ArticleBiophysics reviews2024
An open computational toolbox to analyze multi- and single-unit sympathetic nerve activity in microneurography.
Article in Biophysics reviews, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
2 citing papers in PubMed.
- Autonomic effects of simulated periodic breathing in patients with chronic heart failure on contemporary guideline-directed therapy.Clinical autonomic research : official journal of the Clinical Autonomic Research Society · 2026Article
- Hybrid knowledge- and data-driven modelling for robust spike detection and sorting in human C-fiber microneurography.Scientific reports · 2026Article
Corrections and comments
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Authors and funding
18 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
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