Email updates

Keep up to date with the latest news and content from BMC Neuroscience and BioMed Central.

This article is part of the supplement: Sixteenth Annual Computational Neuroscience Meeting: CNS*2007

Open Access Poster presentation

How specific is synchronous neuronal firing?

Wei Wu1* and Gordon Pipa23

Author Affiliations

1 Frankfurt International Graduate School for Science, 60438 Frankfurt, Germany

2 Frankfurt Institute for Advanced Studies, 60438 Frankfurt am Main, Germany

3 Max-Planck-Institute for Brain Research, 60528 Frankfurt am Main, Germany

For all author emails, please log on.

BMC Neuroscience 2007, 8(Suppl 2):P50  doi:10.1186/1471-2202-8-S2-P50


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


Published:6 July 2007

© 2007 Wu and Pipa; licensee BioMed Central Ltd.

Background

Synchronous neuronal firing has been discussed as a potential neuronal code. For testing first, if synchronous firing exists, second if it is modulated by the behaviour, and third if it is not by chance, a large set of tools has been developed. However, to test whether synchronous neuronal firing is really involved in information processing one needs a direct comparison of the amount of synchronous firing for different factors like experimental or behavioural conditions. To this end we present an extended version of a previously published method NeuroXidence [1], which tests, based on a bi- and multivariate test design, whether the amount of synchronous firing above the chance level is different for different factors.

Methods

In order to make a spike rate correction of an observed amount of joint-spike-event (JSE), we define two time scales: 1. τc, which defines the fine-temporal cross-structure of interest and is equal to the assumed temporal extension of JSE (~5 ms), 2. τr, which is η times slower than τc and equal to a lower bound of rate changes (τr = η* τc,η~5). Using τc and τr the chance amount of JSE is derived based on surrogate data. The latter is generated by random jittering of all spikes in each individual original spike train by an amount smaller than τr. Hence, jittering destroys the fine-temporal cross-structure but maintains any other properties of each spike train like the full auto-structure and rate co-variation. Next we compute for each trial (m) and each factor (i) the difference between the amount of JSE in the original and jittered spike train Δfm,i. To assess if Δfm,i is different for different factors, we use a bi-, and multivariate test (Mann-Whitney, Kruskawalis).

Results

We demonstrate based on toy data that the bi- and multivariate version of NeuroXidence is a conservative and reliable method for detecting modulations in the synchronous firing across different experimental factors. To this end we used various scenarios that had been discussed to induce false positives like rate changes and rate co-variations, low rates and different forms of renewal processes. Furthermore we show results based on simultaneous recordings from awake monkeys performing a short term memory paradigm, that modulations of synchronous firing are correlated to behavior and task conditions.

Acknowledgements

This work was supported by the Hertie foundation.

References

  1. Pipa G, Riehle A, Grün S: Validation of task-related excess of spike coincidences based on NeuroXidence.

    Neurocomputing 2007, 70:2064-2068. Publisher Full Text OpenURL