Tag Archives: connectome

Ultrastructural Connectomics Reveals The Entire Chemical And Electrical Synaptic Cohort Of An ON Cone Bipolar Cell In The Inner Plexiform Layer Of The Rabbit Retina

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This abstract was presented at the 2014 Society for Neuroscience meeting in Washington D.C. by J. Scott Lauritzen, Crystal L. Sigulinsky, Danny P. Emrich, Joshua M. Dudleston, Noah T. Nelson, Rebecca L. Pfeiffer, Nathan R. Sherbotie, John V. Hoang, Jefferson R. Brown, Carl B. WattJames R. Anderson, Bryan W. Jones and Robert E. Marc.

Purpose: Despite large-scale efforts aimed at mapping the mammalian nervous system, the entire synaptic cohort of a single mammalian neuron of any class has never been mapped. To this end we reconstructed all chemical and electrical synaptic partners of a single ON cone bipolar cell (ON CBC) in the inner plexiform layer (IPL) of the rabbit retina. We then searched all members of the same cell class for repeating network motifs and explored postsynaptic cell sampling topologies from this bipolar cell (BC).

Methods: Cells in retinal connectome 1 (RC1) were annotated with Viking viewer, and explored via graph visualization of connectivity and 3D rendering (Anderson et al., 2011 J Microscopy). Small molecule signals in RC1, e.g. GABA, glycine, and L-glutamate, combined with morphological reconstruction and connectivity analysis allow robust cell classification. The default resolution of RC1 is 2.18nm/pixel, however goniometric recapture at 0.273 nm/pixel was performed as needed for synapse verification.

Results: ON CBC 593 is one of 20 BCs of this class in RC1, the axonal arbors of which tile with gap junctions between nearest neighbors at their distal axonal tips. ON CBC 593 contains 194 ribbons, 274 postsynaptic densities, 20 gap junctions, and 66 conventional synapses, for a total of 554 synaptic connections. Twenty ganglion cells sample the glutamatergic output. ON CBC 593 is presynaptic to 262 amacrine cell (AC) processes, and is postsynaptic to 228 AC processes. Of these, 33% form reciprocal connections. We approximate that ON CBC 593 forms synapses with 50 distinct ACs. ON CBC 593 is routinely pre- and postsynaptic to within-class, cross-class, feedback, and feedforward inhibition motifs, including 1 instance of OFF-ON crossover inhibition. ON CBC 593 forms 12 gap junctions with at least 2 AII ACs, 7 with 5 ON CBCs, and 1 with itself. We searched for repeating network motifs across all ON CBCs of this class in RC1. Thus far, 80% of these form in-class inhibitory motifs, and 75% form cross-class inhibitory motifs. All ACs and GCs discovered to contact multiple branches of ON CBC 593 form synapses on every branch.

Conclusions: An individual bipolar cell is inherently multi-kinetic, receiving inhibition driven by all ON CBC classes, sharing these signals via gap junctions with ON CBCs of the same class, and driving inhibition of all ON CBC classes. This constitutes a substrate for multi-channel coordination throughout the IPL, and predicts multi-kinetic BC responses. The results establish a normative framework against which members of the same and different classes may be compared, and foster interpretation of BC physiological behavior under different stimulus regimes.

The AII Amacrine Cell Connectome: A Dense Network Hub

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We have a new publication in Frontiers in Neuroscience, The AII Amacrine Cell Connectome: A Dense Network Hub.  Authors are Robert E. MarcJames R. Anderson, Bryan W. Jones, Crystal Sigulinsky and J. Scott Lauritzen.

Abstract:  The mammalian AII retinal amacrine cell is a narrow-field, multistratified glycinergic neuron best known for its role in collecting scotopic signals from rod bipolar cells and distributing them to ON and OFF cone pathways in a crossover network via a combination of inhibitory synapses and heterocellular AII::ON cone bipolar cell gap junctions. Long considered a simple cell, a full connectomics analysis shows that AII cells possess the most complex interaction repertoire of any known vertebrate neuron, contacting at least 28 different cell classes, including every class of retinal bipolar cell. Beyond its basic role in distributing rod signals to cone pathways, the AII cell may also mediate narrow-field feedback and feedforward inhibition for the photopic OFF channel, photopic ON-OFF inhibitory crossover signaling, and serves as a nexus for a collection of inhibitory networks arising from cone pathways that likely negotiate fast switching between cone and rod vision. Further analysis of the complete synaptic counts for five AII cells shows that (1) synaptic sampling is normalized for anatomic target encounter rates; (2) qualitative targeting is specific and apparently errorless; and (3) that AII cells strongly differentiate partner cohorts by synaptic and/or coupling weights. The AII network is a dense hub connecting all primary retinal excitatory channels via precisely weighted drive and specific polarities. Homologs of AII amacrine cells have yet to be identified in non-mammalians, but we propose that such homologs should be narrow-field glycinergic amacrine cells driving photopic ON-OFF crossover via heterocellular coupling with ON cone bipolar cells and glycinergic synapses on OFF cone bipolar cells. The specific evolutionary event creating the mammalian AII scotopic-photopic hub would then simply be the emergence of large numbers of pure rod bipolar cells.

 

A Synaptic Basis for Small World Network Design in the ON Inner Plexiform Layer of the Rabbit Retina

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This abstract was presented today at the 2014 Association for Research in Vision and Opthalmology (ARVO) meetings in Orlando, Florida by J Scott Lauritzen, Noah T. Nelson, Crystal L. Sigulinsky, Nathan Sherbotie, John Hoang, Rebecca L. PfeifferJames R. Anderson, Carl B. Watt, Bryan W. Jones and Robert E. Marc.

Purpose: Converging evidence suggests that large- and intermediate-scale neural networks throughout the nervous system exhibit small world’ design characterized by high local clustering of connections yet short path length between neuronal modules (Watts & Strogatz 1998 Nature; Sporns et al.2004 Trends in Cog Sci). It is suspected that this organizing principle scales to local networks (Ganmor et al. 2011 J Neurosci; Sporns 2006 BioSystems) but direct observation of synapses and local network topologies mediating small world design has not been achieved in any neuronal tissue. We sought direct evidence for synaptic and topological substrates that instantiate small world network architectures in the ON inner plexiform layer (IPL) of the rabbit retina. To test this we mined ≈ 200 ON cone bipolar cells (BCs) and ≈ 500 inhibitory amacrine cell (AC) processes in the ultrastructural rabbit retinal connectome (RC1).

Methods: BC networks in RC1 were annotated with the Viking viewer and explored via graph visualization of connectivity and 3D rendering (Anderson et al. 2011 J Microscopy). Small molecule signals embedded in RC1 e.g. GABA glycine and L-glutamate combined with morphological reconstruction and connectivity analysis allow for robust cell classification. MacNeil et al. (2004 J Comp Neurol) BC classification scheme used for clarity.

Results: Homocellular BC coupling (CBb3::CBb3 CBb4::CBb4 CBb5::CBb5) and within-class BC inhibitory networks (CBb3 → AC –| CBb3 CBb4 → AC –| CBb4 CBb5 → AC –| CBb5) in each ON IPL strata form laminar-specific functional sheets with high clustering coefficients. Heterocellular BC coupling (CBb3::CBb4 CBb4::CBb5 CBb3::CBb5) and cross-class BC inhibitory networks (CBb3 → AC –| CBb4 CBb4 → AC –| CBb3 CBb4 → AC –| CBb5 CBb5 → AC –| CBb4 CBb3 → AC –| CBb5 CBb5 → AC –| CBb3) establish short synaptic path lengths across all ON IPL laminae.

Conclusions: The retina contains a greater than expected number of synaptic hubs that multiplex parallel channels presynaptic to ganglion cells. The results validate a synaptic basis (ie. direct synaptic connectivity) and local network topology for the small world architecture indicated at larger scales providing neuroanatomical plausibility of this organization for local networks and are consistent with small world design as a fundamental organizing principle of neural networks on multiple spatial scales.

Support:  NIH EY02576 (RM), NIH EY015128 (RM), NSF 0941717 (RM), NIH EY014800 Vision Core (RM), RPB CDA (BWJ), Thome AMD Grant (BWJ).

Retinal connectomics: A New Era For Connectivity Analysis in The New Visual Neurosciences

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We have a new publication, this one a chapter titled: Retinal connectomics: A New Era For Connectivity Analysis in The New Visual Neurosciences (A little cheaper on Amazon here) textbook.  Authors are Robert E. Marc, Bryan W. Jones, James S. Lauritzen, Carl B. Watt and James R. Anderson.

Retinal Connectomics: Toward Complete, Accurate Networks

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We have a new publication, Retinal connectomics: Toward complete, accurate networks in Progress in Retinal and Eye Research.  Authors are:  Robert E. Marc, Bryan W. JonesCarl B. Watt, Crystal Sigulinsky, James R. Anderson and J. Scott Lauritzen.

Abstract:
Connectomics is a strategy for mapping complex neural networks based on high-speed automated electron optical imaging, computational assembly of neural data volumes, web-based navigational tools to explore 1012-1015 byte (terabyte to petabyte) image volumes, and annotation and markup tools to convert images into rich networks with cellular metadata. These collections of network data and associated metadata, analyzed using tools from graph theory and classification theory, can be merged with classical systems theory, giving a more completely parameterized view of how biologic information processing systems are implemented in retina and brain. Networks have two separable features: topology and connection attributes. The first findings from connectomics strongly validate the idea that the topologies complete retinal networks are far more complex than the simple schematics that emerged from classical anatomy. In particular, connectomics has permitted an aggressive refactoring of the retinal inner plexiform layer, demonstrating that network function cannot be simply inferred from stratification; exposing the complex geometric rules for inserting different cells into a shared network; revealing unexpected bidirectional signaling pathways between mammalian rod and cone systems; documenting selective feedforward systems, novel candidate signaling architectures, new coupling motifs, and the highly complex architecture of the mammalian AII amacrine cell. This is but the beginning, as the underlying principles of connectomics are readily transferrable to non-neural cell complexes and provide new contexts for assessing intercellular communication.