Skip to main content

Neuronal network information processing through heterogeneities and resonance frequency shifts

How can groups of neurons selectively encode different memories? We investigated a possible mechanism for the selective activation of regions of a network based on the resonance properties of individual neurons and heterogeneities in the network connectivity. In network simulations of coupled resonate and fire neurons, we incorporated the experimentally observed phenomena of resonance frequency shift based on membrane voltage changes. We aim to understand to what extent the resonance frequency shift allows for the separation of signals. We find that formation of neuronal subgroups, whether through higher connectivity strength or number of connections can lead to different activation properties from the rest of the network.


This work was supported by NSF CMMI 1029388 (MZ), NSF PoLS 1058034 (MZ).

Author information

Authors and Affiliations


Corresponding author

Correspondence to Elizabeth Shtrahman.

Rights and permissions

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Reprints and Permissions

About this article

Cite this article

Shtrahman, E., Zochowski, M. Neuronal network information processing through heterogeneities and resonance frequency shifts. BMC Neurosci 14 (Suppl 1), P361 (2013).

Download citation

  • Published:

  • DOI:


  • Animal Model
  • Information Processing
  • Frequency Shift
  • Neuronal Network
  • Network Connectivity