Characterization of Structural Connectivity of the Default Mode Network in Dogs using Diffusion Tensor Imaging
Robinson, Jennifer L.
Katz, Jeffrey S.
Denney, Thomas S.
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CitationRobinson, Jennifer L., Madhura Baxi, Jeffrey S. Katz, Paul Waggoner, Ronald Beyers, Edward Morrison, Nouha Salibi, Thomas S. Denney, Vitaly Vodyanoy, and Gopikrishna Deshpande. 2016. “Characterization of Structural Connectivity of the Default Mode Network in Dogs using Diffusion Tensor Imaging.” Scientific Reports 6 (1): 36851. doi:10.1038/srep36851. http://dx.doi.org/10.1038/srep36851.
AbstractDiffusion tensor imaging (DTI) provides us an insight into the micro-architecture of white-matter tracts in the brain. This method has proved promising in understanding and investigating the neuronal tracts and structural connectivity between the brain regions in primates as well as rodents. The close evolutionary relationship between canines and humans may have spawned a unique bond in regard to social cognition rendering them useful as an animal model in translational research. In this study, we acquired diffusion data from anaesthetized dogs and created a DTI-based atlas for a canine model which could be used to investigate various white matter diseases. We illustrate the application of this atlas by calculating DTI tractography based structural connectivity between the anterior cingulate cortex (ACC) and posterior cingulate cortex (PCC) regions of the default mode network (DMN) in dogs. White matter connectivity was investigated to provide structural basis for the functional dissociation observed between the anterior and posterior parts of DMN. A comparison of the integrity of long range structural connections (such as in the DMN) between dogs and humans is likely to provide us with new perspectives on the neural basis of the evolution of cognitive functions.
Citable link to this pagehttp://nrs.harvard.edu/urn-3:HUL.InstRepos:29625984
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