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Focused Review ARTICLE

Can attractor network models account for the statistics of firing during persistent activity in prefrontal cortex?

Francesca Barbieri¹ and Nicolas Brunel^1,2,3*

ISI Foundation, Torino, Italy

Laboratoire de Neurophysique et Physiologie, Université Paris Descartes, Paris, France

UMR 8119, CNRS, Paris, France

Persistent activity observed in neurophysiological experiments in monkeys is thought to be the neuronal correlate of working memory. Over the last decade, network modellers have strived to reproduce the main features of these experiments. In particular, attractor network models have been proposed in which there is a coexistence between a non-selective attractor state with low background activity with selective attractor states in which sub-groups of neurons fire at rates which are higher (but not much higher) than background rates. A recent detailed statistical analysis of the data seems however to challenge such attractor models: the data indicates that firing during persistent activity is highly irregular (with an average CV larger than 1), while models predict a more regular firing process (CV smaller than 1). We discuss here recent proposals that allow to reproduce this feature of the experiments.

Keywords:

network model, integrate-and-fi re neuron, working memory, prefrontal cortex, short-term depression

Citation:

Barbieri F and Brunel N (2008). Can attractor network models account for the statistics of firing during persistent activity in prefrontal cortex? Front. Neurosci.2,1: 114-122 doi: 10.3389/neuro.01.003.2008

Received:

29 April 2008;

Paper pending published:

16 May 2008;

Accepted:

16 May 2008;

Published online:

15 July 2008.

Edited by:

Misha Tsodyks, Weizmann Institute of Science, Israel

Reviewed by:

Peter Dayan, University College London, UK

© 2008 Barbieri and Brunel. This is an open-access article subject to an exclusive license agreement between the authors and the Frontiers Research Foundation, which permits unrestricted use, distribution, and reproduction in any medium, provided the original authors and source are credited.

*Correspondence:

Nicolas Brunel, Laboratoire de Neurophysique et Physiologie, Université Paris Descartes, Paris, France; CNRS UMR 8119 45 rue des Saints Peres 75270 Paris Cedex 06. e-mail: nicolas.brunel@univ-paris5.fr