NGC-Learn: Neurobiological Learning and Biomimetic Systems Simulation in Python
-
Updated
Nov 19, 2024 - Python
NGC-Learn: Neurobiological Learning and Biomimetic Systems Simulation in Python
Papers : Biological and Artificial Neural Networks
JAX-based Spiking Neural Network framework
Implementation/simulation of the predictive forward-forward credit assignment algorithm for training neurobiologically-plausible recurrent neural network models.
Forward Pass Learning and Inference Library, for neural networks and general intelligence, Signal Propagation (sigprop)
NeuroMorphic Predictive Model with Spiking Neural Networks (SNN) using Pytorch
A framework for simulating mean-field neural mass models of spiking neurons, comparing them to large network simulations, and predicting electrical stimulation responses of neural populations.
NEST Desktop is a web-based GUI for NEST Simulator and other simulators of spiking networks.
We introduce Local recurrent Predictive coding model termed as Parallel temporal Neural Coding Network. Unlike classical RNNs, our model is pure local and doesn't require computing gradients backward in time; thus computationally more efficient compared to BPTT and can be used for online learning
Code behind the work "Multiple Synaptic Contacts Combined with Dendritic Filtering Enhance Spatio-Temporal Pattern Recognition of Single Neurons", bioRxiv 2022
Implementations of various simulations for integrate and fire models, as well as conductance based models with synaptic neurotransmission
C++ neuron-based neural network library
computational efficacy of a modular spiking neural network as a function of heterogeneity of delay in the network
Biological Neural Network based on Izhikevich Neuron Model
Open documentation hosting for the Neuroblox project
Add a description, image, and links to the biological-neural-networks topic page so that developers can more easily learn about it.
To associate your repository with the biological-neural-networks topic, visit your repo's landing page and select "manage topics."