Neurogenesis Drives Stimulus Decorrelation in a Model of the Olfactory Bulb

TL;DR

This paper presents a computational model demonstrating that adult neurogenesis in the olfactory bulb facilitates stimulus decorrelation, improving odor discrimination and perceptual learning.

Contribution

It shows that neurogenesis, including new inhibitory neuron addition and activity-dependent survival, can adaptively restructure the network for better stimulus decorrelation.

Findings

Neurogenesis reduces correlations between similar odor stimuli.

Model captures the role of neurogenesis in perceptual learning.

Predicts effective odor enrichment strategies.

Abstract

The reshaping and decorrelation of similar activity patterns by neuronal networks can enhance their discriminability, storage, and retrieval. How can such networks learn to decorrelate new complex patterns, as they arise in the olfactory system? Using a computational network model for the dominant neural populations of the olfactory bulb we show that fundamental aspects of the adult neurogenesis observed in the olfactory bulb -- the persistent addition of new inhibitory granule cells to the network, their activity-dependent survival, and the reciprocal character of their synapses with the principal mitral cells -- are sufficient to restructure the network and to alter its encoding of odor stimuli adaptively so as to reduce the correlations between the bulbar representations of similar stimuli. The decorrelation is quite robust with respect to various types of perturbations of the reciprocity. The model parsimoniously captures the experimentally observed role of neurogenesis in perceptual learning and the enhanced response of young granule cells to novel stimuli. Moreover, it makes specific predictions for the type of odor enrichment that should be effective in enhancing the ability of animals to discriminate similar odor mixtures.