Evaluation of nuisance removal for functional MRI of rodent brain.

Functional MRI (fMRI) has become an important translational tool for studying brain activity and connectivity in animal models and humans. For accurate and reliable measurement of functional connectivity, nuisance removal strategies developed for human brain, such as regressing motion parameters, cerebrospinal fluid (CSF)/white matter-derived signals and the global signal, have been applied to rodent. However, due to the very different anatomy, with the majority of the rodent brain being gray matter, and experimental conditions, in which animals are anesthetized and head-fixed, these methods may not be suitable for rodent fMRI. In this study, we assessed various nuisance regression methods and the effects of motion correction on a large dataset of both task and resting fMRI of anesthetized rat brain. Sensitivity and specificity were assessed in the somatosensory pathway under forepaw stimulation and resting state. Reproducibility at various sample sizes was simulated by randomly subsampling the dataset. To overcome the difficulty in extracting nuisance from the brain, a method using principal components estimated from tissues outside the brain was evaluated. Our results showed that neither detrend, motion correction, motion regression nor CSF signal regression could improve specificity despite increasing temporal signal-to-noise ratios. Although global signal regression increased the specificity of task activation and functional connectivity, the sensitivity and connectivity strength was drastically reduced, likely due to its strong correlation with the cortical signal. Motion parameters also correlated with task activation and the global signal, indicating that motion correction detected intensity variations in the brain. The nuisance estimated from tissues outside the brain produced a moderate improvement in specificity. In conclusion, nuisance removal suitable for human fMRI may not be optimal for rodents. While further development is needed, estimating nuisance from tissues outside the brain may be an alternative.