Image copyright: CC-BY; Tobias C. Potjans, Markus Diesmann, The Cell-Type Specific Cortical Microcircuit: Relating Structure and Activity in a Full-Scale Spiking Network Model, Cerebral Cortex, Volume 24, Issue 3, March 2014, Pages 785–806, https://doi.org/10.1093/cercor/bhs358
Potjans and Diesmann (2014) describes a microcircuit model of early sensory cortex, displaying asynchronous irregular activity with layer-specific firing rates similar to the activity observed in cortex in the awake spontaneous condition. The inhibitory neurons have higher firing rates than the excitatory neurons, despite being modeled with identical intrinsic properties. Hence, this feature arises due to the connectivity of the network.
Website: Microcircuit Model
Multi Area Model
Image copyright: Fig 1; Schmidt, M., Bakker, R., Hilgetag, C.C. et al. Multi-scale account of the network structure of macaque visual cortex. Brain Struct Funct 223, 1409–1435 (2018). https://doi.org/10.1007/s00429-017-1554-4; Courtesy: S. van Albada
The multi-area model of the vision-related areas of macaque cortex uses the microcircuit model of as a prototype for all 32 areas in the FV91 parcellation and customizes it based on experimental findings on cortical structure. From anatomical studies, it is known that cortical areas in the macaque monkey are heterogeneous in their laminar structure and can be roughly categorized into 8 different architectural types based on cell densities and laminar thicknesses. This distinction was originally developed for prefrontal areas, and then extended to the entire cortex. The visual cortex, and thus the model, comprises areas of categories 2, 4, 5, 6, 7 and 8. Precise layer-specific neuron densities are available for a number of areas, while for other areas, the neuron density is estimated based on their architectural type.
Website: Multi Area Model