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Custom spiking neuron simulation code for modelling the neurobiology of olfactory learning and context dependent recall in Drosophila.

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Spiking Neural Simulation of Larval Drosophila Learning

author: Konstantinos Lagogiannis 2016

Description

Custom spiking neuron code used as a framework to research and validate hypothesis on neurobiology and behaviour of learning and recall in Drosophila Larvae.

It comprises of a set of C++ classes that implemend different type of Spiking Neuron Models, as well as Spike-Timing Dependent Plasticity rules for learning. In main.cpp these are connected in a configurations that capture the anatomical details as revealed by electron microscopy in the Mushroom body output network of the larval Drosophila brain.
The code in STPD_mod.cpp tests/validates Long-Term Potentiation / Depression synaptic learning can be repreoduced by the model.

Neurons implemented:

* IFNeuron : Integrate and Fire Neuron
* CFSNeuron : Izhikevich Fast spiking  neuron
* CRSNeuron : Izhikevich Regular Spiking  neuron 
* PoissonSource : A Poisson type spiking neuron

Synaptic learning rules:

* synapseSW :Implements the individual Synaptic switch as described in the Appleby & Elliot 2005 STPD paper
* synapseEnsemble collection of individual SW synapses. The Ensemble propagates spike events to synapses,
* synapticTransmission :  Handles the dynamics of synaptic transmission due to a pre synaptic spike event. 

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This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

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Custom spiking neuron simulation code for modelling the neurobiology of olfactory learning and context dependent recall in Drosophila.

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