ReviewFrontiers in physiology2022
Studying Cardiac Neural Network Dynamics: Challenges and Opportunities for Scientific Computing.
Review in Frontiers in physiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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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.
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Who cites it
4 citing papers in PubMed.
- Cardiac Neuroanatomy and Fundamentals of Neurocardiology.Cardiac electrophysiology clinics · 2024Review
- The promise of cardiac neuromodulation: can computational modelling bridge the gap?The Journal of physiology · 2023Article
- Vagal Nerve Stimulation Reduces Ventricular Arrhythmias and Mitigates Adverse Neural Cardiac Remodeling Post-Myocardial Infarction.JACC. Basic to translational science · 2023Article
- Metrics of high cofluctuation and entropy to describe control of cardiac function in the stellate ganglion.eLife · 2022Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Neural control of the heart involves continuous modulation of cardiac mechanical and electrical activity to meet the organism's demand for blood flow. The closed-loop control scheme consists of interconnected neural networks with central and peripheral components working cooperatively with each other. These components have evolved to cooperate control of various aspects of cardiac function, which produce measurable "functional" outputs such as heart rate and blood pressure. In this review, we will outline fundamental studies probing the cardiac neural control hierarchy. We will discuss how computational methods can guide improved experimental design and be used to probe how information is processed while closed-loop control is operational. These experimental designs generate large cardio-neural datasets that require sophisticated strategies for signal processing and time series analysis, while presenting the usual large-scale computational challenges surrounding data sharing and reproducibility. These challenges provide unique opportunities for the development and validation of novel techniques to enhance understanding of mechanisms of cardiac pathologies required for clinical implementation.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.