Data-based PFC-like circuit with layer 2/3 and 5, synaptic clustering, four types of interneurons and cell-type specific short-term synaptic plasticity; neuron parameters fitted to in vitro data, all other parameters constrained by experimental literature. Reproduces key features of in vivo resting state activity without specific tuning.
Model Type: Realistic Network
Region(s) or Organism(s): Prefrontal cortex (PFC)
Cell Type(s): Abstract integrate-and-fire adaptive exponential (AdEx) neuron
Model Concept(s): Activity Patterns; Methods; Laminar Connectivity
Simulation Environment: C or C++ program; MATLAB
Implementer(s): Hass, Joachim [joachim.hass at zi-mannheim.de]; Hertäg, Loreen [loreen.hertaeg at tu-berlin.de]; Durstewitz, Daniel [daniel.durstewitz at plymouth.ac.uk]
References:
Hass J, Hertäg L, Durstewitz D. (2016). A Detailed Data-Driven Network Model of Prefrontal Cortex Reproduces Key Features of In Vivo Activity. PLoS computational biology 12 [PubMed]