Smelling an odour induces a pattern of sensations, images and memories which participate in identification. It was proposed that perceptual memory performances for odours could be inferred from the description of these olfactory representations. The subject was asked to elaborate an odour descriptor profile, and a short-term odour recognition memory task was chosen to test the individual perceptual memory performance. Two pattern-recognition methods based on artificial neural networks and discriminant analysis were carried out and allowed odour profile and perceptual memory performance to be related. Insofar as the subjects gave dichotomic responses in the recognition memory task, each response could be evaluated in terms of correct or incorrect responses. Simulations indicated that the olfactory recognition memory performance can be predicted in man from odour-elicited semantic profiles by using artificial neural networks. It was also shown that all semantic descriptors do not participate in olfactory recognition to the same degree. Low-level information, such as intensity, familiarity and hedonic judgements, did not allow the artificial neural network to predict the olfactory performance. By contrast, high-level information, such as gustatory, olfactory and visual evocations, allowed artificial networks to make such predictions.
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http://dx.doi.org/10.1093/chemse/21.5.553 | DOI Listing |
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