title: Exploring the retinal connectome.
abstract: OBJECTIVE
  A connectome is a comprehensive description of synaptic connectivity for a neural domain. Our goal was to produce a connectome data set for the inner plexiform layer of the mammalian retina. This paper describes our first retinal connectome, validates the method, and provides key initial findings.
  
  
  METHODS
  We acquired and assembled a 16.5 terabyte connectome data set RC1 for the rabbit retina at ≈ 2 nm resolution using automated transmission electron microscope imaging, automated mosaicking, and automated volume registration. RC1 represents a column of tissue 0.25 mm in diameter, spanning the inner nuclear, inner plexiform, and ganglion cell layers. To enhance ultrastructural tracing, we included molecular markers for 4-aminobutyrate (GABA), glutamate, glycine, taurine, glutamine, and the in vivo activity marker, 1-amino-4-guanidobutane. This enabled us to distinguish GABAergic and glycinergic amacrine cells; to identify ON bipolar cells coupled to glycinergic cells; and to discriminate different kinds of bipolar, amacrine, and ganglion cells based on their molecular signatures and activity. The data set was explored and annotated with Viking, our multiuser navigation tool. Annotations were exported to additional applications to render cells, visualize network graphs, and query the database.
  
  
  RESULTS
  Exploration of RC1 showed that the 2 nm resolution readily recapitulated well known connections and revealed several new features of retinal organization: (1) The well known AII amacrine cell pathway displayed more complexity than previously reported, with no less than 17 distinct signaling modes, including ribbon synapse inputs from OFF bipolar cells, wide-field ON cone bipolar cells and rod bipolar cells, and extensive input from cone-pathway amacrine cells. (2) The axons of most cone bipolar cells formed a distinct signal integration compartment, with ON cone bipolar cell axonal synapses targeting diverse cell types. Both ON and OFF bipolar cells receive axonal veto synapses. (3) Chains of conventional synapses were very common, with intercalated glycinergic-GABAergic chains and very long chains associated with starburst amacrine cells. Glycinergic amacrine cells clearly play a major role in ON-OFF crossover inhibition. (4) Molecular and excitation mapping clearly segregates ultrastructurally defined bipolar cell groups into different response clusters. (5) Finally, low-resolution electron or optical imaging cannot reliably map synaptic connections by process geometry, as adjacency without synaptic contact is abundant in the retina. Only direct visualization of synapses and gap junctions suffices.
  
  
  CONCLUSIONS
  Connectome assembly and analysis using conventional transmission electron microscopy is now practical for network discovery. Our surveys of volume RC1 demonstrate that previously studied systems such as the AII amacrine cell network involve more network motifs than previously known. The AII network, primarily considered a scotopic pathway, clearly derives ribbon synapse input from photopic ON and OFF cone bipolar cell networks and extensive photopic GABAergic amacrine cell inputs. Further, bipolar cells show extensive inputs and outputs along their axons, similar to multistratified nonmammalian bipolar cells. Physiologic evidence of significant ON-OFF channel crossover is strongly supported by our anatomic data, showing alternating glycine-to-GABA paths. Long chains of amacrine cell networks likely arise from homocellular GABAergic synapses between starburst amacrine cells. Deeper analysis of RC1 offers the opportunity for more complete descriptions of specific networks.
authors.affiliation: Department of Ophthalmology, Moran Eye Center, University of Utah, Salt Lake City, UT, USA.
authors.forename: James R
authors.initials: JR
authors.lastname: Anderson
authors.forename: Bryan W
authors.initials: BW
authors.lastname: Jones
authors.forename: Carl B
authors.initials: CB
authors.lastname: Watt
authors.forename: Margaret V
authors.initials: MV
authors.lastname: Shaw
authors.forename: Jia-Hui
authors.initials: JH
authors.lastname: Yang
authors.forename: David
authors.initials: D
authors.lastname: Demill
authors.forename: James S
authors.initials: JS
authors.lastname: Lauritzen
authors.forename: Yanhua
authors.initials: Y
authors.lastname: Lin
authors.forename: Kevin D
authors.initials: KD
authors.lastname: Rapp
authors.forename: David
authors.initials: D
authors.lastname: Mastronarde
authors.forename: Pavel
authors.initials: P
authors.lastname: Koshevoy
authors.forename: Bradley
authors.initials: B
authors.lastname: Grimm
authors.forename: Tolga
authors.initials: T
authors.lastname: Tasdizen
authors.forename: Ross
authors.initials: R
authors.lastname: Whitaker
authors.forename: Robert E
authors.initials: RE
authors.lastname: Marc
mesh_terms: D025042:Amacrine Cells / Q000166:cytology; D000818:Animals; D001331:Automation; D005260:Female; D005998:Glycine / Q000737:chemistry; D006801:Humans; D051379:Mice; D046529:Microscopy, Electron, Transmission / Q000379:methods; D009415:Nerve Net; D009474:Neurons / Q000502:physiology; D020419:Photoreceptor Cells, Vertebrate / Q000166:cytology; D011817:Rabbits; D012160:Retina / Q000378:metabolism* / Q000502:physiology; D013569:Synapses / Q000378:metabolism; D005680:gamma-Aminobutyric Acid / Q000378:metabolism
chemical_list: D005680:gamma-Aminobutyric Acid; D005998:Glycine