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Imaging of Functional Connectivity in the Mouse Brain

Overview of attention for article published in PLOS ONE, January 2011
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Title
Imaging of Functional Connectivity in the Mouse Brain
Published in
PLOS ONE, January 2011
DOI 10.1371/journal.pone.0016322
Pubmed ID
Authors

Brian R. White, Adam Q. Bauer, Abraham Z. Snyder, Bradley L. Schlaggar, Jin-Moo Lee, Joseph P. Culver

Abstract

Functional neuroimaging (e.g., with fMRI) has been difficult to perform in mice, making it challenging to translate between human fMRI studies and molecular and genetic mechanisms. A method to easily perform large-scale functional neuroimaging in mice would enable the discovery of functional correlates of genetic manipulations and bridge with mouse models of disease. To satisfy this need, we combined resting-state functional connectivity mapping with optical intrinsic signal imaging (fcOIS). We demonstrate functional connectivity in mice through highly detailed fcOIS mapping of resting-state networks across most of the cerebral cortex. Synthesis of multiple network connectivity patterns through iterative parcellation and clustering provides a comprehensive map of the functional neuroarchitecture and demonstrates identification of the major functional regions of the mouse cerebral cortex. The method relies on simple and relatively inexpensive camera-based equipment, does not require exogenous contrast agents and involves only reflection of the scalp (the skull remains intact) making it minimally invasive. In principle, fcOIS allows new paradigms linking human neuroscience with the power of molecular/genetic manipulations in mouse models.

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Mendeley readers

The data shown below were compiled from readership statistics for 335 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 12 4%
Germany 3 <1%
Japan 3 <1%
United Kingdom 2 <1%
Taiwan 1 <1%
Brazil 1 <1%
Canada 1 <1%
Korea, Republic of 1 <1%
Unknown 311 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 82 24%
Researcher 76 23%
Professor > Associate Professor 26 8%
Student > Master 24 7%
Professor 22 7%
Other 66 20%
Unknown 39 12%
Readers by discipline Count As %
Neuroscience 80 24%
Agricultural and Biological Sciences 72 21%
Engineering 46 14%
Medicine and Dentistry 40 12%
Physics and Astronomy 12 4%
Other 31 9%
Unknown 54 16%