Resting state network topology of the ferret brain

Neuroimage. 2016 Dec:143:70-81. doi: 10.1016/j.neuroimage.2016.09.003. Epub 2016 Sep 2.

Abstract

Resting state functional magnetic resonance imaging (rsfMRI) has emerged as a versatile tool for non-invasive measurement of functional connectivity patterns in the brain. RsfMRI brain dynamics in rodents, non-human primates, and humans share similar properties; however, little is known about the resting state functional connectivity patterns in the ferret, an animal model with high potential for developmental and cognitive translational study. To address this knowledge-gap, we performed rsfMRI on anesthetized ferrets using a 9.4T MRI scanner, and subsequently performed group-level independent component analysis (gICA) to identify functionally connected brain networks. Group-level ICA analysis revealed distributed sensory, motor, and higher-order networks in the ferret brain. Subsequent connectivity analysis showed interconnected higher-order networks that constituted a putative default mode network (DMN), a network that exhibits altered connectivity in neuropsychiatric disorders. Finally, we assessed ferret brain topological efficiency using graph theory analysis and found that the ferret brain exhibits small-world properties. Overall, these results provide additional evidence for pan-species resting-state networks, further supporting ferret-based studies of sensory and cognitive function.

Keywords: Default mode network; Ferret; Graph theory; Networks; Resting state; fMRI.

MeSH terms

  • Animals
  • Brain / diagnostic imaging
  • Brain / physiology*
  • Brain Mapping / methods*
  • Female
  • Ferrets / physiology*
  • Magnetic Resonance Imaging / methods*