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Early Information Processing in the Vertebrate Olfactory System: A Computational Study
KTH, School of Computer Science and Communication (CSC), Numerical Analysis and Computer Science, NADA.
2007 (English)Licentiate thesis, comprehensive summary (Other scientific)
Abstract [en]

The olfactory system is believed to be the oldest sensory system. It developed to detect and analyse chemical information in the form of odours, and its organisation 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 has 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, both experimental and theoretical. 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 the basis of a biologically realistic model of the olfactory system. Our goal is to be able to represent the whole olfactory system. We are not there yet, but we have some of the necessary building blocks; a model of the input from the olfactory receptor neuron population and a model of the olfactory bulb. Taking into account the reported variability of geometrical, electrical and receptor-dependent neuronal characteristics, we have been able to model the frequency response of a population of olfactory receptor neurons. By constructing several olfactory bulb models of different size, we have shown that the size of the bulb network has an impact on its ability to process noisy information. We have also, through biochemical modelling, investigated the behaviour of the enzyme CaMKII which is known to be critical for early olfactory adaptation (suppression of constant odour stimuli).

Abstract [sv]

Luktsystemet anses allmänt vara det äldsta sensoriska systemet. Det utvecklades för att upptäcka och analysera kemisk information i form av lukter, och det är organiserat efter samma principer hos nästan alla djurarter: insekter så väl som däggdjur. Troligen beror likheterna på parallell evolution -- samma organisation har uppstått mer än en gång. Därför antas det ofta att luktsystemet är nära optimalt anpassat för sina arbetsuppgifter. Paradoxalt nog är luktsystemets arbetssätt ännu inte väl känt, 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 formar grunden för vår nuvarande förståelse av luktsystemet. Luktsystemet har länge varit ett fokus för vetenskapligt intresse, både experimentellt och teoretiskt. Ända sedan fältet beräkningsbiologi grundades har luktsystemet undersökts genom datormodellering. I denna avhandling presenterar jag grunden för en biologiskt realistisk modell av luktsystemet. Vårt mål är att kunna representera hela luktsystemet. Så långt har vi ännu inte nått, men vi har några av de nödvändiga byggstenarna: en modell av signalerna från populationen av luktreceptorceller, och en modell av luktbulben. Genom att ta hänsyn till nervcellernas rapporterade variationer i geometriska, elektriska och receptor-beroende karaktärsdrag har vi lyckats modellera svarsfrekvenserna från en population av luktreceptorceller. Genom att konstruera flera olika stora modeller av luktbulben har vi visat att storleken på luktbulbens cellnätverk påverkar dess förmåga att behandla brusig information. Vi har också, genom biokemisk modellering, undersökt beteendet hos enzymet CaMKII, som är kritiskt viktigt för adaptering (undertryckning av ständigt närvarande luktstimuli) i luktsystemet.

Place, publisher, year, edition, pages
Stockholm: Numerisk analys och datalogi , 2007.
Series
Trita-CSC-A, ISSN 1653-5723 ; 2007:8
Keyword [en]
olfaction, olfactory system, olfactory bulb, synchronisation, CaMKII, mathematical modelling
National Category
Computer Science
Identifiers
URN: urn:nbn:se:kth:diva-4408ISBN: 978-91-7178-696-8 (print)OAI: oai:DiVA.org:kth-4408DiVA: diva2:12177
Presentation
2007-06-08, E2, Lindstedtsvägen 3, Stockholm, 15:00
Opponent
Supervisors
Available from: 2007-05-30 Created: 2007-05-30 Last updated: 2012-03-21
List of papers
1. The impact of the distribution of isoforms on CaMKII activation
Open this publication in new window or tab >>The impact of the distribution of isoforms on CaMKII activation
2006 (English)In: Neurocomputing, ISSN 0925-2312, Vol. 69, no 10-12, 1010-1013 p.Article in journal (Refereed) Published
Abstract [en]

We have developed a computational model of the regulation of alpha- and beta-CaMKII activity, in order to examine (i) the importance of neighbour subunit interactions and (ii) the effect the higher CaMCa4 affinity of beta-CaMKII has on the holoenzyme activity in different configurations with the same alpha: beta ratio. The model consists of a deterministic biochemical network coupled to stochastic activation of CaMKII The results suggest that CaMKII holoenzyme activity is non-linear and dependent on the holoenzyme configuration of isoforms. This is especially pronounced in situations with a high-dephosphorylation rate of CaMKII.

Keyword
CaMKII; Plasticity; Computer modelling; Stochastic model
National Category
Information Science
Identifiers
urn:nbn:se:kth:diva-7227 (URN)10.1016/j.neucom.2005.12.035 (DOI)000237873900004 ()2-s2.0-33646520327 (Scopus ID)
Note
Hjorth, Johannes: Lic (Manuskript) QC 20100723Available from: 2007-05-30 Created: 2007-05-30 Last updated: 2012-01-08Bibliographically approved
2. Scaling effects in a model of the olfactory bulb
Open this publication in new window or tab >>Scaling effects in a model of the olfactory bulb
2007 (English)In: Neurocomputing, ISSN 0925-2312, Vol. 70, no 10-12, 1802-1807 p.Article in journal (Refereed) Published
Abstract [en]

Most computational models of the olfactory bulb are much smaller than any biological olfactory bulb-usually because the number of granule cells is much lower. The resulting subsampling of the inhibitory input may distort network dynamics and processing. We have constructed a large-scale model of the zebrafish olfactory bulb, as well as two smaller models, using the efficient parallellizing neural simulator SPLIT and data from a previously existing GENESIS model. We are studying several characteristics-among them overall behaviour, degree of synchrony of mitral cells and the timescale of appearance of synchrony-using cross-correlation plots and synthesized EEGs. Larger models with higher proportions of granule cells to mitral cells appear to give more synchronized output, especially for stimuli with shorter timescales.

Keyword
olfactory bulb; oscillation; synchronization
Identifiers
urn:nbn:se:kth:diva-7228 (URN)10.1016/j.neucom.2006.10.062 (DOI)000247215300040 ()2-s2.0-34247547342 (Scopus ID)
Note
QC20100723Available from: 2007-05-30 Created: 2007-05-30 Last updated: 2012-01-08Bibliographically approved
3. Modelling the population of olfactory receptor neurons
Open this publication in new window or tab >>Modelling the population of olfactory receptor neurons
2007 (English)Manuscript (preprint) (Other academic)
National Category
Computer Science
Identifiers
urn:nbn:se:kth:diva-7229 (URN)
Note

QC 20101116

Available from: 2007-05-30 Created: 2007-05-30 Last updated: 2016-02-02Bibliographically approved

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