2022
DOI: 10.1109/tsp.2022.3221892
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A New Framework for the Time- and Frequency-Domain Assessment of High-Order Interactions in Networks of Random Processes

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Cited by 42 publications
(43 citation statements)
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“…LF interactions are weaker, prevalent along the direction from H to R that is usually less investigated in the literature, and appear more influenced by the paced breathing maneuver along this pathway. These results confirm from the point of view of bivariate cardiorespiratory interactions previous findings on the same dataset based on measures of highorder interactions (taking also into account systolic arterial pressure) showing that paced breathing evokes significant effects within the LF band of the frequency spectrum, but not in the HF band classically studied [13].…”
Section: Resultssupporting
confidence: 90%
“…LF interactions are weaker, prevalent along the direction from H to R that is usually less investigated in the literature, and appear more influenced by the paced breathing maneuver along this pathway. These results confirm from the point of view of bivariate cardiorespiratory interactions previous findings on the same dataset based on measures of highorder interactions (taking also into account systolic arterial pressure) showing that paced breathing evokes significant effects within the LF band of the frequency spectrum, but not in the HF band classically studied [13].…”
Section: Resultssupporting
confidence: 90%
“…Considering M stationary discrete-time stochastic processes X M = {X 1 , ..., X M } which map the states visited by a network of dynamic systems, their organizational structure is assessed in the information-theoretic domain using the socalled O-information rate (OIR) [5], [6]. The OIR of a subset of N processes taken from X M is defined recursively as [7]…”
Section: Framework To Measure O-information Ratementioning
confidence: 99%
“…In this work, the OIR is computed following a linear parametric approach based on vector autoregressive (VAR) models [6]. Specifically, X M is represented as a VAR process in the framework of state-space models, and the N submodels describing the joint dynamics of Z 1 = X j and Z 2 = X N −mj are derived (m varying as in (2)).…”
Section: Framework To Measure O-information Ratementioning
confidence: 99%
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“…Furthermore, emerging trends, such as the development of high-order interaction measures, are coming up in the neurosciences to respond to the need for providing more exhaustive descriptions of brain-network interactions. These measures allow one to deal with multivariate representations of complex systems [ 25 , 26 , 27 ], showing their potential for disentangling physiological mechanisms involving more than two units or subsystems [ 28 ]. Additionally, more sophisticated tools, such as graph theory [ 29 , 30 , 31 ], are widely used to depict the functional structure of the brain intended as a whole complex network where neural units are highly interconnected with each other via different direct and indirect pathways.…”
Section: Introductionmentioning
confidence: 99%