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This article is part of the supplement: Seventeenth Annual Computational Neuroscience Meeting: CNS*2008

Open Access Oral presentation

Information flow in local cortical networks is not democratic

Aonan Tang1*, Christopher J Honey2, Jon Hobbs1, Alexander Sher3, Alan M Litke3, Olaf Sporns2 and John M Beggs1*

Author Affiliations

1 Indiana University Department of Physics, Bloomington, IN 47403, USA

2 Indiana University Department of Psychological and Brain Sciences, Bloomington, IN 47403, USA

3 University of California, Santa Cruz Institute for Particle Physics, Santa Cruz, CA 95064, USA

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BMC Neuroscience 2008, 9(Suppl 1):O3  doi:10.1186/1471-2202-9-S1-O3


The electronic version of this article is the complete one and can be found online at: http://www.biomedcentral.com/1471-2202/9/S1/O3


Published:11 July 2008

© 2008 Tang et al; licensee BioMed Central Ltd.

Oral presentation

The average cortical neuron makes and receives about 1,000 – 10,000 synaptic contacts. This anatomical information suggests that local cortical networks are connected in a fairly democratic manner, with all neurons having about the same number of incoming and outgoing connections. But the physical connections found in the cortex do not necessarily reveal how information flows through cortical networks. What is the network diagram for information flow in cortical networks? To investigate this issue, we recorded spontaneous spiking activity at 20 kHz for over 1 hr from organotypic cortex cultures [1] placed on a high-density 512 electrode array with 60 μm interelectrode distance. The high-density array increased the chances that we would record from synaptically connected neurons and allowed us to obtain stable long-term recordings that were essential for accurate estimates of entropy rates [2] and information flow. To measure information flow, we used a new method called transfer entropy [3] that has been shown to accurately identify connections in model networks. Our initial "democratic" hypothesis was that network diagrams of information flow would show all neurons to have approximately equal amounts of incoming and outgoing information flow. Surprisingly, our analysis revealed wide differences in the amount of information flowing into and out of different neurons in the network, indicating that information flow is not "democratically" distributed [4]. These data point to the existence of cells with high information flow that act as highly central hub nodes in the network. Future work combining experiments and simulations will be directed at exploring why local cortical networks assume such non-democratic information flow patterns.

Acknowledgements

This work was supported by NSF grant number 0343636 to JMB, by NSF grant number PHY-0417175 to AML, by the McKnight Foundation to AML, by the Burroughs Wellcome Fund Career Award at the Scientific Interface to AS, by McCormick Science Grant from Indiana University to AT.

References

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  4. Pajek software is available at [http://vlado.fmf.uni-lj.si/pub/networks/pajek/] webcite