Realistic barrel cortical column - NetPyNE (Huang et al., 2022)

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Reconstructed rodent barrel cortical column (thalamic filter-and-fire input, L4 and L2/3 spiking neurons) based on measured distributions, so each run will create a different connectivity). Includes 13 types of inhibitory and excitatory neurons, implemented as Izhikevich neurons. Includes both a Matlab and a Python (NetPyNe) implementation.
1 . Huang C, Zeldenrust F, Celikel T (2022) Cortical Representation of Touch in Silico Neuroinformatics [PubMed]
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Model Type: Realistic Network; Spiking neural network;
Brain Region(s)/Organism: Barrel cortex;
Cell Type(s): Abstract Izhikevich neuron; Barrel cortex L2/3 pyramidal cell;
Gap Junctions:
Simulation Environment: NetPyNE;
Model Concept(s): Long-term Synaptic Plasticity; Action Potentials; Synaptic Integration; Synaptic Plasticity; Calcium dynamics; Sensory coding; Spike Frequency Adaptation; Spatial connectivity;
Implementer(s): Zeldenrust, Fleur [fleurzeldenrust at]; Huang, Chao; Celikel, T;
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