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Updated: Jan 31, 2026

Optogenetic Functional MRI
Published on: April 19, 2016
Evaluation of nuisance removal for functional MRI of rodent brain
Kai-Hsiang Chuang1, Hsu-Lei Lee1, Zengmin Li2
1Queensland Brain Institute, The University of Queensland, Brisbane, QLD, 4072, Australia; Centre for Advanced Imaging, The University of Queensland, Brisbane, QLD, 4072, Australia.
Abstract:
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.
Insights
Standard human functional MRI (fMRI) nuisance removal techniques are not optimal for rodent brains. Nuisance signal estimation from outside the brain shows promise for improving rodent fMRI specificity.
Area of Science:
- Neuroimaging
- Comparative Neuroscience
- Animal Models
Background:
- Functional MRI (fMRI) is crucial for studying brain activity in humans and animal models.
- Human fMRI nuisance removal strategies (motion, CSF/white matter, global signal regression) are often applied to rodent fMRI.
- Rodent brain anatomy and experimental conditions (anesthesia, head fixation) differ significantly from humans, potentially limiting the efficacy of standard methods.
Purpose of the Study:
- To assess various nuisance regression methods and motion correction effects on rodent fMRI data.
- To evaluate the suitability of human-derived nuisance removal strategies for anesthetized rat brains.
- To investigate an alternative nuisance estimation method using signals from extra-cerebral tissues.
Main Methods:
- Analysis of a large dataset of task and resting-state fMRI in anesthetized rats.
- Assessment of sensitivity and specificity in the somatosensory pathway during forepaw stimulation.
- Simulation of reproducibility across different sample sizes via random subsampling.
- Evaluation of a novel method for estimating nuisance using principal components from extra-cerebral tissues.
Main Results:
- Detrending, motion correction, motion regression, and CSF signal regression did not improve specificity in rodent fMRI.
- Global signal regression increased specificity but significantly reduced sensitivity and connectivity strength.
- Motion parameters correlated with task activation and global signal, indicating detection of intensity variations.
- Nuisance estimation from extra-cerebral tissues provided a moderate improvement in specificity.
Conclusions:
- Nuisance removal strategies optimized for human fMRI may not be optimal for rodent fMRI.
- Standard methods like motion correction and CSF regression are insufficient for improving rodent fMRI specificity.
- Estimating nuisance signals from tissues outside the brain presents a promising alternative for rodent fMRI analysis, though further development is required.
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