 × 64). Respiratory and cardiac
signals were recorded during the imaging session using the data acquired from theimplemented physiological monitoring unit. The Spinal Cord Toolbox and FSL were used forimage processing and analysis. Generated respiration and cardiac regressors were includedin the GLM for the quantification of the effect of each of them on the task-analyses results. The sum of activated voxels of the clusters in the spinal cord and in all the image was
calculated.
 
Results:
Comparison of sum of activated voxels. A one-way within subject’s ANOVA was applied toevaluate the effect of physiological functions on spinal cord fMRI in three noise correction inthe GLM. There was a statistically significant effect of physiological noise correctiononnumber of activated voxels in Image, F (3, 42) = 3.00689, p = .040817, η2 =0.17, and thisvalues in spinal cord was F(3, 42) = 21.314, p =.00001, , η2 =0.6. Bonferroni post hoc testsillustrate that cardiac noise correction had an effective role on increase activated voxels
(mean = 23.46±9.46) compared to other noise correction methods.
 
Conclusion:
The effect of the Heart-beat and Respiration movements has a significant role in thephysiological noise and concurrency between movements with task and correction of thismovements can remove the real effect of stimulation. Cardiac effect and changes in thecorrected results are higher than other physiological noise sources. In spite of previous work,displacement of the spinal cord and effect of this noise in the fMRI results are significant andcannot be ignored.