synaptic-plasticity

Convolutional spiking neural network implementing STDP

Convolutional spiking neural network implementing voltage-dependent synaptic plasticity and single-spike integrate-and-fire neurons

Spike-Timing-Dependent Plasticity (STDP) unsupervised Hebbian synaptic learning rule with asymmetric exponential long-term potentiation and depression.

Spike-Timing-Dependent Plasticity (STDP) unsupervised Hebbian synaptic learning rule with asymmetric exponential long-term potentiation and depression.

Neuron++ is a library which wraps NEURON (http://www.neuron.yale.edu) with easy to use Python objects.

Biomimetic cognitive memory system for AI agents, brain-inspired persistence with synaptic plasticity, hybrid PPMI+SVD vector search, LTP/LTD, and inter-agent shared cortex. Pure Python + SQLite, zero heavy dependencies.

Companion code to Confavreux*, Ramesh*, Goncalves, Macke* & Vogels*, Meta-learning families of plasticity rules in recurrent spiking networks using simulation-based inference, NeurIPS 2023

This repository contains my current doctoral research at the University of Manchester

Simulation code for Hashemi, S., and Shafiee, S., and Tetzlaff, C. (2025)."Robust Input Disentanglement Through Dendritic Calcium-Mediated Action Potentials"

Showcases of Spiking Neural Network, which have Synaptic Plasticity

Simulation code for Limbacher, T. and Legenstein, R. (2020). Emergence of Stable Synaptic Clusters on Dendrites Through Synaptic Rewiring

Spiking-network simulations of stable, overlapping neural assemblies learned via dendritic-specific inhibitory gating (Onasch, Miehl et al.).

interactive, sub-16ms vector explainer built for the DataForge 2026 Pathway Track.It proves why classical State Space Models suffer exponential associative forgetting ($\rho(A)^L$) and visualizes how Pathway's Dragon Hatchling (BDH) synaptic plasticity and BDH CQ continuous latent reasoning eliminate interference without KV-cache explosion.

LSTN is an experimental text generation engine that models language not as static probabilities, but as a dynamic and "liquid" neural network. Each trigram (3-character sequence) acts as an individual neuron within a continuous temporal dynamic system.

Biologically inspired STDP neural plasticity simulator with visualizations, tests, and educational examples.

Johnny Silverfly, son of Stonkfly: a fly-connectome spiking network - MaleCNS v1.0, 166,700 neurons, 25.6M connections - wired to a guarded Coinbase trading loop. Kernel and importer adapted from DOOMFLY. Real neural output, real execution guard, no profitable learning demonstrated.

it is my first project, but... It's getting a bit hard to keep going now... I'm looking for someone who can finish this project.

Independent research software for data-free synthetic plasticity modeling. Contributions welcome.

Hybrid long short-term plasticity liquid state machine

Model of the Thalamo-Cortical Microcircuit - Please, refer to the new repository https://github.com/celinesoeiro/TCM-model