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This article is part of the supplement: Nineteenth Annual Computational Neuroscience Meeting: CNS*2010

Open Access Poster Presentation

Random wiring limits the development of functional structure in large recurrent neuronal networks

Susanne Kunkel12*, Markus Diesmann234 and Abigail Morrison12

Author Affiliations

1 Functional Neural Circuits, Faculty of Biology, Albert-Ludwig University of Freiburg, Germany

2 Bernstein Center Freiburg, Albert-Ludwig University of Freiburg, Germany

3 RIKEN Brain Science Institute, Wako City, Japan

4 RIKEN Computational Science Research Program, Wako City, Japan

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BMC Neuroscience 2010, 11(Suppl 1):P108  doi:10.1186/1471-2202-11-S1-P108

The electronic version of this article is the complete one and can be found online at: http://www.biomedcentral.com/1471-2202/11/S1/P108


Published:20 July 2010

© 2010 Kunkel et al; licensee BioMed Central Ltd.

Poster Presentation

Spike-timing dependent plasticity (STDP) has traditionally been of great interest to theoreticians, as it seems to provide an answer to the question of how the brain can develop functional structure in response to repeated stimuli. However, despite this high level of interest, convincing demonstrations of this capacity in large, initially random networks have not been forthcoming. Such demonstrations as there are typically rely on constraining the problem artificially. Techniques include employing additional pruning mechanisms or STDP rules that enhance symmetry breaking, simulating networks with low connectivity that magnify competition between synapses, or combinations of the above (see, e.g. [1-3]).

Here, we describe a theory for the stimulus-driven development of feed-forward structures in random networks. The theory explains why the emergence of such structures does not take place in unconstrained systems [4] and enables us to identify candidate biologically motivated adaptations to the balanced random network model that might facilitate it. Finally, we investigate these candidate adaptations in large-scale simulations.

Acknowledgments

Partially supported by the Helmholtz Alliance on Systems Biology, the Next-Generation Supercomputer Project of MEXT, EU Grant 15879 (FACETS), DIP F1.2, and BMBF Grant 01GQ0420 to BCCN Freiburg. Access to HPC provided by JUGENE-Grant JINB33. All network simulations were carried out with NEST (http://www.nest-initiative.org).

References

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