Abstract

Resting-state networks are spatially distributed, functionally connected brain regions. Studying these networks gives us information about the large-scale functional organization of the brain and alternations in these networks are considered to play a role in a wide range of neurological conditions and aging. To describe resting-state networks in dogs, we measured 22 awake, unrestrained individuals of both sexes and carried out group-level spatial independent component analysis to explore whole-brain connectivity patterns. In this exploratory study, using resting-state functional magnetic resonance imaging (rs-fMRI), we found several such networks: a network involving prefrontal, anterior cingulate, posterior cingulate and hippocampal regions; sensorimotor (SMN), auditory (AUD), frontal (FRO), cerebellar (CER) and striatal networks. The network containing posterior cingulate regions, similarly to Primates, but unlike previous studies in dogs, showed antero-posterior connectedness with involvement of hippocampal and lateral temporal regions. The results give insight into the resting-state networks of awake animals from a taxon beyond rodents through a non-invasive method.

Highlights

  • Resting-state networks are spatially distributed, functionally connected brain regions

  • The structure and assumed tasks of Resting-state networks (RSNs) are of high interest as they have the potential to provide information about the brain’s large scale functional organization[1,3], and alternations in these networks have been found to correspond with various pathologies such as dementia or ADHD4

  • Our goal was to investigate whether applying the currently available methods yield interpretable results with our setup and if so, what kind of spatially distributed resting-state networks are detectable in a larger sample of awake, unrestrained family dogs in a resting-state functional magnetic resonance imaging (fMRI) setup, following up on previous reports[11,13]

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Summary

Introduction

Resting-state networks are spatially distributed, functionally connected brain regions. To describe resting-state networks in dogs, we measured 22 awake, unrestrained individuals of both sexes and carried out group-level spatial independent component analysis to explore wholebrain connectivity patterns. In this exploratory study, using resting-state functional magnetic resonance imaging (rs-fMRI), we found several such networks: a network involving prefrontal, anterior cingulate, posterior cingulate and hippocampal regions; sensorimotor (SMN), auditory (AUD), frontal (FRO), cerebellar (CER) and striatal networks. ICA is appropriate to describe networks in case of a species which brain’s functional characteristics are yet to be determined, as it does not require selection of a priori seed regions This method attempts to discover statistically independent source signals from the measured observations, using non-linear transformations while looking for spatial independence[2]. Our goal was to investigate whether applying the currently available methods yield interpretable results with our setup (proof-of-concept) and if so, what kind of spatially distributed resting-state networks are detectable in a larger sample of awake, unrestrained family dogs in a resting-state fMRI setup, following up on previous reports[11,13]

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