Spectral decomposition of cerebrovascular and cardiovascular interactions in patients prone to postural syncope and healthy controls

Pernice, Riccardo; Sparacino, Laura; Bari, Vlasta; Gelpi, Francesca; Cairo, Beatrice; Mijatovic, Gorana; Antonacci, Yuri; Tonon, Davide; Rossato, Gianluca; Javorka, Michal; Porta, Alberto; Faes, Luca

doi:10.1016/j.autneu.2022.103021

Cited by 11 publications

(13 citation statements)

References 94 publications

(125 reference statements)

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“…𝑝 𝑘=1 [8], being n the time index, k the lag of interactions, p the model order (manually fixed for each subject), 𝑨(𝑘) the 2x2 coefficient matrices defining the time-lagged effects within and between the two processes, and 𝑼 a vector of zero-mean innovation processes with 2x2 covariance matrix 𝜮. The frequency-domain AR representation of the model coefficients leads to obtain the 2x2 transfer matrix as 𝑯(𝑓) = [𝑰 − 𝑨(𝑓)] −1 (being 𝑰 the identity matrix) from which the spectral density matrix of the bivariate process is derived as 𝑺(𝑓) = 𝑯(𝑓)𝚺𝑯 * (𝑓) (* stands for Hermitian transpose).…”

Section: Methodsmentioning

confidence: 99%

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Assessment of Cardiorespiratory Interactions During Spontaneous and Controlled Breathing: Linear Parametric Analysis

Pernice

Sparacino

Barà

et al. 2022

2022 12th Conference of the European Study Group on Cardiovascular Oscillations (ESGCO)

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In this work, we perform a linear parametric analysis of cardiorespiratory interactions in bivariate time series of heart period (HP) and respiration (RESP) measured in 19 healthy subjects during spontaneous breathing and controlled breathing at varying breathing frequency. The analysis is carried out computing measures of the total and causal interaction between HP and RESP variability in both time and frequency domains (low-and high-frequency, LF and HF). Results highlight strong cardiorespiratory interactions in the time domain and within the HF band that are not affected by the paced breathing condition. Interactions in the LF band are weaker and prevalent along the direction from HP to RESP, but result more influenced by the shift from spontaneous to controlled respiration.

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Section: Methodsmentioning

confidence: 99%

“…𝑯). Given (1) and (2), it has been shown [8], [10] that the sum of the two GC terms does not yield the total coupling, so that a spectral measure of the spectral mixing between the two causal directions can be defined as:…”

Section: Methodsmentioning

confidence: 99%

Assessment of Cardiorespiratory Interactions During Spontaneous and Controlled Breathing: Linear Parametric Analysis

Pernice

Sparacino

Barà

et al. 2022

2022 12th Conference of the European Study Group on Cardiovascular Oscillations (ESGCO)

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“…It is worth noting that the IC is always zero in the absence of zero-lag effects between the time series, i.e., when the AR model is strictly causal [ 122 ], but this is generally not true in practical analysis, when significant fast effects occur and are no more negligible [ 123 ]. A measure of the so-called “extended GC”, quantifying both time-lagged and instantaneous effects between time series, has also been proposed [ 124 ].…”

Section: Functional Connectivity Estimation Approachesmentioning

confidence: 99%

“…The computation of pairwise GC indexes as a function of frequency is based on: (i) fitting the observed set of time series with a linear parametric model as in ( 2 ); (ii) representing the model coefficients in the Fourier domain; (iii) deriving the frequency-dependent causal relations among signals starting from the definition of DC in ( 9 ). Indeed, it is possible to show that, under the assumption of strict causality, there exists a relationship between the frequency-specific GC

and the DC in ( 9 ), the former being defined as the logarithmic counterpart of the latter [ 24 , 122 ]:

…”

Section: Functional Connectivity Estimation Approachesmentioning

confidence: 99%

“…Contrary to the other terms of ( 11 ) and to its time-domain counterpart, the spectral IC does not fulfill the requirements of Geweke. Indeed, it may be negative for some frequencies and has no clear physical meaning [ 24 ], resulting in non-zero estimates at frequency

, even in the case of strict causality [ 122 ].…”

Section: Functional Connectivity Estimation Approachesmentioning

confidence: 99%

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Connectivity Analysis in EEG Data: A Tutorial Review of the State of the Art and Emerging Trends

et al. 2023

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Understanding how different areas of the human brain communicate with each other is a crucial issue in neuroscience. The concepts of structural, functional and effective connectivity have been widely exploited to describe the human connectome, consisting of brain networks, their structural connections and functional interactions. Despite high-spatial-resolution imaging techniques such as functional magnetic resonance imaging (fMRI) being widely used to map this complex network of multiple interactions, electroencephalographic (EEG) recordings claim high temporal resolution and are thus perfectly suitable to describe either spatially distributed and temporally dynamic patterns of neural activation and connectivity. In this work, we provide a technical account and a categorization of the most-used data-driven approaches to assess brain-functional connectivity, intended as the study of the statistical dependencies between the recorded EEG signals. Different pairwise and multivariate, as well as directed and non-directed connectivity metrics are discussed with a pros–cons approach, in the time, frequency, and information-theoretic domains. The establishment of conceptual and mathematical relationships between metrics from these three frameworks, and the discussion of novel methodological approaches, will allow the reader to go deep into the problem of inferring functional connectivity in complex networks. Furthermore, emerging trends for the description of extended forms of connectivity (e.g., high-order interactions) are also discussed, along with graph-theory tools exploring the topological properties of the network of connections provided by the proposed metrics. Applications to EEG data are reviewed. In addition, the importance of source localization, and the impacts of signal acquisition and pre-processing techniques (e.g., filtering, source localization, and artifact rejection) on the connectivity estimates are recognized and discussed. By going through this review, the reader could delve deeply into the entire process of EEG pre-processing and analysis for the study of brain functional connectivity and learning, thereby exploiting novel methodologies and approaches to the problem of inferring connectivity within complex networks.

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Concomitant evaluation of cardiovascular and cerebrovascular controls via Geweke spectral causality to assess the propensity to postural syncope

Porta

Gelpi

Bari

et al. 2023

Med Biol Eng Comput

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The evaluation of propensity to postural syncope necessitates the concomitant characterization of the cardiovascular and cerebrovascular controls and a method capable of disentangling closed loop relationships and decomposing causal links in the frequency domain. We applied Geweke spectral causality (GSC) to assess cardiovascular control from heart period and systolic arterial pressure variability and cerebrovascular regulation from mean arterial pressure and mean cerebral blood velocity variability in 13 control subjects and 13 individuals prone to develop orthostatic syncope. Analysis was made at rest in supine position and during head-up tilt at 60°, well before observing presyncope signs. Two different linear model structures were compared, namely bivariate autoregressive and bivariate dynamic adjustment classes. We found that (i) GSC markers did not depend on the model structure; (ii) the concomitant assessment of cardiovascular and cerebrovascular controls was useful for a deeper comprehension of postural disturbances; (iii) orthostatic syncope appeared to be favored by the loss of a coordinated behavior between the baroreflex feedback and mechanical feedforward pathway in the frequency band typical of the baroreflex functioning during the postural challenge, and by a weak cerebral autoregulation as revealed by the increased strength of the pressure-to-flow link in the respiratory band. GSC applied to spontaneous cardiovascular and cerebrovascular oscillations is a promising tool for describing and monitoring disturbances associated with posture modification. Graphical Abstract

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Spectral decomposition of cerebrovascular and cardiovascular interactions in patients prone to postural syncope and healthy controls

Cited by 11 publications

References 94 publications

Assessment of Cardiorespiratory Interactions During Spontaneous and Controlled Breathing: Linear Parametric Analysis

Assessment of Cardiorespiratory Interactions During Spontaneous and Controlled Breathing: Linear Parametric Analysis

Connectivity Analysis in EEG Data: A Tutorial Review of the State of the Art and Emerging Trends

Concomitant evaluation of cardiovascular and cerebrovascular controls via Geweke spectral causality to assess the propensity to postural syncope

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