Skip to content

Code and data used in Bordt et al (2019) Synaptic inputs from identified bipolar and amacrine cells to a sparsely branched ganglion cell in rabbit retina

Notifications You must be signed in to change notification settings

neitzlab/RabbitGammaCell

 
 

Repository files navigation

Synaptic inputs from identified bipolar and amacrine cells to a sparsely branched ganglion cell in rabbit retina

Data and code to produce the figures in:

Bordt, A., Perez, D., Tseng, L., Liu, W., Neitz, J., Patterson, S., Famiglietti, E., Marshak, D. (2019). Synaptic inputs from identified bipolar and amacrine cells to a sparsely branched ganglion cell in rabbit retina. Visual Neuroscience, 36, E004

Contents:

  • FullFigures.m - code for the paper figures that were created with SBFSEM-tools. Loads neurons from the existing annotation database.
  • FullFiguresCached.m - same as above but uses the neurons stored as .json files.
  • c13525_synapses.m - code to mark synapses on c13525 (the labels and specialized markers were edited outside Matlab)
  • ReciprocalSynapseAnalysis.m - code used to pull raw data on synapse distances, which was further analyzed outside Matlab.
  • RabbitPaperCache.m - code used to save the neuron data into the .json files.

Use:

The annotation database for the rabbit connectome is edited constantly. While major changes are unlikely, there's no guarantee that the data associated with a given Neuron ID will remain the same long-term. For this reason, the annotations associated with a given neuron are preserved in .json files under the \data folder. You can run the figure code from the cached data with FullFiguresCached.m.

Dependencies:

  • MATLAB 2015b or higher
  • SBFSEM-tools, an open-source Matlab toolbox for connectomics visualization and analysis, used to mine the rabbit connectome developed in the Marc/Jones lab.

More information:

About

Code and data used in Bordt et al (2019) Synaptic inputs from identified bipolar and amacrine cells to a sparsely branched ganglion cell in rabbit retina

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • MATLAB 100.0%