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Universal Laws For Smell Hard-Wired In Brain? Print E-mail
SciMed - Neuroscience
TS-Si News Service   
Sunday, 01 June 2008 18:00
The scent of something.
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Rehovot, Israel. Women refer to the smell of testosterone; this is an especially common occurence for HBS females following transition. Men generally catch a female's biological scent of estrogen before turning their attention to other womanly aspects. But how do we know the difference? Is the smell of almonds closer to that of roses or bananas? Scientists have answered that question (roses) by showing that smells can be mapped and the relative distance between various odors determined.
 
The findings of researchers at the Weizmann Institute of Science, appearing in Nature Methods, may help scientists to unravel the basic laws underlying our sense of smell, as well as potentially enabling odors to be digitized and transferred via computer in the future.
 

A metric for odorant comparison. Rafi Haddad, Rehan Khan, Yuji K Takahashi, Kensaku Mori, David Harel, Noam Sobel. Nature Methods 5(5), 425-429 (2008). doi: 10.1038 / nmeth.1197.

 
No such physical relationship had been discovered for smells, in part because odor molecules are much more difficult to pin down than sound frequencies.We know the musical note do is farther from la than from re on a scale — not only because our ears tell us the distance is greater, but because their frequencies are farther apart.
 
No such physical relationship had been discovered for smells, in part because odor molecules are much more difficult to pin down than sound frequencies.
 
To create their smell map, the scientists began with 250 odorants and generated, for each, a list of around 1,600 chemical characteristics. From this dataset, the researchers created a multidimensional map of smells that revealed the distance between one odor molecule and another.
 
Eventually, they pared the list of traits needed to situate an odor on the map down to around 40. They then checked to see whether the brain recognizes this map, similar to the way it recognizes musical scales.
 
They reexamined numerous previously published studies that measured the neural response patterns to smells in a variety of lab animals — from fruit flies to rats — and found that across all the species, the closer any two smells were on the map, the more similar the neural patterns.
 
The scientists also tested 70 new odors by predicting the neural patterns they would arouse and running comparisons with the unpublished results of olfaction experiments done at the University of Tokyo. They found that their predictions closely matched the experimental results.
 
These findings lend support to the scientist’s theory that, contrary to the commonly held view that smell is a subjective experience, there are universal laws governing the organization of smells, and these laws determine how our brains perceive them.
 


The principal Weizmann research team consisted of Rafi Haddad, a graduate student with Prof. Noam Sobel in the Neurobiology Department, Prof. David Harel of the Computer Science and Applied Mathematics Department, and their colleague Rehan Khan.

Prof. Noam Sobel’s research is supported by the Nella and Leon Benoziyo Center for Neurosciences; the J&R Foundation; and the Eisenberg Keefer Fund for New Scientists.

Prof. David Harel’s research is supported by the Arthur and Rochelle Belfer Institute of Mathematics and Computer Science; and the Henri Gutwirth Fund for Research.

Prof. Harel is the incumbent of the William Sussman Professorial Chair.

 


A metric for odorant comparison. Rafi Haddad, Rehan Khan, Yuji K Takahashi, Kensaku Mori, David Harel, Noam Sobel. Nature Methods 5(5), 425-429 (2008). doi: 10.1038 / nmeth.1197.

Abstract. In studies of vision and audition, stimuli can be systematically varied by wavelength and frequency, respectively, but there is no equivalent metric for olfaction. Restricted odorant-feature metrics such as number of carbons and functional group do not account for response patterns to odorants varying along other structural dimensions. We generated a multidimensional odor metric, in which each odorant molecule was represented as a vector of 1,664 molecular descriptor values. Revisiting many studies, we found that this metric and a second optimized metric were always better at accounting for neural responses than the specific metric used in each study. These metrics were applicable across studies that differed in the animals studied, the type of olfactory neurons tested, the odorants applied and the recording methods used. We use this new metric to recommend sets of odorants that span the physicochemical space for use in olfaction experiments.

 
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Last Updated on Wednesday, 11 June 2008 19:20