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  • Open Access

Neuronal network information processing through heterogeneities and resonance frequency shifts

BMC Neuroscience201314 (Suppl 1) :P361

https://doi.org/10.1186/1471-2202-14-S1-P361

  • Published:

Keywords

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

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.

Declarations

Acknowledgements

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

Authors’ Affiliations

(1)
Department of Physics, University of Michigan, Ann Arbor, MI 48109, USA
(2)
Department of Physics, University of Michigan, Ann Arbor, MI 48109, USA

Copyright

© Shtrahman and Zochowski; licensee BioMed Central Ltd. 2013

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 (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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