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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.

Neuroimage
|December 30, 2018
PubMed

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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