Mechanisms of simultaneous linear and nonlinear computations at the mammalian cone photoreceptor synapse

  • Steven H DeVries (Creator)
  • Chad Grabner (Creator)
  • Daiki Futagi (Creator)
  • Jun Shi (Creator)
  • Vytas Bindokas (Creator)
  • Katsunori Kitano (Creator)
  • Eric Schwartz (Creator)



Neurons enhance their computational power by combining linear and nonlinear transformations in extended dendritic trees. Rich, spatially distributed processing is rarely associated with individual synapses, but the cone photoreceptor synapse may be an exception. Graded voltages temporally modulate vesicle fusion at a cone’s ~20 ribbon active zones. The transmitter then flows into a common, glia-free volume where bipolar cell dendrites are organized by type in successive tiers. Using super-resolution microscopy and tracking vesicle fusion and postsynaptic response at the quantal level in the thirteen-lined ground squirrel, Ictidomys tridecemlineatus, we show that certain bipolar cell types respond to individual fusion events in the stream while other types respond to degrees of locally coincident events, creating a gradient across tiers that are increasingly nonlinear. Nonlinearities emerge from a combination of factors specific to each bipolar cell type including diffusion distance, contact number, receptor affinity, and proximity to transporters. Complex computations related to feature detection begin within the first visual synapse.
Date made available2023

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