A NN with synaptic depression for testing the effects of connectivity on dynamics (Jacob et al 2019)

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Here we used a 10,000 neuron model. The neurons are a mixture of excitatory and inhibitory integrate-and-fire neurons connected with synapses that exhibit synaptic depression. Three different connectivity paradigms were tested to look for spontaneous transition between interictal spiking and seizure: uniform, small-world network, and scale-free. All three model types are included here.
1 . Jacob T, Lillis KP, Wang Z, Swiercz W, Rahmati N, Staley KJ (2019) A Proposed Mechanism for Spontaneous Transitions between Interictal and Ictal Activity. J Neurosci 39:557-575 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Connectionist Network;
Brain Region(s)/Organism: Mouse; Hippocampus;
Cell Type(s): Abstract integrate-and-fire neuron;
Channel(s): I_K,Na;
Gap Junctions:
Receptor(s): GabaA; Glutamate;
Transmitter(s): Gaba; Glutamate;
Simulation Environment: C or C++ program;
Model Concept(s): Connectivity matrix; Epilepsy;
Implementer(s): Jacob, Theju ;
Search NeuronDB for information about:  GabaA; Glutamate; I_K,Na; Gaba; Glutamate;
CCFLAGS = -std=c++11 -g -fopenmp 

macgregor:main.o layer.o neuron.o
	${COMPILER} ${CCFLAGS} -o macgregor main.o layer.o neuron.o
neuron.o: neuron.cpp neuron.h
	${COMPILER} ${CCFLAGS} -c neuron.cpp  
layer.o: layer.cpp layer.h
	${COMPILER} ${CCFLAGS} -c layer.cpp  
main.o: main.cpp layer.h 
	${COMPILER} ${CCFLAGS} -c main.cpp  
	rm -rf *.o macgregor

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