Abstract This thesis is a study of the odour responses of insect olfactory (or odorant) receptor neurons (ORN) of blowfly (Calliphora vicina), mosquito (Aedes communis), fruitflies (Drosophila melanogaster and D. virilis) and large pine weevil (Hylobius abietis). A power-law dependence (similar to Stevens' law in psychophysics) was obtained for the action potential rate of ORN responses vs. odour concentration in measurements with metal microelectrodes from blowfly ORNs and an analysis system was developed for the extracellularily recorded action potentials (or nerve pulses). Odour exposure sequences were used to study action potential rates quantitatively as a function of odour concentration in air exposure. For an odour exposure sequence, a known initial amount of the odour compound in a filter paper inside a Pasteur pipette at the beginning of repeated exposures caused a gradual dilution of the odour concentration in the exposure sequence. The concentration at each exposure was calculated according to the discrete multiple headspace extraction and dilution (DMHED) method. The estimated odour concentration was assumed to obey in the method an exponential law with respect to the exposure number in the sequence. Despite that many uncontrollable parameters remain for measuring quantitatively the characteristics of the ORNs, the results obtained, e.g., sensitivity, specificity, adaptability, and the power-law realation are both biologically and technically very interesting. A time-to-voltage converter (TVC) was utilized for the response analysis in determining action potential intervals originating from a single ORN. A precision analysis of TVC was also performed. With the mosquito (Aedes communis), fruitflies (Drosophila melanogaster and D. virilis) and large pine weevil (Hylobius abietis) antennae were tested for inhibitory and excitatory effects to find out repellents and attractants. Human sweat was found to cause strong stimulus exposure in the responses of the mosquito ORNs and Neutroil® caused inhibitory responses in pine weevil ORNs, respectively. The power-law exponents for blowfly ORNs were about 0.19 in the case of 1-hexanol (HX), 0.065 in the case of 1,4-diaminobutane (14DAB) and 0.32 in the case of butyric acid (BA). The corresponding Stevens' law exponent values 0.39 and 0.33 have been reported for HX and BA, respectively, by Patte et al. (1975).

Chemical sensing is believed to be the oldest sensory ability. The chemical senses, olfaction and gustation, developed to detect and analyze information in the form of air- or waterborne chemicals, to find food and mates, and to avoid danger. The organization of the olfactory system follows the same principles in almost all living animals, insects as well as mammals. Likely, the similarities are due to parallel evolution – the same type of organisation seems to have arisen more than once. Therefore, the olfactory system is often assumed to be close to optimally designed for its tasks.Paradoxically, the workings of the olfactory system are not yet well known,although several milestone discoveries have been made during the last decades. The most well-known is probably the disovery of the olfactory receptor gene family,announced in 1991 by Linda Buck and Richard Axel. For this and subsequent work, they were awarded a Nobel Prize Award in 2004. This achievement has been of immense value for both experimentalists and theorists, and forms the basis of the current understanding of olfaction. The olfactory system has long been a focus for scientific interest within several fields, both experimental and theoretical, and it has often been used asa model system. And ever since the field of computational neuroscience was founded, the functions of the olfactory system have been investigated through computational modelling. In this thesis, I present several approaches to biologically realistic computational models of parts of the olfactory system, with an emphasis on the earlier stages of the vertebrate olfactory system – olfactory receptor neurons (ORNs) and the olfactory bulb (OB). I have investigated the behaviour of the enzyme CaMKII, which is known to be critical for olfactory adaptation (suppression of constant odour stimuli) in the ORN, using a biochemical model. By constructing several OB models of different size, I have shown that the size of the OB network has an impact on its ability to process noisy information. Taking into account the reported variability of geometrical, electrical and receptor-dependent neuronal characteristics, I have been able to model the frequency response of a population of ORNs. I have used this model to find the key properties that govern most of the ORN population’s response, and investigated some of the possible implications of these key properties in subsequent studies of the ORN population and the OB – what we call the fuzzy concentration coding hypothesis. / Detektion av kemiska ämnen anses allmänt vara den äldsta sensoriska förmågan. De kemiska sinnena, lukt och smak, utvecklades för att upptäcka och analysera kemisk information i form av luft- eller vattenburna ämnen, för att hitta mat och partners, och för att undvika fara. Luktsystemet är organiserat efter samma principer hos nästan alla djurarter, insekter såväl som däggdjur. Troligen beror likheterna på parallell evolution – samma organisation verkar ha uppstått mer än en gång. Därför antas det ofta att luktsystemet är nära optimalt anpassat för sina arbetsuppgifter.Paradoxalt nog är luktsystemets arbetsprinciper ännu inte väl kända, även om flera banbrytande framsteg gjorts de senaste decennierna. Det mest välkända är nog upptäckten av genfamiljen av luktreceptorer, som tillkännagavs 1991 av Linda Buck och Rikard Axel. För detta och efterföljande arbete belönades de med Nobelpriset år 2004. Upptäckten har varit mycket värdefull för både experimentalister och teoretiker, och är grunden för vår nuvarande förståelse av luktsystemet. Luktsystemet har länge varit ett fokus för vetenskapligt intresse inom flera fält, experimentella såväl som teoretiska, och har ofta använts som ett modellsystem. Och ända sedan fältet beräkningsneurobiologi grundades har luktsystemet undersökts genom datormodellering. I denna avhandling presenterar jag flera ansatser till biologiskt realistiskaberäkningsmodeller av luktsystemet, med tonvikt på de tidigare delarna av ryggradsdjurens luktsystem – luktreceptorceller och luktbulben. Jag har undersökt beteendet hos enzymet CaMKII, som anses vara kritiskt viktigt för adaptation (undertryckning av ständigt närvarande luktstimuli) i luktsystemet, i en biokemisk modell. Genom att konstruera flera olika stora modeller av luktbulben har jag visat att storleken på luktbulbens cellnätverk påverkar dess förmåga att behandla brusig information. Genom att ta hänsyn till nervcellernas rapporterade variationer i geometriska, elektriska och receptor-beroende karaktärsdrag har jag lyckats modellera svarsfrekvenserna från en population av luktreceptorceller. Jag har använt denna modell för att hitta de nyckelprinciper som styr huvuddelen av luktreceptorneuron-populationens svar, ochundersökt några av de tänkbara konsekvenserna av dessa nyckelprinciper i efterföljande studier av luktreceptorneuron-populationen och luktbulben – det vi kallar ”fuzzy concentration coding”-hypotesen. / QC20100723

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