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arXiv · 1706.02912

Associative properties of structural plasticity based on firing rate homeostasis in recurrent neuronal networks

Júlia V Gallinaro·Stefan Rotter
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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.

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Júlia V Gallinaro, Stefan Rotter. 2017-06-09. Associative properties of structural plasticity based on firing rate homeostasis in recurrent neuronal networks. https://doi.org/10.1038/s41598-018-22077-3

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