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Odor recognition in an attractor network model of the mammalian olfactory cortex
KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).ORCID iD: 0000-0001-6553-823X
2017 (English)In: 2017 International Joint Conference on Neural Networks (IJCNN), Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 3561-3568, article id 7966304Conference paper, Published paper (Refereed)
Abstract [en]

Odor recognition constitutes a key functional aspect of olfaction and in real-world scenarios it requires that odorants occurring in complex chemical mixtures are identified irrespective of their concentrations. We investigate this challenging pattern recognition problem in the framework of a three-stage computational model of the mammalian olfactory system. To this end, we first synthesize odor stimuli with the primary representations in the olfactory receptor neuron (ORN) layer and the secondary representations in the output of the olfactory bulb (OB) in the model. Next, sparse olfactory codes are extracted and fed into the recurrent network model, where as a result of Hebbian-like associative learning an attractor memory storage is produced. We demonstrate the capability of the resultant olfactory cortex (OC) model to perform robust odor recognition tasks and offer computational insights into the underlying network mechanisms.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2017. p. 3561-3568, article id 7966304
Keyword [en]
Attractor network, Computational model, Learning, Olfaction, Pattern recognition
National Category
Bioinformatics (Computational Biology)
Identifiers
URN: urn:nbn:se:kth:diva-218557DOI: 10.1109/IJCNN.2017.7966304ISI: 000426968703110Scopus ID: 2-s2.0-85031048062ISBN: 9781509061815 (print)OAI: oai:DiVA.org:kth-218557DiVA, id: diva2:1161439
Conference
2017 International Joint Conference on Neural Networks, IJCNN 2017, Anchorage, United States, 14 May 2017 through 19 May 2017
Note

QC 20171130

Available from: 2017-11-30 Created: 2017-11-30 Last updated: 2018-04-11Bibliographically approved

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Herman, Pawel

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf