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A Digital Atlas of the Dog Brain

Overview of attention for article published in PLOS ONE, December 2012
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Title
A Digital Atlas of the Dog Brain
Published in
PLOS ONE, December 2012
DOI 10.1371/journal.pone.0052140
Pubmed ID
Authors

Ritobrato Datta, Jongho Lee, Jeffrey Duda, Brian B. Avants, Charles H. Vite, Ben Tseng, James C. Gee, Gustavo D. Aguirre, Geoffrey K. Aguirre

Abstract

There is a long history and a growing interest in the canine as a subject of study in neuroscience research and in translational neurology. In the last few years, anatomical and functional magnetic resonance imaging (MRI) studies of awake and anesthetized dogs have been reported. Such efforts can be enhanced by a population atlas of canine brain anatomy to implement group analyses. Here we present a canine brain atlas derived as the diffeomorphic average of a population of fifteen mesaticephalic dogs. The atlas includes: 1) A brain template derived from in-vivo, T1-weighted imaging at 1 mm isotropic resolution at 3 Tesla (with and without the soft tissues of the head); 2) A co-registered, high-resolution (0.33 mm isotropic) template created from imaging of ex-vivo brains at 7 Tesla; 3) A surface representation of the gray matter/white matter boundary of the high-resolution atlas (including labeling of gyral and sulcal features). The properties of the atlas are considered in relation to historical nomenclature and the evolutionary taxonomy of the Canini tribe. The atlas is available for download (https://cfn.upenn.edu/aguirre/wiki/public:data_plosone_2012_datta).

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Mendeley readers

The data shown below were compiled from readership statistics for 208 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Hungary 3 1%
United States 2 <1%
Italy 1 <1%
Austria 1 <1%
Unknown 201 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 32 15%
Student > Master 24 12%
Student > Ph. D. Student 22 11%
Other 16 8%
Student > Doctoral Student 15 7%
Other 66 32%
Unknown 33 16%
Readers by discipline Count As %
Veterinary Science and Veterinary Medicine 32 15%
Agricultural and Biological Sciences 32 15%
Neuroscience 23 11%
Medicine and Dentistry 18 9%
Psychology 14 7%
Other 51 25%
Unknown 38 18%