Structural adaptation in young neocortical networks modeled by spatially coupled oscillators

The spontaneous synchronous activity in neocortical networks during early development is considered to be a requisite for the maturation of the networks. To analyze the structural adaptation of synaptic connections in large scale area, we simulate the network activity by distributed population models (complex oscillators). In this way we get a spatial distribution of parameters and activity and are able to study effects of local external stimulation and propagation of excitation waves in large network areas. Considering a small world connection strategy most connections are local but there are a number of long range connections, which work as shortcuts and help to synchronize the whole network activity. These long range connections can be used to adapt the network architecture by a Hebbian learning mechanism depending on the intrinsic wavelike network activity and external stimulation.