Odor Processing with an experimental model of Olfactory epithelium and bulb
2011 (English)In: Chemical Senses, ISSN 0379-864X, E-ISSN 1464-3553, Vol. 36, no 1, E4-E4 p.Article in journal, Meeting abstract (Other academic) Published
Artificial olfaction was introduced as a model tool to investigateolfaction properties . Nonetheless, the only analogy between the natural and the artificial system lies just in the selectivity proper- ties of the receptors. The implementation of more sophisticated fea- tures such as the large number of receptors and the glomerular layer have been hampered by technical difficulties related to the manage- ment of large numbers of simultaneous signals.As demonstrated in the past, optical imaging is a read-out tech- nique for sensors development that can provide large sensor arrays . On that basis, we recently introduced an artificial olfaction sys- tem based on the imaging of a continuous layer of chemical indi- cators . In this situation an image sensor provides a segmentation of the whole sensing layer in a number of elementary units corre- sponding to the pixels of the image. Eventually, since it is possible to evaluate the optical properties of every single pixel, each pixel of the image may correspond to an individual sensor. In this regard, even low-resolution images may easily result in thousands of independ- ent sensing units.In our system a collection of arbitrarily shaped regions of color indicators is illuminated by a controlled light source; the optical characteristics of each pixel of the image are measured by a camera yielding the light intensities in the three channels red, green, and blue. The combination of illumination sequence and cameraread-out results in a fingerprint encoding the optical properties of the sensing layer portioned in image pixels. Even a simple clas- sification of these fingerprints assigns each pixel to a class, and each class contains pixels carrying the same color indicator. This behav- ior resembles the association between ORNs carrying the same chemical receptors into the same glomerulus . On the basis of this analogy it is straightforward to describe the layer of indicators as an artificial epithelium, pixels of the image as artificial olfactory neu- rons, and the classes provided by the classifier as an abstract rep- resentation of artificial glomeruli.This system thus allows the generation of a complex model of olfaction, including glomerular compartmentalization , which is then applied to data generated by the exposure to pure and mixed gases. Results show that such a model enhances the discrimination of pure and mixed odors. Eventually, such a platform, apart from evidencing the similarities between natural and artificial olfactory systems, is also proposed as a practical tool to test olfactory models.
1. K. Persaud and G. Dodds, Nature 299 (1982) 352
2. Dickinson et al., Nature 382 (1996) 697
3. C. Di Natale et al., PLoS ONE 3 (2008) 3139
4. P. Mombaerts, Annu Rev Neurosci 22 (1999) 487
5. D. Schild and H. Riedel, Biophysical Journal, 61 (1992) 704
Place, publisher, year, edition, pages
Oxford University Press, 2011. Vol. 36, no 1, E4-E4 p.
Engineering and Technology
IdentifiersURN: urn:nbn:se:liu:diva-65954DOI: 10.1093/chemse/bjq126ISI: 000285414900013OAI: oai:DiVA.org:liu-65954DiVA: diva2:400665
20th Congress of European Chemoreception Research Organization (ECRO-2010), Avignon, France, SEP 14-19, 2010