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

(Spaghetti) Implementation of Hodgkin-Huxley Spiking Neuron Model

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

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

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

Modelling Hodgkin-Huxley neural response with dynamic input

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.

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

Physiological Models

KU ELEC 436 - Bioelectronics

Model of Motor Network during Parkinson's Disease and Deep Brain Stimulation. The model simulates LFP, EMG and associated force signals from the motor system. A multivariable adaptive control strategy is implemented in the model to control two biomarkers of Parkinsonian tremor and motor impairment symptoms.

Homeworks of Neuroscience of Learning, Memory and Cognition, taught by Dr. Hamid Karbalai Aghajan.

Various Numerical Analysis algorithms for science and engineering.

Python scripts supporting a tutorial on the Hodgkin-Huxley model.

A code for simulating neuronal firing under the Hodgkin-Huxley model.