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

J Comput Neurosci. 1999 Jan;6(1):27-48. doi: 10.1023/a:1008804916112.


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

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Computer Systems*
  • Cortical Synchronization
  • Membrane Potentials / physiology
  • Neural Inhibition*
  • Neural Networks, Computer*
  • Neurons / physiology
  • Oscillometry
  • Synaptic Transmission / physiology