Population bursts in a modular neural network as a mechanism for synchronized activity in KNDy neurons
dc.contributor.author | Blanco, W | |
dc.contributor.author | Tabak, J | |
dc.contributor.author | Bertram, R | |
dc.date.accessioned | 2024-10-03T10:28:32Z | |
dc.date.issued | 2024-07-31 | |
dc.date.updated | 2024-10-02T22:16:12Z | |
dc.description.abstract | The pulsatile activity of gonadotropin-releasing hormone neurons (GnRH neurons) is a key factor in the regulation of reproductive hormones. This pulsatility is orchestrated by a network of neurons that release the neurotransmitters kisspeptin, neurokinin B, and dynorphin (KNDy neurons), and produce episodic bursts of activity driving the GnRH neurons. We show in this computational study that the features of coordinated KNDy neuron activity can be explained by a neural network in which connectivity among neurons is modular. That is, a network structure consisting of clusters of highly-connected neurons with sparse coupling among the clusters. This modular structure, with distinct parameters for intracluster and intercluster coupling, also yields predictions for the differential effects on synchronization of changes in the coupling strength within clusters versus between clusters. | en_GB |
dc.description.sponsorship | Conselho Nacional de Desenvolvimento Cientifico e Tecnológico - CNPq | en_GB |
dc.description.sponsorship | Biotechnology and Biological Sciences Research Council (BBSRC) | en_GB |
dc.description.sponsorship | Engineering and Physical Sciences Research Council (EPSRC) | en_GB |
dc.description.sponsorship | National Science Foundation (NSF) | en_GB |
dc.format.extent | e1011820- | |
dc.format.medium | Electronic-eCollection | |
dc.identifier.citation | Vol. 20(7), article e1011820 | en_GB |
dc.identifier.doi | https://doi.org/10.1371/journal.pcbi.1011820 | |
dc.identifier.grantnumber | 200551/2022-1 | en_GB |
dc.identifier.grantnumber | BB/X005038/1 | en_GB |
dc.identifier.grantnumber | EP/V048716/1 | en_GB |
dc.identifier.grantnumber | DMS 2324962 | en_GB |
dc.identifier.uri | http://hdl.handle.net/10871/137597 | |
dc.identifier | ORCID: 0000-0002-0588-957X (Tabak, Joel) | |
dc.language.iso | en | en_GB |
dc.publisher | Public Library of Science (PLoS) | en_GB |
dc.relation.url | https://www.math.fsu.edu/~bertram/software/neuron/ | en_GB |
dc.relation.url | https://www.ncbi.nlm.nih.gov/pubmed/39083544 | en_GB |
dc.rights | © 2024 Blanco et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. | en_GB |
dc.title | Population bursts in a modular neural network as a mechanism for synchronized activity in KNDy neurons | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2024-10-03T10:28:32Z | |
dc.contributor.editor | Touboul, JD | |
dc.identifier.issn | 1553-734X | |
exeter.article-number | ARTN e1011820 | |
exeter.place-of-publication | United States | |
dc.description | This is the final version. Available on open access from Public Library of Science via the DOI in this record | en_GB |
dc.description | Data Availability: Computer codes are available for free download from www.math.fsu.edu/~bertram/software/neuron/ | en_GB |
dc.identifier.eissn | 1553-7358 | |
dc.identifier.journal | PLoS Computational Biology | en_GB |
dc.relation.ispartof | PLoS Comput Biol, 20(7) | |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en_GB |
dcterms.dateAccepted | 2024-07-16 | |
dc.rights.license | CC BY | |
rioxxterms.version | VoR | en_GB |
rioxxterms.licenseref.startdate | 2024-07 | |
rioxxterms.type | Journal Article/Review | en_GB |
refterms.dateFCD | 2024-10-03T10:25:56Z | |
refterms.versionFCD | VoR | |
refterms.dateFOA | 2024-10-03T10:29:21Z | |
refterms.panel | A | en_GB |
refterms.dateFirstOnline | 2024-07-31 |
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Except where otherwise noted, this item's licence is described as © 2024 Blanco et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.