Abstract
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.
Highlights
Spontaneous fluctuations in activity in different parts of the brain can be used to study functional brain networks [1]
respiratory rate (RR) varied during Resting-state functional Magnetic Resonance Imaging (rs-functional magnetic resonance imagining (fMRI)) between 10-21/min
This study proves the feasibility of rs-fMRI in anesthetized healthy beagle dogs and documents several brain resting state networks (RSNs), such as default mode network (DMN), primary and higher order visual, auditory, somatosensory and sensory-motor
Summary
Spontaneous fluctuations in activity in different parts of the brain can be used to study functional brain networks [1]. Blood oxygenation level-dependent (BOLD) functional magnetic resonance imagining (fMRI) technique takes advantage of the fact that oxyhaemoglobin is diamagnetic, and de-oxyhaemoglobin is paramagnetic which leads to an increased. Canine resting state fMRI signal intensity in activated brain areas [3]. Resting-state fMRI (rs-fMRI) is based on spontaneous low frequency fluctuations (0.1 Hz) in the BOLD signal when the brain is at rest (not performing any specific task). Studying correlations between variations of the BOLD signal can identify anatomically distinct regions, which activate synchronously with each other, these regions are called “resting state networks” [4]. Resting state networks (RSN) have been identified in many species including rodents [5,6,7], ferrets [8], monkeys [9, 10] and humans [11, 12] and have been extensively used in cognitive neuroscience research [13]
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