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Telluride 2021 - NMC21: Neuromodulation Control resources

This repository provides the code for defining and simulating a software model of the NeuroDyn hardware (T. Yu and G. Cauwenberghs, 2010), as well as Hodgkin-Huxley-type conductance-based models and their networks.

The repository also contains Jupyter notebooks that provide a guide to building and simulating neural networks using either the NeuroDyn or Hodgkin-Huxley neuronal models.

Model Definitions

cb_models.py

The file provides the main model definitions for NeuroDyn and Hodgkin-Huxley type neurons, as well as for defining arbitrary neural networks using the two models.

Fitting Utilities

fitting_utilities.py

The file provides the class and the methods for mapping the parameters of a Hodgkin-Huxley-type neuron to the parameters of the NeuroDyn software model.

Notebooks

Notebook 1 - Designing excitable behaviors

Designing excitable behaviors.ipynb

This notebook offers an introduction to designing and controlling spiking and bursting behaviors using a simplified neuronal model described in Neuromodulation of Neuromorphic Circuits and Neuromorphic Control. The model definitions used by this notebook are contained in iv_model.py.

Additional resources for this model are provided at https://github.com/lukaribar/Circuit-Neuromodulation.

Notebook 2 - NeuroDyn Python model

NeuroDyn Python model.ipynb

This notebook provides a guide to using the Python model of a NeuroDyn circuit, along with the environment for simulating and fitting Hodgkin-Huxley-type conductance-based models.

Notebook 3 - Complex biophysical models in NeuroDyn

Complex biophysical models in NeuroDyn.ipynb

This notebook provides a guide to interconnecting elementary Hodgkin-Huxley circuits in order to build more complex neuronal behavior such as burst firing.

Notebook 4 - Networks in NeuroDyn

Networks in NeuroDyn.ipynb

This notebook provides a guide to defining networks using Hodgkin-Huxley and NeuroDyn models.

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