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Phase response theory in sparsely + strongly connected inhibitory NNs (Tikidji-Hamburyan et al 2019)

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Accession:239177

Reference:
1 . Tikidji-Hamburyan RA, Leonik CA, Canavier CC (2019) Phase response theory explains cluster formation in sparsely but strongly connected inhibitory neural networks and effects of jitter due to sparse connectivity. J Neurophysiol 121:1125-1142 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism:
Cell Type(s): Abstract single compartment conductance based cell;
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON; Python;
Model Concept(s):
Implementer(s): Tikidji-Hamburyan, Ruben [ruben.tikidji.hamburyan at gmail.com] ;
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JNeurophy-2019
PIR-EInetwork
PIR-Inetwork
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