Repositorio Institucional
Repositorio Institucional
CONICET Digital
  • Inicio
  • EXPLORAR
    • AUTORES
    • DISCIPLINAS
    • COMUNIDADES
  • Estadísticas
  • Novedades
    • Noticias
    • Boletines
  • Ayuda
    • General
    • Datos de investigación
  • Acerca de
    • CONICET Digital
    • Equipo
    • Red Federal
  • Contacto
JavaScript is disabled for your browser. Some features of this site may not work without it.
  • INFORMACIÓN GENERAL
  • RESUMEN
  • ESTADISTICAS
 
Artículo

Dorsal and median raphe neuronal firing dynamics characterized by nonlinear measures

Pascovich, Claudia; Serantes, Diego; Rodriguez, Alejo; Mateos, Diego MartínIcon ; González, Joaquín; Gallo, Diego; Rivas, Mayda; Devera, Andrea; Lagos, Patricia; Rubido, Nicolás; Torterolo, Pablo
Fecha de publicación: 05/2024
Editorial: Public Library of Science
Revista: PLOS Computational Biology
ISSN: 1553-7358
Idioma: Inglés
Tipo de recurso: Artículo publicado
Clasificación temática:
Otras Ciencias Biológicas

Resumen

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.
Palabras clave: RAPHE NUCLEI , NEURONAL FIRING , ENTROPY , COMPLEXITY
Ver el registro completo
 
Archivos asociados
Thumbnail
 
Tamaño: 2.465Mb
Formato: PDF
.
Descargar
Licencia
info:eu-repo/semantics/openAccess Excepto donde se diga explícitamente, este item se publica bajo la siguiente descripción: Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Unported (CC BY-NC-SA 2.5)
Identificadores
URI: http://hdl.handle.net/11336/258910
URL: https://dx.plos.org/10.1371/journal.pcbi.1012111
DOI: http://dx.doi.org/10.1371/journal.pcbi.1012111
Colecciones
Articulos(CCT - SANTA FE)
Articulos de CTRO.CIENTIFICO TECNOL.CONICET - SANTA FE
Articulos(IMAL)
Articulos de INST.DE MATEMATICA APLICADA "LITORAL"
Citación
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
Compartir
Altmétricas
 

Enviar por e-mail
Separar cada destinatario (hasta 5) con punto y coma.
  • Facebook
  • X Conicet Digital
  • Instagram
  • YouTube
  • Sound Cloud
  • LinkedIn

Los contenidos del CONICET están licenciados bajo Creative Commons Reconocimiento 2.5 Argentina License

https://www.conicet.gov.ar/ - CONICET

Inicio

Explorar

  • Autores
  • Disciplinas
  • Comunidades

Estadísticas

Novedades

  • Noticias
  • Boletines

Ayuda

Acerca de

  • CONICET Digital
  • Equipo
  • Red Federal

Contacto

Godoy Cruz 2290 (C1425FQB) CABA – República Argentina – Tel: +5411 4899-5400 repositorio@conicet.gov.ar
TÉRMINOS Y CONDICIONES