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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  
dc.subject.classification
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