Implementing multiple Neural Dynamic models of single cell and population models

In this Prject, I’ve implemented several models of Neural Dynamic models of single cell and population models with python.

Hodgkin–Huxley model

The Hodgkin–Huxley model is one of the most recognized models in computational neuroscience. Describing the propagation of an action potential along the squid’s giant axon, the HH model states that the axon carries three ionic currents

leaky-integrate-and-fire

The leaky integrate and fire model which can be traced back to Louis Lapicque, is an idealization of a neuron having ohmic leakage current and a number of voltage-gated currents that are completely deactivated at rest.

Morris-Lecar

The Morris-Lecar model is a two-dimensional “reduced” excitation model applicable to systems having two noninactivating voltage-sensitive conductances (one voltage variable and one gating variable). The original form of the model employed an instantaneously responding voltage-sensitive $Ca^{2+}$ conductance for excitation and a delayed voltage-dependent $K^{+}$ conductance for recovery. The model has three channels: a potassium channel, a leak, and a calcium channel. In the simplest version of the model, the calcium current depends instantaneously on the voltage.

Wilson-Cowan

The Wilson-Cowan model is a powerful yet simple model that describes the interactions between two populations of excitatory and inhibitory neurons. This model is capable of analyzing neural hysteresis phenomena related to binocular vision and is used as a canonical model of visual cortical activity.