leaky-integrate-and-fire-neuron

Energy-efficient Event-driven Spiking Neural Network accelerator for FPGA with PyTorch integration

Basic SNN propogating spikes between LIF neurons

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.

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

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

Simulation of cat V1 simple cell and receptive field.

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

Neuroscience simulator project

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.

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

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

code implementation of neuron models.

Implementation of leaky integrate-and-fire model.

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

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

Leaky Integrate and fire model Example

Simulation-based inference of Leaky Integrate-and-Fire neuron parameters using BayesFlow and neural posterior estimation.