Volume 10 Supplement 1

Eighteenth Annual Computational Neuroscience Meeting: CNS*2009

Open Access

Influence of external input on waxing and waning of neuronal network oscillations

  • Oscar J Avella Gonzalez1Email author,
  • Ronald van Elburg2,
  • Huibert Mansvelder1,
  • Jaap van Pelt1 and
  • Arjen van Ooyen1
BMC Neuroscience200910(Suppl 1):P257

DOI: 10.1186/1471-2202-10-S1-P257

Published: 13 July 2009


Experimental observations have reported modulation of cortical oscillations as phases of high synchronization (waxing) followed by periods of reduced synchronization (waning) [13]. Although the phenomenon is present in almost all frequency bands, it is still not understood how this is driven. Here we study whether this phenomenon can occur in a network of inhibitory (I) and excitatory (E) cells and what effect external inputs have.


Using NEURON, we model a network of N e excitatory and N i inhibitory cells such that N e /N i = 4. The cells have a single compartment, and include passive channels and voltage dependent Na+, K+ channels. Synaptic connections are random, projecting GABA synapses from I to I and I to E cells and AMPA synapses from E to E and E to I cells. To stimulate the network, each cell receives a baseline of current and a stream of spikes delivered at random intervals across the simulated period.


We show that in a stable oscillatory network, waxing and waning occurs without the need for other synaptic mechanisms than the spike generating K+ and Na+ channels. The phenomenon can be modulated by changing the characteristics of the external input, such as number of spikes, mean inter-spike interval, randomness and whether E or I cells receive the external input. See figures 1 and 2.
Figure 1

Raster plots of E (top) and I (middle) populations, during waxing and waning of a beta oscillation, and firing rate histograms (bottom).

Figure 2

Wavelet transform of the activity in the E population for the same time period as shown in figure 1.



The work was supported by the EU grant MC-RTN NEURoVERS-it (019247).

Authors’ Affiliations

Department of Integrative Neurophysiology, VU University Amsterdam
Department of Artificial Intelligence, University of Groningen


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© Gonzalez et al; licensee BioMed Central Ltd. 2009

This article is published under license to BioMed Central Ltd.