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


Model Type: Realistic Network

Cell Type(s): Abstract single compartment conductance based cell

Simulation Environment: NEURON; Python

Implementer(s): Tikidji-Hamburyan, Ruben [ruben.tikidji.hamburyan at gmail.com]

References:

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. Journal of neurophysiology. 121 [PubMed]


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