Reading Out Olfactory Receptors: Feedforward Circuits Detect Odors in Mixtures without Demixing

Neuron
Alexander MathisVenkatesh N Murthy

Abstract

The olfactory system, like other sensory systems, can detect specific stimuli of interest amidst complex, varying backgrounds. To gain insight into the neural mechanisms underlying this ability, we imaged responses of mouse olfactory bulb glomeruli to mixtures. We used this data to build a model of mixture responses that incorporated nonlinear interactions and trial-to-trial variability and explored potential decoding mechanisms that can mimic mouse performance when given glomerular responses as input. We find that a linear decoder with sparse weights could match mouse performance using just a small subset of the glomeruli (∼15). However, when such a decoder is trained only with single odors, it generalizes poorly to mixture stimuli due to nonlinear mixture responses. We show that mice similarly fail to generalize, suggesting that they learn this segregation task discriminatively by adjusting task-specific decision boundaries without taking advantage of a demixed representation of odors.

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Citations

Dec 6, 2016·Nature Neuroscience·Agnieszka Grabska-BarwińskaPeter E Latham
Nov 12, 2016·PloS One·David Zwicker
Jul 6, 2020·Nature Communications·Joseph D ZakVenkatesh N Murthy
Aug 2, 2020·Nature Communications·Naoki Hiratani, Peter E Latham
Jul 10, 2020·Annual Review of Neuroscience·David H Brann, Sandeep Robert Datta
Aug 5, 2018·Nature Communications·Srinath NizampatnamBaranidharan Raman
Dec 18, 2020·Frontiers in Systems Neuroscience·Sapir PenkerDan Rokni

Related Concepts

Metazoa
Discrimination (Process of Differentiation)
Odors
Accessory Olfactory Bulb
Olfactory tubercle
Log-Linear Models
Olfactory Receptor Cells
Receptors, Odorant
Feedback, Biochemical
Complex Extracts

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