Code for the assignments for the Computational Neuroscience Course BT6270 in the Fall 2018 semester
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Updated
Feb 4, 2019 - Jupyter Notebook
Code for the assignments for the Computational Neuroscience Course BT6270 in the Fall 2018 semester
Implementation of a Spiking Neural Network in Tensorflow.
Neural simulations using Brian2 Python Package
This repository contains all material related to the course Computational Neuroscience (BT6270) in the Fall 2020 semester.
A Hodgkin-Huxley model visualization for a neural tree
Functions to plot various parameters of the HH neuron model
Model 3 HH neurons connected in different motifs and different axonal delays. Compute synchronization between spikes and information flow between them.
NEUROFIT is a program that fits Hodgkin-Huxley models to voltage-clamp data.
Large-scale thalamocortical network model for simulating physiological and paroxysmal brain rhythms: version 2
KU ELEC 436 - Bioelectronics
Implementation of Hodgkin-Huxley Spiking Neuron Model
Large-scale thalamocortical network model for simulating physiological and paroxysmal brain rhythms: version 1
an implementation of Hodgkin-Huxley model using python package numpy and brian2
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.
Simulation of a Mathematical Model of Homeostatic Regulation of Sleep-Wake Cycles by Hypocretin/Orexin (Postnova et al., 2009)
Code for the paper "Stochastic analysis of the electromagnetic induction effect on a neuron's action potential dynamics"
A code for simulating neuronal firing under the Hodgkin-Huxley model.
Various Numerical Analysis algorithms for science and engineering.
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