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

## TL;DR

This study demonstrates that a homeostatic firing rate-based structural plasticity rule can induce associative connectivity patterns in recurrent neuronal networks, resembling experimental observations in visual cortex.

## Contribution

It shows that Hebbian-like associative properties can emerge from a purely homeostatic plasticity rule in simulated recurrent networks.

## Key findings

- Within-group connectivity increases with external stimulation.
- Feature-specific connectivity emerges similar to rodent visual cortex.
- Structural changes are long-lasting and decay slowly without specific input.

## 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.