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Theory and simulation of integrate-and-fire neurons driven by shot noise (Droste & Lindner 2017)
 
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Model File
Accession:
228604
This archive contains source code for the paper "Exact analytical results for integrate-and-fire neurons driven by excitatory shot noise" by Droste and Lindner, 2017. Specifically, it contains a Python implementation of the analytical formulas derived in that paper (allowing to calculate firing rate, CV and stationary voltage distribution of general integrate-and-fire neurons driven by excitatory shot noise, as well as power spectrum and rate-response of leaky integrate-and-fire neurons with such input) and C++ code implementing a Monte-Carlo simulation to estimate these quantities. A sample Jupyter notebook to play around with the analytics is included, as are scripts to reproduce the figures from the paper.
Reference:
1 .
Droste F, Lindner B (2017) Exact analytical results for integrate-and-fire neurons driven by excitatory shot noise
J. Comp. Neurosci.
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Model Information
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Model Type:
Brain Region(s)/Organism:
Cell Type(s):
Abstract integrate-and-fire leaky neuron;
Abstract theta neuron;
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment:
C or C++ program;
Python;
Model Concept(s):
Implementer(s):
Droste, Felix [fedro at posteo.de];
/
shotnoise_analytics
analytics
data
grace_plot
latex_param_values
param_scan
plots
simulation
README
generate_plots.sh
LICENSE
parameters
*
Other models using parameters:
Theory and simulation of integrate-and-fire neurons driven by shot noise (Droste & Lindner 2017)
qif_diff_app.sim
run_make_view_into
run_simulation
run_simulations.sh
shotnoise_examples.ipynb
shotnoise_examples.ipynb'
shotnoise_examples.ipynb'A=0
shotnoise_examples.ipynb''A=0
sn_fpt_theo.sim
sn_sig.sim
sn_spont.sim
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