A simple generative model of the mouse mesoscale connectome

Sid Henriksen, Rich Pang, Mark Wronkiewicz
2016 eLife  
Recent technological advances now allow for the collection of vast data sets detailing the intricate neural connectivity patterns of various organisms. Oh et al. (2014) recently published the most complete description of the mouse mesoscale connectome acquired to date. Here we give an in-depth characterization of this connectome and propose a generative network model which utilizes two elemental organizational principles: proximal attachment ‒ outgoing connections are more likely to attach to
more » ... arby nodes than to distant ones, and source growth ‒ nodes with many outgoing connections are likely to form new outgoing connections. We show that this model captures essential principles governing network organization at the mesoscale level in the mouse brain and is consistent with biologically plausible developmental processes.
doi:10.7554/elife.12366 pmid:26978793 pmcid:PMC4807721 fatcat:3pzqjvzibffrpp6pogxufl2ahi