ArticleIEEE transactions on bio-medical engineering2014
Time-varying modeling of cerebral hemodynamics.
Article in IEEE transactions on bio-medical engineering, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 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.
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Who cites it
16 citing papers in PubMed, 30 citations in OpenAlex.
- A Closed-Loop Cardiovascular Model of the Supine-To-Stand Manoeuvre: Implications for Falls.International journal for numerical methods in biomedical engineering · 2026Article
- Time-domain methods for quantifying dynamic cerebral blood flow autoregulation: Review and recommendations. A white paper from the Cerebrovascular Research Network (CARNet).Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2024Review
- Cognitive activity significantly affects the dynamic cerebral autoregulation, but not the dynamic vasoreactivity, in healthy adults.Frontiers in physiology · 2024Article
- Reduced-order modeling and analysis of dynamic cerebral autoregulation via diffusion maps.Physiological measurement · 2023Article
- The Utility of Cerebrovascular Reactivity MRI in Brain Rehabilitation: A Mechanistic Perspective.Frontiers in physiology · 2021Review
- Joint time-frequency analysis of dynamic cerebral autoregulation using generalized harmonic wavelets.Physiological measurement · 2020Article
- Assessment of dynamic cerebral autoregulation in humans: Is reproducibility dependent on blood pressure variability?PloS one · 2020Article
- Dynamic Cerebral Autoregulation Reproducibility Is Affected by Physiological Variability.Frontiers in physiology · 2019Article
- Multivariate Granger causality unveils directed parietal to prefrontal cortex connectivity during task-free MRI.Scientific reports · 2018Article
- Methodology of Recurrent Laguerre-Volterra Network for Modeling Nonlinear Dynamic Systems.IEEE transactions on neural networks and learning systems · 2017Article
- Compartmental and Data-Based Modeling of Cerebral Hemodynamics: Nonlinear Analysis.IEEE transactions on bio-medical engineering · 2017Article
- Applying time-frequency analysis to assess cerebral autoregulation during hypercapnia.PloS one · 2017Article
- Comparison of Model-Based Indices of Cerebral Autoregulation and Vasomotor Reactivity Using Transcranial Doppler versus Near-Infrared Spectroscopy in Patients with Amnestic Mild Cognitive Impairment.Journal of Alzheimer's disease : JAD · 2017Article
- Globally conditioned Granger causality in brain-brain and brain-heart interactions: a combined heart rate variability/ultra-high-field (7 T) functional magnetic resonance imaging study.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2016Article
- Multiple-input nonlinear modelling of cerebral haemodynamics using spontaneous arterial blood pressure, end-tidal CO2 and heart rate measurements.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2016Article
- Compartmental and Data-Based Modeling of Cerebral Hemodynamics: Linear Analysis.IEEE access : practical innovations, open solutionsArticle
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Authors and funding
4 authors at 3 institutions in 1 country.
Funding
Abstract
The scientific and clinical importance of cerebral hemodynamics has generated considerable interest in their quantitative understanding via computational modeling. In particular, two aspects of cerebral hemodynamics, cerebral flow autoregulation (CFA) and CO2 vasomotor reactivity (CVR), have attracted much attention because they are implicated in many important clinical conditions and pathologies (orthostatic intolerance, syncope, hypertension, stroke, vascular dementia, mild cognitive impairment, Alzheimer's disease, and other neurodegenerative diseases with cerebrovascular components). Both CFA and CVR are dynamic physiological processes by which cerebral blood flow is regulated in response to fluctuations in cerebral perfusion pressure and blood CO2 tension. Several modeling studies to date have analyzed beat-to-beat hemodynamic data in order to advance our quantitative understanding of CFA-CVR dynamics. A confounding factor in these studies is the fact that the dynamics of the CFA-CVR processes appear to vary with time (i.e., changes in cerebrovascular characteristics) due to neural, endocrine, and metabolic effects. This paper seeks to address this issue by tracking the changes in linear time-invariant models obtained from short successive segments of data from ten healthy human subjects. The results suggest that systemic variations exist but have stationary statistics and, therefore, the use of time-invariant modeling yields "time-averaged models" of physiological and clinical utility.
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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.