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This article is part of the supplement: Eighteenth Annual Computational Neuroscience Meeting: CNS*2009

Open Access Poster presentation

Burst firing regulates correlated activity in neurons

Oscar Avila Akerberg12* and Maurice J Chacron123

Author Affiliations

1 Centre for Nonlinear Dynamics in Physiology and Medicine, McGill University, Montreal, QC, H3G1Y6, Canada

2 Department of Physics, McGill University, Montreal, QC, H3A2T8, Canada

3 Department of Physiology, McGill University, Montreal, QC, H3G1Y6, Canada

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BMC Neuroscience 2009, 10(Suppl 1):P189  doi:10.1186/1471-2202-10-S1-P189

The electronic version of this article is the complete one and can be found online at:

Published:13 July 2009

© 2009 Akerberg and Chacron; licensee BioMed Central Ltd.

Poster presentation

Understanding how sensory information is encoded by populations of neurons is complicated by the fact that neurons display variability in their responses to repeated presentations of the same stimulus. A further complication comes from the fact that these variabilities can be correlated. In fact, the role of correlations in neural variabilities (noise correlations) has been the focus of much debate in recent years as even a small amount of correlation between a pair of neurons can have dramatic effects on information transmission by neural populations [1]. Recent experimental evidence has shown that burst firing can modulate the amount of noise correlations displayed by neural populations [2]. Here we investigate the role of intrinsic bursting dynamics in model neurons receiving correlated input. These model neurons transition from a tonic firing regime to a bursting regime as the amount of depolarizing current is varied. We find that, given an input correlation c, the output correlation R between neural pairs in the network is less when both neurons are in bursting regime than when they are in the tonic regime. Our theoretical results are supported by experimental results obtained from a slice preparation. We show that intrinsic burst dynamics can decorrelate neural populations and therefore regulate their information transmission properties.


This work was supported by CONACyT (O. A. A.) and CIHR, CFI and CRC (M. C.).


  1. Schneidman E, Berry MJ II, Segev R, Bialek W: Weak pairwise correlations imply strongly correlated network states in a neural population.

    Nature 2008, 440:1007-1012. Publisher Full Text OpenURL

  2. Chacron MJ, Bastian J: Population coding by electrosensory neurons.

    J Neurophysiol 2008, 99:1825-1835. PubMed Abstract | Publisher Full Text OpenURL