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An open computational toolbox to analyze multi- and single-unit sympathetic nerve activity in microneurography.
D'Alesio, Giacomo; Stumpp, Lars Ingmar; Sciarrone, Paolo; Navari, Alessandro; Gentile, Francesco; Borrelli, Chiara; Ballanti, Sara; Degl'Innocenti, Eleonora; Carrasco, Adrian; Costa, Ana Catarina; Andrade, Alexandre; Mannini, Andrea; Macefield, Vaughan Gary; Emdin, Michele; Passino, Claudio; Mazzoni, Alberto; Giannoni, Alberto; Oddo, Calogero Maria.
Afiliação
  • D'Alesio G; The BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy.
  • Stumpp LI; The BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy.
  • Navari A; Cardiovascular Medicine Department, Fondazione Toscana Gabriele Monasterio, Pisa, Italy.
  • Borrelli C; Medical Research Center, University of Iowa, Iowa City, Iowa, USA.
  • Ballanti S; The BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy.
  • Degl'Innocenti E; Cardiovascular Medicine Department, Fondazione Toscana Gabriele Monasterio, Pisa, Italy.
  • Costa AC; Faculdade de Ciências da Universidade de Lisboa, Lisbon, Portugal.
  • Andrade A; Instituto de Biofísica e Engenharia Biomédica, Faculdade de Ciências da Universidade de Lisboa, Lisbon, Portugal.
  • Mannini A; Artificial Intelligence for Rehabilitation Laboratory, Fondazione Don Carlo Gnocchi IRCCS, Florence, Italy.
  • Mazzoni A; The BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy.
Biophys Rev (Melville) ; 5(2): 021401, 2024 Jun.
Article em En | MEDLINE | ID: mdl-38895135
ABSTRACT
Microelectrode recordings from human peripheral and cranial nerves provide a means to study both afferent and efferent axonal signals at different levels of detail, from multi- to single-unit activity. Their analysis can lead to advancements both in diagnostic and in the understanding of the genesis of neural disorders. However, most of the existing computational toolboxes for the analysis of microneurographic recordings are limited in scope or not open-source. Additionally, conventional burst-based metrics are not suited to analyze pathological conditions and are highly sensitive to distance of the microelectrode tip from the active axons. To address these challenges, we developed an open-source toolbox that offers advanced analysis capabilities for studying neuronal reflexes and physiological responses to peripheral nerve activity. Our toolbox leverages the observation of temporal sequences of action potentials within inherently cyclic signals, introducing innovative methods and indices to enhance analysis accuracy. Importantly, we have designed our computational toolbox to be accessible to novices in biomedical signal processing. This may include researchers and professionals in healthcare domains, such as clinical medicine, life sciences, and related fields. By prioritizing user-friendliness, our software application serves as a valuable resource for the scientific community, allowing to extract advanced metrics of neural activity in short time and evaluate their impact on other physiological variables in a consistent and standardized manner, with the final aim to widen the use of microneurography among researchers and clinicians.

Texto completo: 1 Base de dados: MEDLINE Idioma: En Revista: Biophys Rev (Melville) Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Itália

Texto completo: 1 Base de dados: MEDLINE Idioma: En Revista: Biophys Rev (Melville) Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Itália