Unveiling the Odor Representation in the Inner Brain of Drosophila through Compressed Sensing

Abstract

The putative dimension of a space spanned by chemical stimuli is deemed enormous; however, when odorant molecules are bound to a finite number of receptor types and their information is transmitted and projected to a perceptual odor space in the brain, a substantial reduction in dimensionality is made. Compressed sensing (CS) is an algorithm that enables recovery of high-dimensional signals from the data compressed in a lower dimension when the representation of such signals is sufficiently sparse. By analyzing the recent Drosophila connectomics data, we find that the Drosophila olfactory system effectively meets the prerequisites for CS to work. The neural activity profile of projection neurons (PNs) can be faithfully recovered from a low-dimensional response profile of mushroom body output neurons (MBONs) which can be reconstructed using the electro-physiological recordings to a wide range of odorants. By leveraging the residuals calculated between the measured and the predicted MBON responses, we visualize the perceptual odor space by means of residual spectrum and discuss the differentiability of an odor from others. Our study highlights the sparse coding of odor to the receptor space as an essential component for odor identifiability, clarifying the concentration-dependent odor percept. Further, a simultaneous exposure of the olfactory system to many different odorants saturates the neural activity profile of PNs, significantly degrading the capacity of signal recovery, resulting in a perceptual state analogous to "olfactory white." Our study applying the CS to the connectomics data provides novel and quantitative insights into the odor representation in the inner brain of Drosophila.