Mechanisms of simultaneous linear and nonlinear computations at the mammalian cone photoreceptor synapse
Data files
Jun 14, 2023 version files 11.19 GB
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Dataset_MF01.zip
6.16 GB
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Dataset_SF04.zip
1.25 GB
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Dataset_SF06.zip
3.78 GB
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README.md
857 B
Abstract
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.
Methods
Whole-cell patch clamp recording, dual cell, triple, cell, rapid perfusion, capacitance measurements, processed using Igor 8.0 from Wavemetrics
Super-resolution imaging with a Leica SP8 3D-STED microscope processed with Fiji and Imaris 10.0.0 software
MCELL 3.4 Monte Carlo simulation program
Usage notes
Microsoft Excel or similar. Fiji or similar. MCELL 3.4.