Vijay Singh, CNI postdoc

What the odor is not: Estimation by elimination

Our olfactory system detects a large variety of odors using a receptor repertoire whose size is much smaller than the number of types of behaviorally relevant odorants. Recent results from compressive sensing show that the olfactory system has the capacity to detect sparse natural odors, but the decoding scheme through which this can be done is unclear. In this talk, I will describe a method to estimate the composition of complex odors from the response of olfactory receptors. I will show that the proposed scheme works well for a large range of biologically relevant parameters (number of the odorants, number of olfactory receptors, and sparsity of natural odors), and estimates complex odors correctly with probability approaching one. The main idea behind the decoding scheme is that it is much easier to identify what the odor is not, rather than what the odor is. This is because, since a typical receptor binds to many odorants, if its response is zero, it signals the absence of all such odorants in the odor mixture. Thus, with just a few non-responding receptors, one can identify most of the odorants that are not present in the mixture. The concentrations of the rest of the odorants can be estimated from the remaining receptors. The details of the decoding scheme depend on the model of odor encoding at the receptor, as I will explain in the talk. The known properties of the olfactory system support our decoding scheme. I will provide a neural network model to implement this decoder in the olfactory cortex.

A pizza lunch will be served.