Normalized Neural Representations of Complex Odors.

David Zwicker,Hiroaki Matsunami

doi:10.1371/journal.pone.0166456

Abstract

The olfactory system removes correlations in natural odors using a network of inhibitory neurons in the olfactory bulb. It has been proposed that this network integrates the response from all olfactory receptors and inhibits them equally. However, how such global inhibition influences the neural representations of odors is unclear. Here, we study a simple statistical model of the processing in the olfactory bulb, which leads to concentration-invariant, sparse representations of the odor composition. We show that the inhibition strength can be tuned to obtain sparse representations that are still useful to discriminate odors that vary in relative concentration, size, and composition. The model reveals two generic consequences of global inhibition: (i) odors with many molecular species are more difficult to discriminate and (ii) receptor arrays with heterogeneous sensitivities perform badly. Comparing these predictions to experiments will help us to understand the role of global inhibition in shaping normalized odor representations in the olfactory bulb.

Highlights

Sensory systems encode information efficiently by removing redundancies present in natural stimuli [1, 2]
We study a simple model of the olfactory system that resembles its first processing layers, which transform the odor representation successively [16, 17], see Fig 1
Experiments suggest that the activity of projection neurons is concentration-invariant [49, 50] and exhibits more uniform distances between odors [38, 50], indicating that they encode the odor composition efficiently

Summary

Introduction

Sensory systems encode information efficiently by removing redundancies present in natural stimuli [1, 2]. For instance, neighboring regions are likely of similar brightness and the image can be characterized by the regions of brightness changes [3] This structure is exploited by ganglion cells in the retina that respond to brightness gradients by receiving excitatory input from photo receptors in one location and inhibitory input from the surrounding [4]. To arrive at a general model of olfaction that applies to insects and mammals, we chose a simplified description, which focuses on global inhibition, as described This global inhibition leads to normalization, which separates the odor composition from its intensity and encodes it in a sparse representation. The model reveals two generic consequences of global inhibition: (i) odors comprised of many different molecules exhibit sparser representations and should be more difficult to distinguish and (ii) overly sensitive receptors could dominate the sparse responses and arrays with heterogeneous receptors should perform poorly

Simple Model of the Olfactory System

Results

Sparse coding transmits useful information

Larger mixtures have sparser representations

Effective arrays have similar receptor sensitivities

Discussion