Scientists have "trained" an electronic system to predict the pleasantness of novel odors, just like a human would perceive them, turning on its head the popular notion that smell is completely personal and culture-specific. The scientists, from the Weizmann Institute of Science and Edith Wolfson Medical Center, argue that the perception of an odor's pleasantness is innately hard-wired to its molecular structure, and it is only within specific contexts that personal or cultural differences are made apparent. Details are published April 15 in the open-access journal PLoS Computational Biology.
Over the last decade, electronic devices, commonly known as electronic noses or "eNoses," have been developed to detect and recognize odors. The main component of an eNose is an array of chemical sensors. As an odor passes through the eNose, its molecular features stimulate the sensors in such a way as to produce a unique electrical pattern an "odor fingerprint" that characterizes that specific odor. Like a sniffer dog, an eNose first needs to be trained with odor samples so as to build a database of reference. But unlike humans, if eNoses are presented with a novel odor whose fingerprint has not already been recorded in their database, they are unable to classify or recognize it.
The scientists decided to approach this issue from a different perspective, training the eNose to estimate the odor along an axis of odorant pleasantness In other words, they trained their eNose to predict whether an odor would be perceived as pleasant or unpleasant, or anywhere in between. The scientists stressed that "the uniquness of this approach was that rather than learning singular odorant objects such as "rose" or "skunk", their eNose learned an axis, and could then place novel objects anywhere along the axis it learned".
The scientists first asked a group of native Israelis to rate the pleasantness of a selection of odors according to a 30-point s
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