Simulating human single motor units using self-organizing agents

dc.contributor.authorGurcan O.
dc.contributor.authorBernon C.
dc.contributor.authorTurker K.S.
dc.contributor.authorMano J.-P.
dc.contributor.authorGlize P.
dc.contributor.authorDikenelli O.
dc.date.accessioned2019-10-26T21:42:33Z
dc.date.available2019-10-26T21:42:33Z
dc.date.issued2012
dc.departmentEge Üniversitesien_US
dc.descriptionIEEE;IEEE Communications Society;Universite Jean Moulin Lyon 3, Ecole Universitaire de Management;Ecole Nationale Superieure des Mines;UCLB Lyon 1en_US
dc.description2012 IEEE 6th International Conference on Self-Adaptive and Self-Organizing Systems, SASO 2012 -- 10 September 2012 through 14 September 2012 -- Lyon -- 95450en_US
dc.description.abstractUnderstanding functional synaptic connectivity of human central nervous system is one of the holy grails of the neuroscience. Due to the complexity of nervous system, it is common to reduce the problem to smaller networks such as motor unit pathways. In this sense, we designed and developed a simulation model that learns acting in the same way of human single motor units by using findings on human subjects. The developed model is based on self-organizing agents whose nominal and cooperative behaviors are based on the current knowledge on biological neural networks. The results show that the simulation model generates similar functionality with the observed data. © 2012 IEEE.en_US
dc.identifier.doi10.1109/SASO.2012.18
dc.identifier.endpage20en_US
dc.identifier.isbn9780769548517
dc.identifier.issn1949-3673
dc.identifier.issn1949-3673en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage11en_US
dc.identifier.urihttps://doi.org/10.1109/SASO.2012.18
dc.identifier.urihttps://hdl.handle.net/11454/18354
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.relation.ispartofInternational Conference on Self-Adaptive and Self-Organizing Systems, SASOen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectbiological neural networksen_US
dc.subjectself-wiringen_US
dc.titleSimulating human single motor units using self-organizing agentsen_US
dc.typeConference Objecten_US

Dosyalar