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This article is part of the supplement: Twentieth Annual Computational Neuroscience Meeting: CNS*2011

Open Access Poster presentation

Different neural codes result in bidirectional connectivity formed by the same model of spike-timing-dependent plasticity

Florian Hauser1*, Andreas Knoblauch2 and Günther Palm1

Author Affiliations

1 Institute of Neural Information Processing, Ulm University, 89069 Ulm, Germany

2 Honda Research Institute EU, 63073 Offenbach/Main, Germany

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BMC Neuroscience 2011, 12(Suppl 1):P247  doi:10.1186/1471-2202-12-S1-P247

The electronic version of this article is the complete one and can be found online at: http://www.biomedcentral.com/1471-2202/12/S1/P247


Published:18 July 2011

© 2011 Hauser et al; licensee BioMed Central Ltd.

This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Poster presentation

Recent studies on phenomenological models of spike-timing-dependent plasticity (STDP) extend the idea of a pure spike-based paradigm to the level of dendritic voltage [1]. In such models, the decision to induce early long-term potentiation (eLTP) or long-term depression (eLTD) not solely depends on the time difference between pre- and post-synaptic spikes but also on the precise dynamics of the post-synaptic potential. From simulations of small neural networks and different stimulation schemes corresponding to different neural codes, these studies have concluded that the pattern of synaptic connectivity would directly follow from the neural code and vice versa. For example, they have suggested that strong uni-directional connectivity would emerge through temporal coding, whereas bidirectional connectivity would be indicative for a rate code. Relying on results from earlier studies on first generation STDP models [2-4], synchronous temporal codes forming bidirectional connectivity patterns were considered unlikely in [1]. However, recent findings revise a general exclusion of this relationship [5] even for first generation STDP models. In particular, our work shows that realistic STDP models as proposed in [1] can actually not predict the neural code (temporal vs. rate coding) by looking at the pattern of synaptic connectivity within a specific brain area. With the same kind of simulations as in [1], but additionally considering stimulation conditions for synchronous temporal coding, we show that bidirectional connections are still possible. Furthermore we discuss the influence of synchronization precision and oscillatory activity.

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