  We present a multi-scale spiking network model of all vision-related areas of
macaque cortex that represents each area by a full-scale microcircuit with
area-specific architecture. The layer- and population-resolved network
connectivity integrates axonal tracing data from the CoCoMac database with
recent quantitative tracing data, and is systematically refined using dynamical
constraints. Simulations reveal a stable asynchronous irregular ground state
with heterogeneous activity across areas, layers, and populations. Elicited by
large-scale interactions, the model reproduces longer intrinsic time scales in
higher compared to early visual areas. Activity propagates down the visual
hierarchy, similar to experimental results associated with visual imagery.
Cortico-cortical interaction patterns agree well with fMRI resting-state
functional connectivity. The model bridges the gap between local and
large-scale accounts of cortex, and clarifies how the detailed connectivity of
cortex shapes its dynamics on multiple scales.
