Differentiable neuron simulations with biophysical detail on CPU, GPU, or TPU.
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Updated
Dec 23, 2024 - Python
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
Code for the paper "Stochastic analysis of the electromagnetic induction effect on a neuron's action potential dynamics"
This repository contains all material related to the course Computational Neuroscience (BT6270) in the Fall 2020 semester.
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.
KU ELEC 436 - Bioelectronics
NEUROFIT is a program that fits Hodgkin-Huxley models to voltage-clamp data.
Homeworks of Neuroscience of Learning, Memory and Cognition, taught by Dr. Hamid Karbalai Aghajan.
A code for simulating neuronal firing under the Hodgkin-Huxley model.
Simulation of a Mathematical Model of Homeostatic Regulation of Sleep-Wake Cycles by Hypocretin/Orexin (Postnova et al., 2009)
an implementation of Hodgkin-Huxley model using python package numpy and brian2
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