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Neural network models of the tactile system develop first-order units with spatially complex receptive fields
Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Dept. of Computer Science, Western University, London, Ontario, Canada; Brain and Mind Institute, Western University, London, Ontario, Canada; Dept. of Physiology and Pharmacology, Western University, London, Ontario, Canada; Dept. of Psychology, Western University, London, Ontario, Canada; Robarts Research Institute, Western University, London, Ontario, Canada.
2018 (English)In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 13, no 6, article id e0199196Article in journal (Refereed) Published
Abstract [en]

First-order tactile neurons have spatially complex receptive fields. Here we use machine-learning tools to show that such complexity arises for a wide range of training sets and network architectures. Moreover, we demonstrate that this complexity benefits network performance, especially on more difficult tasks and in the presence of noise. Our work suggests that spatially complex receptive fields are normatively good given the biological constraints of the tactile periphery.

Place, publisher, year, edition, pages
Public Library Science , 2018. Vol. 13, no 6, article id e0199196
National Category
Neurology Neurosciences
Identifiers
URN: urn:nbn:se:umu:diva-150783DOI: 10.1371/journal.pone.0199196ISI: 000435424900098PubMedID: 29902277OAI: oai:DiVA.org:umu-150783DiVA, id: diva2:1241378
Available from: 2018-08-23 Created: 2018-08-23 Last updated: 2018-08-23Bibliographically approved

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Pruszynski, J. Andrew

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CiteExportLink to record
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Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
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Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
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  • Other locale
More languages
Output format
  • html
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