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  Self-organization in balanced state networks by STDP and homeostatic plasticity

Effenberger, F., Jost, J., & Levina, A. (2015). Self-organization in balanced state networks by STDP and homeostatic plasticity. PLoS Computational Biology, 11(9): e1004420. doi:10.1371/journal.pcbi.1004420.

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 Urheber:
Effenberger, Felix, Autor
Jost, Jürgen, Autor
Levina, Anna1, Autor           
Affiliations:
1Department of Nonlinear Dynamics, Max Planck Institute for Dynamics and Self-Organization, Max Planck Society, ou_2063286              

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 Zusammenfassung: Structural inhomogeneities in synaptic efficacies have a strong impact on population response dynamics of cortical networks and are believed to play an important role in their functioning. However, little is known about how such inhomogeneities could evolve by means of synaptic plasticity. Here we present an adaptive model of a balanced neuronal network that combines two different types of plasticity, STDP and synaptic scaling. The plasticity rules yield both long-tailed distributions of synaptic weights and firing rates. Simultaneously, a highly connected subnetwork of driver neurons with strong synapses emerges. Coincident spiking activity of several driver cells can evoke population bursts and driver cells have similar dynamical properties as leader neurons found experimentally. Our model allows us to observe the delicate interplay between structural and dynamical properties of the emergent inhomogeneities. It is simple, robust to parameter changes and able to explain a multitude of different experimental findings in one basic network.

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Sprache(n): eng - English
 Datum: 2015-09-03
 Publikationsstatus: Online veröffentlicht
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 Ort, Verlag, Ausgabe: -
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 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: DOI: 10.1371/journal.pcbi.1004420
BibTex Citekey: EffenbergerJostLevina2015
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Titel: PLoS Computational Biology
Genre der Quelle: Zeitschrift
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Ort, Verlag, Ausgabe: -
Seiten: 30 Band / Heft: 11 (9) Artikelnummer: e1004420 Start- / Endseite: - Identifikator: -