Mesoscopic dynamics from AdEx recurrent networks (Zerlaut et al JCNS 2018) (PyNN)

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Accession:264597
PyNN simulations for Zerlaut et al 2018).
Reference:
1 . Zerlaut Y, Chemla S, Chavane F, Destexhe A (2018) Modeling mesoscopic cortical dynamics using a mean-field model of conductance-based networks of adaptive exponential integrate-and-fire neurons. J Comput Neurosci 44:45-61 [PubMed]
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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 integrate-and-fire adaptive exponential (AdEx) neuron;
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: PyNN; Python;
Model Concept(s): Vision;
Implementer(s): Soler, Amelie [amelie.soler at gmail.com];
 
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simulations_JCNS_2018
simulation1
FS_cell.png
input.png
RS_cell.png
single_cells.py
                            
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