NGC-Learn: Neurobiological Systems Design and Simulation in Python
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Updated
Aug 8, 2025 - Python
NGC-Learn: Neurobiological Systems Design and 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
NEST Desktop is a web-based GUI for NEST Simulator and other simulators of spiking networks.
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.
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
Implementations of various simulations for integrate and fire models, as well as conductance based models with synaptic neurotransmission
Code behind the work "Multiple Synaptic Contacts Combined with Dendritic Filtering Enhance Spatio-Temporal Pattern Recognition of Single Neurons", bioRxiv 2022
C++ neuron-based neural network library
computational efficacy of a modular spiking neural network as a function of heterogeneity of delay in the network
Enabling Scalable Online Learning in Biological Neural Networks.
Biological Neural Network based on Izhikevich Neuron Model
tensorflow-engram: A Python package for Engram Neural Networks, adding biologically-inspired Hebbian memory and engram layers to TensorFlow/Keras models, supporting memory traces, plasticity, attention, and sparsity for neural sequence learning.
Open documentation hosting for the Neuroblox project
SMC-ABC for network inference, illustrated on N populations of the JRNMMs
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