Journal
NEUROIMAGE
Volume 143, Issue -, Pages 70-81Publisher
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2016.09.003
Keywords
Resting state; fMRI; Ferret; Default mode network; Networks; Graph theory
Funding
- UNC Department of Psychiatry
- Human Frontier Science Program [RGY0068/2014]
- National Institute of Mental Health of the National Institutes of Health [R01MH101547]
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Resting state functional magnetic resonance imaging (rsfMRl) has emerged as a versatile tool for noninvasive 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 rsfMRl on anesthetized ferrets using a 9.4 T 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. (C) 2016 Elsevier Inc. All rights reserved.
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