Publication:
Size principle and information theory

cris.virtual.author-orcid0000-0003-3622-0497
cris.virtualsource.author-orcid8365eb36-c1de-4f83-86b5-ce23ba0e33e0
cris.virtualsource.author-orcide915cc64-19da-4a4e-8d38-82fb5b019a32
datacite.rightsopen.access
dc.contributor.authorSenn, Walter
dc.contributor.authorWyler, K.
dc.contributor.authorClamann, H.P.
dc.contributor.authorKleinle, J.
dc.contributor.authorLüscher, Hans-Rudolf
dc.contributor.authorMüller, L.
dc.date.accessioned2024-10-15T09:31:17Z
dc.date.available2024-10-15T09:31:17Z
dc.date.issued1997-01-01
dc.description.abstractThe motor units of a skeletal muscle may be recruited according to different strategies. From all possible recruitment strategies nature selected the simplest one: in most actions of vertebrate skeletal muscles the recruitment of its motor units is by increasing size. This so-called size principle permits a high precision in muscle force generation since small muscle forces are produced exclusively by small motor units. Larger motor units are activated only if the total muscle force has already reached certain critical levels. We show that this recruitment by size is not only optimal in precision but also optimal in an information theoretical sense. We consider the motoneuron pool as an encoder generating a parallel binary code from a common input to that pool. The generated motoneuron code is sent down through the motoneuron axons to the muscle. We establish that an optimization of this motoneuron code with respect to its information content is equivalent to the recruitment of motor units by size. Moreover, maximal information content of the motoneuron code is equivalent to a minimal expected error in muscle force generation.
dc.description.numberOfPages12
dc.description.sponsorshipInstitut für Informatik (INF)
dc.description.sponsorshipInstitut für Physiologie
dc.identifier.doi10.48350/177423
dc.identifier.pmid9050202
dc.identifier.publisherDOI10.1007/s004220050317
dc.identifier.urihttps://boris-portal.unibe.ch/handle/20.500.12422/120544
dc.language.isoen
dc.publisherSpringer
dc.relation.ispartofBiological cybernetics
dc.relation.issn0340-1200
dc.relation.organizationDCD5A442C2AFE17DE0405C82790C4DE2
dc.relation.organizationDCD5A442BCD8E17DE0405C82790C4DE2
dc.subject.ddc000 - Computer science, knowledge & systems
dc.subject.ddc500 - Science::510 - Mathematics
dc.subject.ddc600 - Technology::610 - Medicine & health
dc.titleSize principle and information theory
dc.typearticle
dspace.entity.typePublication
dspace.file.typetext
oaire.citation.endPage22
oaire.citation.issue1
oaire.citation.startPage11
oaire.citation.volume76
oairecerif.author.affiliationInstitut für Informatik (INF)
oairecerif.author.affiliationInstitut für Physiologie
unibe.contributor.rolecreator
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unibe.contributor.rolecreator
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unibe.date.licenseChanged2023-01-20 13:33:29
unibe.description.ispublishedpub
unibe.eprints.legacyId177423
unibe.journal.abbrevTitleBIOL CYBERN
unibe.refereedtrue
unibe.subtype.articlejournal

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