A proposal for a coordinated effort for the determination of brain wide neuroanatomical connectivity in model organisms at a mesoscopic scale

A proposal for a coordinated effort for the determination of brain wide neuroanatomical connectivity in model organisms at a mesoscopic scale

Jason W. Bohland, Caizhi Wu, Helen Barbas, Hemant Bokil, Mihail Bota, Hans C. Breiter, Hollis T. Cline, John C. Doyle, Peter J. Freed, Ralph J. Greenspan, Suzanne N. Haber, Michael Hawrylycz, Daniel G. Herrera, Claus C. Hilgetag, Z. Josh Huang, Allan Jones, Edward G. Jones, Harvey J. Karten, David Kleingeld, Rolf Kotter, Henry A. Lester, John M. Lin, Brett D. Mensh, Shawn Mikula, Jaak Panksepp, Joseph L. Price, Joseph Safdief, Clifford B. Saper, Nicholas D. Schiff, Jeremy D. Schmahmann, Bruce W. Stillman, Karel Svoboda, Larry W. Swanson, Arthur W. Toga, David C. Van Essen, James D. Watson and Partha R. Mitra

PLoS Comput Biol. 5(3):e1000334 (2009)

Abstract

In this era of complete genomes, our knowledge of neuroanatomical circuitry remains surprisingly spare. Such knowledge is critical, however, for both basic and clinical research into brain function. Here we advocate for a concerted effort to fill this gap, through systematic, experimental mapping of neural circuits at a mesoscopic scale of resolution suitable for comprehensive, brainwide coverage, using injections of tracers or viral vectors. We detail the scientific and medical rationale and briefly review existing knowledge and experimental techniques. We define a set of desiderata, including brainwide coverage; validated and extensible experimental techniques suitable for standardization and automation; centralized, open-access data repository; compatibility with existing resources; and tractability with current informatics technology. We discuss a hypothetical but tractable plan for mouse, additonal efforts for the macaque, and technique development for human. We estimate that the mouse connectivity project could be completed within five years with a comparatively modest budget.


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