Basic SNN propogating spikes between LIF neurons

FPGA based Leaky Integrate and Fire (LIF) neuron model accelerator for PyTorch

Interactive Matplotlib Plots in Python, convering Models such as the Leaky Integrate and Fire, Izhikevich Model, FitzHugh-Nagumo Model etc...

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.

Implementation of some of the basic neural models and simulation of interactions between neurons in a population and learning process from scratch in Python.

Neuromorphic event-driven simulator in C and MPI (successor of NeMo https://github.com/markplagge/NeMo)

Simulation of cat V1 simple cell and receptive field.

A collection of artificial neuron models. Written in Julia using Jupyter Notebooks

Neuroscience simulator project

Investigation of spiking patterns in Leaky Integrate-and-Fire (LIF) neurons under constant, linear, floor, random, and sinusoidal current inputs, with and without noise.

Implementation of leaky integrate-and-fire model.

code implementation of neuron models.

Quantum-inspired Leaky Integrate-and-Fire (QLIF) neurons for PyTorch, adaptive thresholds, dynamic spike probabilities, synaptic plasticity, neuromodulation, and optional qubit-based spike decisions.

A repository implementing a biologically inspired spiking neural network for psychological profiling. This project uses my own "QLIF-Neurons" by incorporating feedback and cross‐connections among key brain regions (e.g., prefrontal cortex, amygdala, hippocampus, thalamus, and striatum) and integrates text‐based emotion analysis.

Leaky Integrate and fire model Example

Project done as part of the course Intro to Neural and Cognitive Modelling at IIIT-H

This repository contains classes to simulate single and networks of Leaky-Integrate-and-Fire (LIF) neurons.

Computational model of leaky integrate and fire (LIF) neurons in 1D and 2D.