Associative properties of structural plasticity based on firing rate homeostasis in recurrent neuronal networks
Abstract: Correlation-based Hebbian plasticity is thought to shape neuronal connectivity during development and learning, whereas homeostatic plasticity would stabilize network activity. Here we investigate another, new aspect of this dichotomy: Can Hebbian associative properties also emerge as a network effect from a plasticity rule based on homeostatic principles on the neuronal level? To address this question, we simulated a recurrent network of leaky integrate-and-fire neurons, in which excitatory connections are subject to a structural plasticity rule based on firing rate homeostasis. We show that a subgroup of neurons develop stronger within-group connectivity as a consequence of receiving stronger external stimulation. In an experimentally well-documented scenario we show that feature specific connectivity, similar to what has been observed in rodent visual cortex, can emerge from such a plasticity rule. The experience-dependent structural changes triggered by stimulation are long-lasting and decay only slowly when the neurons are exposed again to unspecific external inputs
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
Online-Ressource
- Sprache
-
Englisch
- Klassifikation
-
Biowissenschaften, Biologie
- Schlagwort
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Hebbsche Lernregel
Neuronale Plastizität
Plastizität
Dichotomie
Konnektionismus
- Ereignis
-
Veröffentlichung
- (wo)
-
Freiburg
- (wer)
-
Universität
- (wann)
-
2018
- Urheber
- DOI
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10.1038/s41598-018-22077-3
- URN
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urn:nbn:de:bsz:25-freidok-161259
- Rechteinformation
-
Kein Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
25.03.2025, 13:52 MEZ
Datenpartner
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Gallinaro, Júlia V.
- Rotter, Stefan
- Universität
Entstanden
- 2018
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