title: Building retinal connectomes.
abstract: Understanding vertebrate vision depends on knowing, in part, the complete network graph of at least one representative retina. Acquiring such graphs is the business of synaptic connectomics, emerging as a practical technology due to improvements in electron imaging platform control, management software for large-scale datasets, and availability of data storage. The optimal strategy for building complete connectomes uses transmission electron imaging with 2 nm or better resolution, molecular tags for cell identification, open-access data volumes for navigation, and annotation with open-source tools to build 3D cell libraries, complete network diagrams and connectivity databases. The first forays into retinal connectomics have shown that even nominally well-studied cells have much richer connection graphs than expected.
authors.affiliation: University of Utah School of Medicine, Department of Ophthalmology/John A. Moran Eye Center, 65 Mario Capecchi Dr, University of Utah, Salt Lake City, UT 84132, United States.
authors.forename: Robert E
authors.initials: RE
authors.lastname: Marc
authors.forename: Bryan W
authors.initials: BW
authors.lastname: Jones
authors.forename: J Scott
authors.initials: JS
authors.lastname: Lauritzen
authors.forename: Carl B
authors.initials: CB
authors.lastname: Watt
authors.forename: James R
authors.initials: JR
authors.lastname: Anderson
mesh_terms: D000818:Animals; D063132:Connectome; D006801:Humans; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology* / Q000648:ultrastructure; D012160:Retina / Q000033:anatomy & histology*; D014795:Visual Pathways / Q000502:physiology* / Q000648:ultrastructure