Ankur Sinha's discusses the paper, 'Associative properties of structural plasticity based on firing rate homeostasis in a balanced recurrent network of spiking neurons (Gallinaro and Stefan (arxiv pre-print: 2017)'. The abstract is below:
Hebbian and homeostatic plasticity have been studied extensively in the past, both experimentally and theoretically, but many aspects of their interaction remain to be elucidated. Hebbian plasticity is thought to shape neuronal connectivity during development and learning, whereas homeostatic plasticity would stabilize network activity. Here we investigate another aspect of this interaction, which is whether Hebbian associative properties can also emerge as a network effect from a plasticity rule based on homeostatic principles on the neuronal level. The maturation of cortical networks during sensory experience is an ideal case to explore this question. Excitatory neurons in the visual cortex of rodents have been shown to connect preferentially to neurons that respond to similar visual features. Since this connectivity bias is not existent at the time of eye opening, but only after some weeks of visual experience, it has been suggested that plastic mechanisms are responsible for the changes taking place during sensory stimulation. We consider a structural plasticity rule driven by a homeostasis of firing rate in a recurrent network of leaky integrate-and-fire (LIF) neurons exposed to external input that is modulated by the orientation of a visual stimulus. Our results show that feature specific connectivity, similar to what has been experimentally observed in rodent visual cortex, can emerge out of a random balanced network of LIF neurons with a plasticity rule that is not explicitly dependent on correlations between pre- and postsynaptic neuronal activity. The synaptic association of neurons responding to similar stimulus features occurs as a side-effect of controlling the activity of individual neurons. The experience dependent structural changes that are triggered by simulation are long lasting and decay only slowly when the neurons are exposed again to non modulated external input.