hodgkin-huxley

A MATLAB neuron simulator. Very fast (written in C++). Flexible (fully object oriented). Immediate (live manipulation in MATLAB). Comes with a powerful parameter optimizer. Get started ➡️

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

Modelling Hodgkin-Huxley neural response with dynamic input

Curated MATLAB portfolio of reduced-order physiological models in circulation, respiratory mechanics, gas exchange, and feedback control.

An interactive computational neuroscience simulator modeling action potential generation using the Hodgkin-Huxley equations (1952). Built with Python, SciPy (RK45 ODE solver), Plotly, and Streamlit.

The brain and a modern AI system on one ladder of scales — every bridge tagged by evidence, every claim cited to a verified DOI. Real atlases, real neurons, live models.

Comprehensive Computational Neuroscience course materials (NYCU LSNS30045). Includes Python-based implementations of neural encoding models, spike-triggered averages, LIF & Hodgkin-Huxley simulations, with lecture notes, homework, and real neural data.

Code and data for the preprint "Smooth Surrogate Models Approve Impossible Firing Patterns." A smooth surrogate of a Hodgkin-Huxley f-I curve silently certifies firing rates the real neuron cannot produce (the Type-II gap and depolarization block); a feasibility screen against the true f-I removes the failure.

Open-source framework predicting ultrasound neuromodulation: transcranial acoustic field to per-voxel neural firing maps, via mechanosensitive ion channels, intramembrane cavitation, and a multi-pathway Hodgkin-Huxley neuron.

Comparative analysis of Hodgkin-Huxley and Morris-Lecar neuronal membrane models using dynamical systems theory and numerical simulations.

Computational neuroscience and learning models in MATLAB: Hodgkin-Huxley, Izhikevich, Hopfield, perceptron, K-means, PCA, STA, PETH

Real Allen Cell Types patch-clamp data plus Hodgkin-Huxley neural excitability simulator.

Code to explore gating variables and simulate an action potential using the equations from the 1952 Hodgkin-Huxley paper, "A quantitative description of membrane current and its application to conduction and excitation in nerve"

This repository contains the basic bio-physical models as part of the course.

Computational cognitive neuroscience coursework spanning behavioral reinforcement learning, EEG analysis, neural dynamics, and fMRI GLM analysis at the University of Tehran.