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


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.

Model Type: Realistic Network; Spiking neural network

Region(s) or Organism(s): Barrel cortex

Cell Type(s): Abstract Izhikevich neuron; Barrel cortex L2/3 pyramidal cell

Model Concept(s): Long-term Synaptic Plasticity; Action Potentials; Synaptic Integration; Synaptic Plasticity; Calcium dynamics; Sensory coding; Spike Frequency Adaptation; Spatial connectivity

Simulation Environment: NetPyNE

Implementer(s): Zeldenrust, Fleur [fleurzeldenrust at gmail.com]; Huang, Chao; Celikel, T

References:

Huang C, Zeldenrust F, Celikel T. (2022). Cortical Representation of Touch in Silico Neuroinformatics. 20 [PubMed]


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