# Coupled Oscillators as a model of Olfactory Network. Importance in Pattern Recognition and Classification tasks

## TL;DR

This paper models the olfactory system using coupled oscillators, highlighting the role of bifurcations and synapse plasticity in pattern recognition and memory functions within olfactory networks.

## Contribution

It introduces a novel application of subthreshold Hopf bifurcations to model olfactory bulb and cortex dynamics, emphasizing the importance of network topology and synaptic plasticity.

## Key findings

- Subthreshold Hopf bifurcation effectively models olfactory bulb oscillations.
- Subcritical bifurcation captures olfactory cortex behavior.
- Network topology analysis underscores synaptic plasticity's role in memory.

## Abstract

The olfactory system is constantly solving pattern-recognition problems by the creation of a large space to codify odour representations and optimizing their distribution within it. A model of the Olfactory Bulb was developed by Z. Li and J. J. Hopfield Li and Hopfield (1989) based on anatomy and electrophysiology. They used nonlinear simulations observing that the collective behavior produce an oscillatory frequency. Here, we show that the Subthreshold hopf bifurcation is a good candidate for modeling the bulb and the Subthreshold subcritical hopf bifurcation is a good candidate for modeling the olfactory cortex. Network topology analysis of the subcritical regime is presented as a proof of the importance of synapse plasticity for memory functions in the olfactory cortex.