001     890401
005     20230111074324.0
024 7 _ |a 10.1007/s00422-020-00852-8
|2 doi
024 7 _ |a 0023-5946
|2 ISSN
024 7 _ |a 0340-1200
|2 ISSN
024 7 _ |a 1432-0770
|2 ISSN
024 7 _ |a 2128/27106
|2 Handle
024 7 _ |a 33289879
|2 pmid
024 7 _ |a WOS:000598085900001
|2 WOS
037 _ _ |a FZJ-2021-00928
041 _ _ |a English
082 _ _ |a 000
100 1 _ |a Codianni, Marcello G.
|0 P:(DE-HGF)0
|b 0
|e Corresponding author
245 _ _ |a The roles of ascending sensory signals and top-down central control in the entrainment of a locomotor CPG
260 _ _ |a Heidelberg
|c 2020
|b Springer
336 7 _ |a article
|2 DRIVER
336 7 _ |a Output Types/Journal article
|2 DataCite
336 7 _ |a Journal Article
|b journal
|m journal
|0 PUB:(DE-HGF)16
|s 1612363646_9592
|2 PUB:(DE-HGF)
336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a JOURNAL_ARTICLE
|2 ORCID
336 7 _ |a Journal Article
|0 0
|2 EndNote
520 _ _ |a Previous authors have proposed two basic hypotheses about the factors that form the basis of locomotor rhythms in walking insects: sensory feedback only or sensory feedback together with rhythmic activity of small neural circuits called central pattern generators (CPGs). Here we focus on the latter. Following this concept, to generate functional outputs, locomotor control must feature both rhythm generation by CPGs at the level of individual joints and coordination of their rhythmic activities, so that all muscles are activated in an appropriate pattern. This work provides an in-depth analysis of an aspect of this coordination process based on an existing network model of stick insect locomotion. Specifically, we consider how the control system for a single joint in the stick insect leg may produce rhythmic output when subjected to ascending sensory signals from other joints in the leg. In this work, the core rhythm generating CPG component of the joint under study is represented by a classical half-center oscillator constrained by a basic set of experimental observations. While the dynamical features of this CPG, including phase transitions by escape and release, are well understood, we provide novel insights about how these transition mechanisms yield entrainment to the incoming sensory signal, how entrainment can be lost under variation of signal strength and period or other perturbations, how entrainment can be restored by modulation of tonic top-down drive levels, and how these factors impact the duty cycle of the motor output.
536 _ _ |a 572 - (Dys-)function and Plasticity (POF3-572)
|0 G:(DE-HGF)POF3-572
|c POF3-572
|f POF III
|x 0
588 _ _ |a Dataset connected to CrossRef
700 1 _ |a Daun, Silvia
|0 P:(DE-Juel1)162297
|b 1
|u fzj
700 1 _ |a Rubin, Jonathan E.
|0 0000-0002-1513-1551
|b 2
773 _ _ |a 10.1007/s00422-020-00852-8
|g Vol. 114, no. 6, p. 533 - 555
|0 PERI:(DE-600)1458477-3
|n 6
|p 533 - 555
|t Biological cybernetics
|v 114
|y 2020
|x 1432-0770
856 4 _ |u https://juser.fz-juelich.de/record/890401/files/Codianni_2020_Biological%20Cybernetics_TheRolesOfAscendingSensorySign...pdf
|y OpenAccess
909 C O |o oai:juser.fz-juelich.de:890401
|p openaire
|p open_access
|p VDB
|p driver
|p dnbdelivery
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 1
|6 P:(DE-Juel1)162297
913 0 _ |a DE-HGF
|b Key Technologies
|l Decoding the Human Brain
|1 G:(DE-HGF)POF3-570
|0 G:(DE-HGF)POF3-572
|3 G:(DE-HGF)POF3
|2 G:(DE-HGF)POF3-500
|4 G:(DE-HGF)POF
|v (Dys-)function and Plasticity
|x 0
913 1 _ |a DE-HGF
|b Key Technologies
|l Natural, Artificial and Cognitive Information Processing
|1 G:(DE-HGF)POF4-520
|0 G:(DE-HGF)POF4-525
|3 G:(DE-HGF)POF4
|2 G:(DE-HGF)POF4-500
|4 G:(DE-HGF)POF
|v Decoding Brain Organization and Dysfunction
|9 G:(DE-HGF)POF4-5251
|x 0
914 1 _ |y 2021
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
|d 2020-08-28
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0160
|2 StatID
|b Essential Science Indicators
|d 2020-08-28
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1050
|2 StatID
|b BIOSIS Previews
|d 2020-08-28
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1190
|2 StatID
|b Biological Abstracts
|d 2020-08-28
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0600
|2 StatID
|b Ebsco Academic Search
|d 2020-08-28
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1040
|2 StatID
|b Zoological Record
|d 2020-08-28
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b BIOL CYBERN : 2018
|d 2020-08-28
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1030
|2 StatID
|b Current Contents - Life Sciences
|d 2020-08-28
915 _ _ |a DEAL Springer
|0 StatID:(DE-HGF)3002
|2 StatID
|d 2020-08-28
|w ger
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
|d 2020-08-28
915 _ _ |a IF < 5
|0 StatID:(DE-HGF)9900
|2 StatID
|d 2020-08-28
915 _ _ |a WoS
|0 StatID:(DE-HGF)0113
|2 StatID
|b Science Citation Index Expanded
|d 2020-08-28
915 _ _ |a Peer Review
|0 StatID:(DE-HGF)0030
|2 StatID
|b ASC
|d 2020-08-28
915 _ _ |a OpenAccess
|0 StatID:(DE-HGF)0510
|2 StatID
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
|d 2020-08-28
915 _ _ |a Nationallizenz
|0 StatID:(DE-HGF)0420
|2 StatID
|d 2020-08-28
|w ger
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Clarivate Analytics Master Journal List
|d 2020-08-28
920 _ _ |l yes
920 1 _ |0 I:(DE-Juel1)INM-3-20090406
|k INM-3
|l Kognitive Neurowissenschaften
|x 0
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a UNRESTRICTED
980 _ _ |a I:(DE-Juel1)INM-3-20090406
980 1 _ |a FullTexts


LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21