Large-scale topology and the default mode network in the mouse connectome

Significance Noninvasive brain imaging holds great promise for expanding our capabilities of treating human neurologic and psychiatric disorders. However, key limitations exist in human-only studies, and the ability to use animal models would greatly advance our understanding of human brain function...

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Published inProceedings of the National Academy of Sciences - PNAS Vol. 111; no. 52; pp. 18745 - 18750
Main Authors Stafford, James M., Jarrett, Benjamin R., Miranda-Dominguez, Oscar, Mills, Brian D., Cain, Nicholas, Mihalas, Stefan, Lahvis, Garet P., Lattal, K. Matthew, Mitchell, Suzanne H., David, Stephen V., Fryer, John D., Nigg, Joel T., Fair, Damien A.
Format Journal Article
LanguageEnglish
Published United States National Academy of Sciences 30.12.2014
National Acad Sciences
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Summary:Significance Noninvasive brain imaging holds great promise for expanding our capabilities of treating human neurologic and psychiatric disorders. However, key limitations exist in human-only studies, and the ability to use animal models would greatly advance our understanding of human brain function. Mice offer sophisticated genetic and molecular methodology, but correlating these data to functional brain imaging in the mouse brain has remained a major hurdle. This study is the first, to our knowledge, to use whole-brain functional imaging to show large-scale functional architecture with structural correlates in the mouse. Perhaps more important is the finding of conservation in brain topology and default network among rodents and primates, thereby clearing the way for a bridge measurement between human and mouse models. Noninvasive functional imaging holds great promise for serving as a translational bridge between human and animal models of various neurological and psychiatric disorders. However, despite a depth of knowledge of the cellular and molecular underpinnings of atypical processes in mouse models, little is known about the large-scale functional architecture measured by functional brain imaging, limiting translation to human conditions. Here, we provide a robust processing pipeline to generate high-resolution, whole-brain resting-state functional connectivity MRI (rs-fcMRI) images in the mouse. Using a mesoscale structural connectome (i.e., an anterograde tracer mapping of axonal projections across the mouse CNS), we show that rs-fcMRI in the mouse has strong structural underpinnings, validating our procedures. We next directly show that large-scale network properties previously identified in primates are present in rodents, although they differ in several ways. Last, we examine the existence of the so-called default mode network (DMN)—a distributed functional brain system identified in primates as being highly important for social cognition and overall brain function and atypically functionally connected across a multitude of disorders. We show the presence of a potential DMN in the mouse brain both structurally and functionally. Together, these studies confirm the presence of basic network properties and functional networks of high translational importance in structural and functional systems in the mouse brain. This work clears the way for an important bridge measurement between human and rodent models, enabling us to make stronger conclusions about how regionally specific cellular and molecular manipulations in mice relate back to humans.
Bibliography:http://dx.doi.org/10.1073/pnas.1404346111
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Author contributions: J.M.S., B.R.J., G.P.L., K.M.L., S.H.M., S.V.D., J.T.N., and D.A.F. designed research; B.R.J., O.M.-D., B.D.M., N.C., and S.M. performed research; O.M.-D., N.C., and S.M. contributed new reagents/analytic tools; J.M.S., B.R.J., O.M.-D., B.D.M., N.C., S.M., and D.A.F. analyzed data; and J.M.S., B.R.J., O.M.-D., B.D.M., G.P.L., K.M.L., S.H.M., S.V.D., J.D.F., J.T.N., and D.A.F. wrote the paper.
1J.M.S. and B.R.J. contributed equally to this work.
Edited by Marcus E. Raichle, Washington University in St. Louis, St. Louis, MO, and approved November 4, 2014 (received for review March 6, 2014)
ISSN:0027-8424
1091-6490
DOI:10.1073/pnas.1404346111