Functional connectivity fMRI of the rodent brain: comparison of functional connectivity networks in rat and mouse

Elisabeth Jonckers1, Johan Van Audekerke, Geofrey De Visscher

  • 1Bio-Imaging Lab, University of Antwerp, Antwerp, Belgium. elisabeth.jonckers@ua.ac.be

Plos One
|May 3, 2011
PubMed

Insights

Resting state functional MRI (rsfMRI) implementation in mice reveals species-specific brain network differences compared to rats. Mouse rsfMRI data showed unique unilateral cortical components, requiring more analytical components for accurate regional separation.

Area of Science:

  • Neuroscience
  • Medical Imaging
  • Comparative Neurology

Background:

  • Resting state functional MRI (rsfMRI) is a valuable tool in human neuropathological research.
  • Mice are crucial models for neurological diseases, necessitating robust rsfMRI protocols.
  • Comparative studies between mice and rats can enhance understanding of species-specific brain function.

Purpose of the Study:

  • To implement and validate resting state functional MRI (rsfMRI) in mice using a standardized protocol.
  • To compare rsfMRI findings between mice and rats under comparable experimental conditions.
  • To identify species-specific differences in resting-state brain networks.

Main Methods:

  • Acquisition of rsfMRI data in both mice and rats.
  • Application of a consistent protocol for anesthesia, scanning, and data analysis.
  • Utilizing Independent Component Analysis (ICA) to identify functional brain networks.

Main Results:

  • rsfMRI outcomes differed significantly between mice and rats.
  • Mouse rsfMRI data exhibited unique unilateral cortical components, unlike the bilateral networks in rats.
  • A higher number of components in ICA was required to delineate cortical regions in mice compared to rats.

Conclusions:

  • rsfMRI is feasible in mice and reveals distinct functional brain organization compared to rats.
  • Species-specific differences in cortical network topology exist between mice and rats.
  • The number of ICA components is a critical parameter influencing the interpretation of rsfMRI data in different species.

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