Emergent oscillations in a realistic network: The role of inhibition and the effect of the spatiotemporal distribution of the input

We have simulated a network of 10,000 two-compartment cells, spatially dist ributed on a two-dimensional sheet; 15% of the cells were inhibitory. The i nput to the network was spatially delimited. Global oscillations frequently were achieved with a simple set of connectivity rules. The inhibitory neur ons paced the network, whereas the excitatory neurons amplified the input, permitting oscillations at low-input intensities. Inhibitory neurons were a ctive over a greater area than excitatory ones, forming a ring of inhibitio n. The oscillation frequency was modulated to some extent by the input inte nsity, as has been shown experimentally in the striate cortex, but predomin antly by the properties of the inhibitory neurons and their connections: th e membrane and synaptic time constants and the distribution of delays. In networks that showed oscillations and in those that did not, widely dist ributed inputs could lead to the specific recruitment of the inhibitory neu rons and to near zero activity of the excitatory cells. Hence the spatial d istribution of excitatory inputs could provide a means of selectively excit ing or inhibiting a target network. Finally, neither the presence of oscill ations nor the global spike activity provided any reliable indication of th e level of excitatory output from the network.