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
Stable and aligned spike sorting and decoding over long-term recordings in BCI
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
Synthesising Realistic Calcium Imaging Data of Neuronal Populations Using GAN.
JAX version of vLGP (github.com/catniplab/vlgp)
Total Spiking Probability Edges is a Cross-Correlation based method for effective connectivity estimation of cortical spiking neurons.
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