Differentiable neuron simulations with biophysical detail on CPU, GPU, or TPU.

Implementation of a Spiking Neural Network in Tensorflow.

Code for the assignments for the Computational Neuroscience Course BT6270 in the Fall 2018 semester

Neural simulations using Brian2 Python Package

A Hodgkin-Huxley model visualization for a neural tree

Implementation of Neuron-model: Integrate-and-fire, Hodgkin–Huxley, Izhikevich, FitzHugh-Nagumo, Poisson Spike

Implementation of Hodgkin-Huxley Spiking Neuron Model

Modelling Hodgkin-Huxley neural response with dynamic input

Investigates the mechanisms underlying epileptic seizures

Code for the paper "Stochastic analysis of the electromagnetic induction effect on a neuron's action potential dynamics"

Model 3 HH neurons connected in different motifs and different axonal delays. Compute synchronization between spikes and information flow between them.

This repository contains all material related to the course Computational Neuroscience (BT6270) in the Fall 2020 semester.

Physiological Models

Hodgkin and Huxley neuron model using Simulink and MATLAB. The Hodgkin and Huxley model is a mathematical representation of the electrical activity in a neuron, capturing the dynamics of ion channels and membrane potential.

an implementation of Hodgkin-Huxley model using python package numpy and brian2

Large-scale thalamocortical network model for simulating physiological and paroxysmal brain rhythms: version 1

KU ELEC 436 - Bioelectronics

Various Numerical Analysis algorithms for science and engineering.

Functions to plot various parameters of the HH neuron model