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

Open Access Poster presentation

Spike timing – an incomplete description of neural code

Dorian Aur1*, Christopher I Connolly2 and Mandar S Jog1

Author Affiliations

1 Department of Clinical Neurological Sciences, Movement Disorders Program, London, Ontario, Canada

2 SRI International, Menlo Park, CA, USA

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BMC Neuroscience 2007, 8(Suppl 2):P149  doi:10.1186/1471-2202-8-S2-P149

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

Published:6 July 2007

© 2007 Aur et al; licensee BioMed Central Ltd.

Poster presentation

Starting with Hebb's investigations the time domain was an important apparatus to study neuronal activity. Increases or decreases in firing rate, precise spike timing sequences or particular spike time patterns were perceived as the only reliable measures of neural code. Despite considerable efforts and some success, the time approach does not seem to offer responses to several questions. What is the meaning of the time code in terms of behavior? Is the time domain consistent enough to measure complex neuronal activity?

One can answer these questions by measuring spike directivity in neurons as rats learned a T-maze procedural task. Based on in vivo recordings we recently demonstrated that spike time alone does not reflect the richness of neuronal activity [1-3]. Additionally, we showed that the electrical flow has directionality which becomes organized with behavioral learning.

We performed neuron simulations with plausible models of biophysically realistic neurons and demonstrated that mutual information between input signal and sodium flux is about two times that between input signal and output spikes during each spike within a millisecond-level time domain [2]. Consistent with this model and previous analyses we reveal that complex coding occurs in expert neurons and spike directivity analyses are able to reliably predict future animal actions [4]. This important feature in the spatio-temporal domain characterized by subtle changes in spike directivity at certain moments in time represents basic steps towards reading the neural code and marks a final requiem for spike timing era.


  1. Aur D, Connolly CI, Jog MS: Computing spike directivity with tetrodes.

    J Neurosci Methods 2005, 149:57-63. PubMed Abstract | Publisher Full Text OpenURL

  2. Aur D, Connolly CI, Jog MS: Computing information in neuronal spikes.

    Neural Processing Letters 2006, 23:183-199. Publisher Full Text OpenURL

  3. Aur D, Jog MS: Building spike representation in tetrodes.

    J Neurosci Methods 2006, 157:364-373. PubMed Abstract | Publisher Full Text OpenURL

  4. Aur D, Jog MS: Neuronal spatial learning.

    Neural Processing Letters 2007, 25:31-47. Publisher Full Text OpenURL