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dc.contributor.author
Pascovich, Claudia
dc.contributor.author
Serantes, Diego
dc.contributor.author
Rodriguez, Alejo
dc.contributor.author
Mateos, Diego Martín
dc.contributor.author
González, Joaquín
dc.contributor.author
Gallo, Diego
dc.contributor.author
Rivas, Mayda
dc.contributor.author
Devera, Andrea
dc.contributor.author
Lagos, Patricia
dc.contributor.author
Rubido, Nicolás
dc.contributor.author
Torterolo, Pablo
dc.date.available
2025-04-16T10:06:59Z
dc.date.issued
2024-05
dc.identifier.citation
Pascovich, Claudia; Serantes, Diego; Rodriguez, Alejo; Mateos, Diego Martín; González, Joaquín; et al.; Dorsal and median raphe neuronal firing dynamics characterized by nonlinear measures; Public Library of Science; PLOS Computational Biology; 20; 5; 5-2024; 1-22
dc.identifier.issn
1553-7358
dc.identifier.uri
http://hdl.handle.net/11336/258910
dc.description.abstract
The dorsal (DRN) and median (MRN) raphe are important nuclei involved in similar functions, including mood and sleep, but playing distinct roles. These nuclei have a different composition of neuronal types and set of neuronal connections, which among other factors, determine their neuronal dynamics. Most works characterize the neuronal dynamics using classic measures, such as using the average spiking frequency (FR), the coefficient of variation (CV), and action potential duration (APD). In the current study, to refine the characterization of neuronal firing profiles, we examined the neurons within the raphe nuclei. Through the utilizationof nonlinear measures, our objective was to discern the redundancy and complementarity of these measures, particularly in comparison with classic methods. To do this, we analyzed the neuronal basal firing profile in both nuclei of urethane-anesthetized rats using the Shannon entropy (Bins Entropy) of the inter-spike intervals, permutation entropy of ordinal patterns (OP Entropy), and Permutation Lempel-Ziv Complexity (PLZC). Firstly, we found that classic (i.e., FR, CV, and APD) and nonlinear measures fail to distinguish between the dynamics of DRN and MRN neurons, except for the OP Entropy. We also found strong relationships between measures, including the CV with FR, CV with Bins entropy, and FR with PLZC, which imply redundant information. However, APD and OP Entropy have either a weak or no relationship with the rest of the measures tested, suggesting that they provide complementary information to the characterization of the neuronal firing profiles. Secondly, we studied how these measures are affected by the oscillatory properties of the firing patterns, including rhythmicity, bursting patterns, and clock-like behavior. We found that all measures are sensitive to rhythmicity, except for the OP Entropy. Overall, our work highlights OP Entropy as a powerful and useful quantity for the characterization of neuronal discharge patterns.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Public Library of Science
dc.rights
info:eu-repo/semantics/openAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
RAPHE NUCLEI
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NEURONAL FIRING
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ENTROPY
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COMPLEXITY
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Otras Ciencias Biológicas
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Ciencias Biológicas
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CIENCIAS NATURALES Y EXACTAS
dc.title
Dorsal and median raphe neuronal firing dynamics characterized by nonlinear measures
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2025-04-14T10:22:26Z
dc.journal.volume
20
dc.journal.number
5
dc.journal.pagination
1-22
dc.journal.pais
Estados Unidos
dc.description.fil
Fil: Pascovich, Claudia. Universidad de la República; Uruguay
dc.description.fil
Fil: Serantes, Diego. Universidad de la República; Uruguay
dc.description.fil
Fil: Rodriguez, Alejo. Universidad de la República; Uruguay
dc.description.fil
Fil: Mateos, Diego Martín. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Matemática Aplicada del Litoral. Universidad Nacional del Litoral. Instituto de Matemática Aplicada del Litoral; Argentina
dc.description.fil
Fil: González, Joaquín. Universidad de la República; Uruguay
dc.description.fil
Fil: Gallo, Diego. Universidad de la República; Uruguay
dc.description.fil
Fil: Rivas, Mayda. Universidad de la República; Uruguay
dc.description.fil
Fil: Devera, Andrea. Universidad de la República; Uruguay
dc.description.fil
Fil: Lagos, Patricia. Universidad de la República; Uruguay
dc.description.fil
Fil: Rubido, Nicolás. Kings College, University Of Aberdeen; Reino Unido
dc.description.fil
Fil: Torterolo, Pablo. Universidad de la República; Uruguay
dc.journal.title
PLOS Computational Biology
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://dx.plos.org/10.1371/journal.pcbi.1012111
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1371/journal.pcbi.1012111
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