M
Mauro Ursino
Researcher at University of Bologna
Publications - 285
Citations - 7181
Mauro Ursino is an academic researcher from University of Bologna. The author has contributed to research in topics: Hemodynamics & Blood pressure. The author has an hindex of 42, co-authored 270 publications receiving 6487 citations. Previous affiliations of Mauro Ursino include University of Siena.
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Journal ArticleDOI
Comparison of different cortical connectivity estimators for high-resolution EEG recordings.
Laura Astolfi,Febo Cincotti,Donatella Mattia,M. Grazia Marciani,Luiz A. Baccalá,Fabrizio De Vico Fallani,Serenella Salinari,Mauro Ursino,Melissa Zavaglia,Lei Ding,J. Christopher Edgar,Gregory A. Miller,Bin He,Fabio Babiloni +13 more
TL;DR: Functional connectivity patterns of cortical activity can be effectively estimated under general conditions met in most EEG recordings by combining high‐resolution EEG techniques, linear inverse estimation of the cortical activity, and frequency domain multivariate methods such as PDC, DTF, and dDTF.
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A simple mathematical model of the interaction between intracranial pressure and cerebral hemodynamics
Mauro Ursino,C. A. Lodi +1 more
TL;DR: It is suggested that PVI tests may be used to extract information not only on intracranial compliance and CSF circulation, but also on the status of mechanisms controlling CBF, and the generation of plateau waves and the effect of acute arterial hypotension on ICP.
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Interaction between carotid baroregulation and the pulsating heart: a mathematical model
TL;DR: A sensitivity analysis suggests that venous unstressed volume control plays the major role in the early hemodynamic response to acute hemorrhage, whereas systemic resistance and heart rate controls are a little less important.
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A mathematical study of human intracranial hydrodynamics part 1—The cerebrospinal fluid pulse pressure
TL;DR: The model explains the intracranial pressure pulse wave as the result of the pulsating changes in cerebral blood volume (related to cerebrovascular compliance) which occur within a rigid space (i.e., the craniospinal compartment).
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Tracking the Time-Varying Cortical Connectivity Patterns by Adaptive Multivariate Estimators
Laura Astolfi,Febo Cincotti,Donatella Mattia,F. De Vico Fallani,A. Tocci,Alfredo Colosimo,Serenella Salinari,Maria Grazia Marciani,Wolfram Hesse,Herbert Witte,Mauro Ursino,Melissa Zavaglia,Fabio Babiloni +12 more
TL;DR: A time-varying multivariate method for the estimation of rapidly changing connectivity relationships between cortical areas of the human brain, based on DTF/PDC and on the use of adaptive MVAR modelling (AMVAR) and to apply it to a set of real high resolution EEG data is tested.