Show simple item record

dc.contributor.authorTowlson, Emma K
dc.contributor.authorVertes, Petra
dc.contributor.authorYan, Gang
dc.contributor.authorChew, Yee Lian
dc.contributor.authorWalker, Denise S
dc.contributor.authorSchafer, William R
dc.contributor.authorBarabási, Albert-László
dc.date.accessioned2019-02-08T00:33:36Z
dc.date.available2019-02-08T00:33:36Z
dc.date.issued2018-09-10
dc.identifier.issn0962-8436
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/289012
dc.description.abstractControl is essential to the functioning of any neural system. Indeed, under healthy conditions the brain must be able to continuously maintain a tight functional control between the system's inputs and outputs. One may therefore hypothesize that the brain's wiring is predetermined by the need to maintain control across multiple scales, maintaining the stability of key internal variables, and producing behaviour in response to environmental cues. Recent advances in network control have offered a powerful mathematical framework to explore the structure-function relationship in complex biological, social and technological networks, and are beginning to yield important and precise insights on neuronal systems. The network control paradigm promises a predictive, quantitative framework to unite the distinct datasets necessary to fully describe a nervous system, and provide mechanistic explanations for the observed structure and function relationships. Here, we provide a thorough review of the network control framework as applied to Caenorhabditis elegans (Yan et al. 2017 Nature550, 519-523. (doi:10.1038/nature24056)), in the style of Frequently Asked Questions. We present the theoretical, computational and experimental aspects of network control, and discuss its current capabilities and limitations, together with the next likely advances and improvements. We further present the Python code to enable exploration of control principles in a manner specific to this prototypical organism.This article is part of a discussion meeting issue 'Connectome to behaviour: modelling C. elegans at cellular resolution'.
dc.format.mediumElectronic
dc.languageeng
dc.publisherThe Royal Society
dc.subjectNerve Net
dc.subjectNeurons
dc.subjectMotor Neurons
dc.subjectAnimals
dc.subjectCaenorhabditis elegans
dc.subjectLocomotion
dc.subjectConnectome
dc.titleCaenorhabditis elegans and the network control framework-FAQs.
dc.typeArticle
prism.issueIdentifier1758
prism.publicationDate2018
prism.publicationNamePhilos Trans R Soc Lond B Biol Sci
prism.volume373
dc.identifier.doi10.17863/CAM.36275
dcterms.dateAccepted2018-08-10
rioxxterms.versionofrecord10.1098/rstb.2017.0372
rioxxterms.versionAM
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserved
rioxxterms.licenseref.startdate2018-09-10
dc.contributor.orcidTowlson, Emma K [0000-0002-0579-3623]
dc.contributor.orcidVertes, Petra [0000-0002-0992-3210]
dc.contributor.orcidSchafer, William R [0000-0002-6676-8034]
dc.identifier.eissn1471-2970
rioxxterms.typeJournal Article/Review
pubs.funder-project-idMQ: Transforming Mental Health (MQ17-24 Vertes)
pubs.funder-project-idMedical Research Council (MR/K020706/1)
cam.issuedOnline2018-09-10
rioxxterms.freetoread.startdate2019-09-10


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record