  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.
