Scientific article
Open access

Resting state networks of the canine brain under sevoflurane anaesthesia

Published inPLOS ONE, vol. 15, no. 4, e0231955
Publication date2020

Resting-state functional Magnetic Resonance Imaging (rs-fMRI) has become an established technique in humans and reliably determines several resting state networks (RSNs) simultaneously. Limited data exist about RSN in dogs. The aim of this study was to investigate the RSNs in 10 healthy beagle dogs using a 3 tesla MRI scanner and subsequently perform group-level independent component analysis (ICA) to identify functionally connected brain networks. Rs-fMRI sequences were performed under steady state sevoflurane inhalation anaesthesia. Anaesthetic depth was titrated to the minimum level needed for immobilisation and mechanical ventilation of the patient. This required a sevoflurane MAC between 0.8 to 1.2. Group-level ICA dimensionality of 20 components revealed distributed sensory, motor and higher-order networks in the dogs' brain. We identified in total 7 RSNs (default mode, primary and higher order visual, auditory, two putative motor-somatosensory and one putative somatosensory), which are common to other mammals including humans. Identified RSN are remarkably similar to those identified in awake dogs. This study proves the feasibility of rs-fMRI in anesthetized dogs and describes several RSNs, which may set the basis for investigating pathophysiological characteristics of various canine brain diseases.

  • Anesthetics, Inhalation/administration & dosage
  • Animals
  • Brain/diagnostic imaging/physiology
  • Brain Mapping
  • Dogs
  • Female
  • Humans
  • Image Processing, Computer-Assisted
  • Magnetic Resonance Imaging
  • Male
  • Sevoflurane/administration & dosage
Citation (ISO format)
BECKMANN, Katrin M et al. Resting state networks of the canine brain under sevoflurane anaesthesia. In: PLOS ONE, 2020, vol. 15, n° 4, p. e0231955. doi: 10.1371/journal.pone.0231955
Main files (1)
Article (Published version)
ISSN of the journal1932-6203

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