Biological Machines/Sensory Systems/Olfactory System/Signal Processing

From Wikibooks, open books for an open world
Jump to: navigation, search
Examples of olfactory thresholds[1].
Substance mg/L of Ari
Ethyl ether 5.83
Chloroform 3.30
Pyridine 0.03
Oil of peppermint 0.02
lodoform 0.02
Butyric acid 0.009
Propyl mercaptan 0.006
Artificial musk 0.00004
Methyl mercaptan 0.0000004

Only substances which come in contact with the olfactory epithelium can excite the olfactory receptors. The right table shows thresholds for some representative substances. These values give an impression of the huge sensitivity of the olfactory receptors.

It is remarkable that humans can recognize more than 10'000 different odors. Many odorant molecules differ only slightly in their chemical structure (e.g. stereoisomers) but can nevertheless be distinguished.

Signal Transduction[edit]

An interesting feature of the olfactory system is that a simple sense organ which apparently lacks a high degree of complexity can mediate discrimination of more than 10'000 different odors. On the one hand this is made possible by the huge number of different odorant receptor. The gene family of the olfactory receptor is in fact the largest family studied so far in mammals. On the other hand, the neural net of the olfactory system provides with its 1800 glomeruli a large two dimensional map in the olfactory bulb that is unique to each odorant. In addition, the extracellular field potential in each glomerulus oscillates, and the granule cells appear to regulate the frequency of the oscillation. The exact function of the oscillation is unknown, but it probably also helps to focus the olfactory signal reaching the cortex [2].

Smell measurement[edit]

Olfaction consists of a set of transformations from physical space of odorant molecules (olfactory physicochemical space), through a neural space of information processing (olfactory neural space), into a perceptual space of smell (olfactory perceptual space) [3]. The rules of these transforms depend on obtaining valid metrics for each of those spaces.

Olfactory perceptual space[edit]

As the perceptual space represent the “input” of the smell measurement, it’s aim is to describe the odors in the most simple possible way. Odor are ordered so that their reciprocal distance in space confers them similarity. This mean that the more two odors are near each other in this space the more are they expected to be similar. This space is thus defined by so called perceptual axes characterized by some arbitrarily chosen “unit” odors.

Olfactory neural space[edit]

As suggested by its name the neural space is generated from neural responses. This gives rise to an extensive database of odorant-induced activity, which can be used to formulate an olfactory space where the concept of similarity serves as a guiding principle. Using this procedure different odorants are expected to be similar if they generate a similar neuronal response. This database can be navigated at the Glomerular Activity Response Archive [4].

Olfactory physicochemical space[edit]

The need to identify the molecular encryption of the biological interaction, makes the physicochemical space the most complex one of the olfactory space described so far. R. Haddad suggest that one possibility is to span this space would to represent each odorant by a very large number of molecular descriptors by use either a variance metric or a distance metric[3]. In his first description single odorants may have many physicochemical features and one expects these features to present themselves at various probabilities within the world of molecules that have a smell. In such metric the orthogonal basis generated from the description of the odorant leads to represent each odorant by a single value. While in the second, the metric represents each odorant with a vector of 1664 values, on the basis of Euclidean distances between odorants in the 1664 physicochemical space. Whereas the first metric enabled the prediction of perceptual attributes, the second enabled the prediction of odorant-induced neuronal response patterns.

Electronic measurement of odors[edit]

Nowadays odors can be measured electronically in a huge amount of different ways, some examples are: mass spectrography, gas chromatography, raman spectra and most recently electronic noses. In general they assume that different olfactory receptors have different affinities to specific molecular physicochemical properties, and that the different activation of these receptors gives rise to a spatio-temporal pattern of activity that reflects odors.

Electronic Nose[edit]

E-noses are artificial odor sensing devices based on a chemosensor array and pattern recognition. They are used to identify and quantify substances dissolved in air (or other carrier substances). An e-nose consists of a sampling device (analog to the nose), a sensor array (analog to the olfactory receptor neurons) and a computing unit (analog to the brain).

Sensor arrays[edit]

Like in the animal noses, unspecific sensors are used. This is not only due to the fact that it is very hard to find very specific sensors, but one also wants to cover a huge range of possible compounds without a sensor for each of them. Furthermore it is more robust, precise and efficient if the processing is based on information of more than one sensor. Such Sensors experience a change in their electrical properties (E.g. higher resistance) when they come in contact with a compound. This alteration leads to a voltage change that is digitized (AD Converter). The most frequently used sensor types include metal oxide semiconductors (MOS), quartz crystal microbalances (QCM), conducting polymers (CP) and surface acoustic wave (SAW) sensors. A promising technique are also bioelectronics noses that use proteins as sensors. It is also possible to use a combination of different sensors to get a more precise result and to combine the advantages of several sensor types, like e.g better temporal responsivity versus better sensitivity.

Example: working principle of a conducting polymer sensor[edit]

A conducting polymer sensor consists of an array of about 2-40 different conducting polymers (long chains of organic molecules). Some odor molecules permeate into the polymer film and cause the film to expand thereby increasing its resistance. This increase in resistance of many polymer types can be explained by percolation theory [5]. Due to the chemical properties of the materials, different polymers react differently to the same odor.

Computation[edit]

The sensor signal has to be matched to an odorant mixture with a pattern recognition algorithm. It is possible to create a database of potential combinations and find the best match with multivariate statistical methods when an odor is presented or a neural network can be trained to recognize the patterns. Often also principal component analysis is used to reduce the dimensionality of the sensor data.

Applications[edit]

There are many applications for e-noses. They are used in aerospace and other industry to detect and monitor hazardous or harmful substances and for quality control. Possible applications in security are drug or explosive detection. E-noses may someday be able to replace police dogs. A very powerful application could be the diagnosis of diseases that alter the chemical composition of breath or the smell of excretions or blood, thereby potentially substituting invasive diagnostic techniques. It can also be employed to diagnose cancer, as certain cancer cells can be identified by their volatile organic compound profile. Cancer diagnosis by smell has already been found to work with dogs, flies [6] and e-noses [7], but practically suitable methods with high sensitivity and specificity are still under development. Another medical application is the treatment of anosmia (inability to perceive odor) by an olfactory implant on basis of an e-nose. This too is still in development. In contrast, e-noses are already in use for environmental monitoring and protection. In robotics, e-noses could be used to follow airborne smells or smells on the ground. Especially for robotics it would be very interesting to have a better understanding of the insect’s olfactory system, since, in order to use the smell to navigate or to locate odor sources the often neglected temporal stimulus information has to be used.

Insects can follow odors as they can react to changes within about 150 milliseconds, and some of their receptors are able to depict fast odor concentration changes that occur in frequencies above at least 10 Hz. In contrast, conducting polymer as well as metal oxide e-noses have response times in the range of seconds to minutes [5] with only few exceptions reported in the range of tens of milliseconds.

  1. Ganong, W. F., & Barrett, K. E. (2005). Review of medical physiology (Vol. 22). New York: McGraw-Hill Medical.
  2. Paxianos, G.; Mai, J.K. (2004). The human Nervous System. Elsevier academic press. 
  3. a b Haddad, R., Lapid, H., Harel, D., & Sobel, N. (2008). Measuring smells. Current opinion in neurobiology, 18(4), 438-444.
  4. Glomerular Activity Response Archive
  5. a b Arshak, K., Moore, E., Lyons, G. M., Harris, J., & Clifford, S. (2004). A review of gas sensors employed in electronic nose applications. Sensor Review, 24(2), 181-198.
  6. Strauch, M., Lüdke, A., Münch, D., Laudes, T., Galizia, C. G., Martinelli, E., ... & Di Natale, C. (2014). More than apples and oranges-Detecting cancer with a fruit fly's antenna. Scientific reports, 4.
  7. D’Amico, A., Pennazza, G., Santonico, M., Martinelli, E., Roscioni, C., Galluccio, G., ... & Di Natale, C. (2010). An investigation on electronic nose diagnosis of lung cancer. Lung Cancer, 68(2), 170-176.