This is a repository with implementations of neuron models, synapses, and spiking neural networks (SNN). It's still in development and it has original content in terms of code.

python code and jupyter notebooks to reproduce figures from our PLOS Computational Biology paper

Ring attractor network implemented in Python by Stefano, Nikitas, Pranjal and Orion, as part of the Neuromatch Academy 2020 summer school project.

LIF implementation from scratch.

Projects of Computational Neuroscience course in Shahid Beheshti University, CS faculty 2020

Lab Work

Leaky Integrate and fire model Example

Vibe-Coded LIF Simulator for Fruit Fly Connectme

Thesis project covering the development, optimization, and measurement of Spiking Neural Network (SNN) models on STMicroelectronics NUCLEO-N657X0-Q development board. Project compared a set of differing neural network sizes in regard to power efficency when executed on pure CPU contra NPU optimized execution.

Python Leaky Integrate and Fire Tester -- A LIF implementation for learning purposes

Recurrent network of leaky integrate-and-fire neurons

SAiDL Summer of Code Project

This repository contains a collection of computational neuroscience models implemented in MATLAB. The project encompasses various approaches to modeling neural dynamics, from single neuron biophysics to network level interactions, including applications to synaptic plasticity and cognitive disease modeling.