Pure python implementation of SNN
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Updated
Jul 29, 2022 - Python
Pure python implementation of SNN
Dimensionality reduction of spikes trains
RBM implemented with spiking neurons in Python. Contrastive Divergence used to train the network.
Nuerapse simulations for SNNs
Extended edit similarity measurement for high dimensional discrete-time series signal (e.g., multi-unit spike-train).
Spike analysis software
SpikeShip: A method for fast, unsupervised discovery of high-dimensional neural spiking patterns.
imaging, spike trains, information theory, neural circuitry, synaptic, channel properties
Continuous-Time Event-based Transfer Entropy
IASBS Theoretical Neuroscience Group toolbox, to analysis the time series, spike trains and graphs in python.
Python Implementation of GLMCC (generalized linear model for spike cross-correlations)
Inner ear models for Python3
Neural Spike Train Analysis
This MATLAB code allows to semi-automatically classify spontaneous firing neurones according to regularity, grouping of spikes in bursts and firing frequency inter- and intra-burst
Synthesising Realistic Calcium Imaging Data of Neuronal Populations Using GAN.
Spiking Neural network
JAX version of vLGP (github.com/catniplab/vlgp)
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