The olfactory system uses the responses of a small number of broadly sensitive receptors to combinatorially encode a vast number of odors. Here, we propose a method for decoding such a distributed representation. Our main idea is that a receptor that does not respond to an odor carries more information than a receptor that does, because a typical receptor binds to many odorants. So a response below threshold signals the absence of all such odorants. As a result, it is easier to identify what the odor is not, rather than what the odor is. We demonstrate that, for biologically realistic numbers of receptors, response functions, and odor mixture complexity, this remarkably simple method of elimination turns an underdetermined decoding problem into an overdetermined one, allowing accurate determination of the odorants in a mixture and their concentrations. We give a simple neural network realization of our algorithm which resembles the known circuit architecture of the piriform cortex .
The olfactory system uses responses of a small number of broadly sensitive receptors to combinatorially encode a vast number of odors. Here, we propose a method for decoding such a distributed representation. Our main idea is that a receptor that does not respond to an odor carries more information than a receptor that does, because a typical receptor binds to many odorants. So a response below threshold signals absence of all such odorants. As a result, it is easier to identify what the odor is not, rather than what the odor is. We demonstrate that, for biologically realistic numbers of receptors, response functions, and odor mixture complexity, this remarkably simple method of elimination turns an underdetermined decoding problem into an overdetermined one, allowing accurate determination of odorants in a mixture and their concentrations. We give a simple neural network realization of our algorithm resembling the circuit architecture in piriform cortex, and propose experimental tests .
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which resembles the known circuit architecture of the piriform cortex
resembling the circuit architecture in piriform cortex, and propose experimental tests