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pyconto
... microscale Connectomics, for
example in combining neural networks and their spiking activity (or any other quantifiable change ...
important examples of applications where the issue of network dynamics arises.
Understanding the dynamics of networked systems ...
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polychronization
... Neuron.cpp file for a concise implementation of a spiking neuron (also following Izhikevich).
The following picture visualizes ... spike representation is moderately slow, but especially the network representation is meant for sparse networks (every neuron ...
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mcpstdp
Recurrent spiking sequence learning neural network
COMPILING
=========
javac net/pakl/levy/*java
RUNNING
=======
The following command executed a simulation that learns a sequence specified by a settings file called "levy.prop" in the current ...
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bain
... (neuromodulator functionality coming soon). The framework is designed
for spiking neuron models and plastic synapses, but can also be ... automatically. Thus to add a new
model of a neural network component, one only need extend the appropriate base
...
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brian
... Brian2 instead.
============ B R I A N =============================
A clock-driven simulator for spiking neural networks
====================================================
Version: 1.4.4
Authors:
Romain Brette
http://romainbrette.fr
Dan ...
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LFPy
... fields, as described in the publication "Multimodal modeling of neural network activity: computing LFP, ECoG, EEG and MEG ... and Customizable Testbench Simulator for Ground-truth Extracellular Spiking Activity. Neuroinform (2020). https://doi.org/10.1007/ ...
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pyN
... (pronounced 'pine') is a python module for simulating spiking neural networks.
- Simulate a network of aforementioned neurons.
- Uses Matplotlib for visualization of ...
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