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Journal of Computational Neuroscience

, Volume 35, Issue 2, pp 187–199 | Cite as

A working memory model for serial order that stores information in the intrinsic excitability properties of neurons

  • Eduardo Conde-Sousa
  • Paulo AguiarEmail author
Article

Abstract

Models for temporary information storage in neuronal populations are dominated by mechanisms directly dependent on synaptic plasticity. There are nevertheless other mechanisms available that are well suited for creating short-term memories. Here we present a model for working memory which relies on the modulation of the intrinsic excitability properties of neurons, instead of synaptic plasticity, to retain novel information for periods of seconds to minutes. We show that it is possible to effectively use this mechanism to store the serial order in a sequence of patterns of activity. For this we introduce a functional class of neurons, named gate interneurons, which can store information in their membrane dynamics and can literally act as gates routing the flow of activations in the principal neurons population. The presented model exhibits properties which are in close agreement with experimental results in working memory. Namely, the recall process plays an important role in stabilizing and prolonging the memory trace. This means that the stored information is correctly maintained as long as it is being used. Moreover, the working memory model is adequate for storing completely new information, in time windows compatible with the notion of “one-shot” learning (hundreds of milliseconds).

Keywords

Working memory Serial order Intrinsic excitability modulation Delay period Match enhancement Short-term memory 

Notes

Acknowledgments

Research funded by the European Regional Development Fund through the programme COMPETE and by the Portuguese Government through the FCT - Fundação para a Ciência e a Tecnologia under the project PEst-C/MAT/UI0144/2011. Eduardo Conde-Sousa was supported by the grant SFRH/BD/65633/2009 from FCT, co-financed by European Social Fund under the program POPH of the National Strategic Reference Framework.

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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.Faculdade de CiênciasUniversidade do PortoPortoPortugal
  2. 2.Centro de Matemática da Universidade do PortoPortoPortugal

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