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While it is well-known that epilepsy has a clear impact on the activity of both the central nervous system (CNS) and the autonomic nervous system (ANS), its role on the complex interplay between CNS and ANS has not been fully elucidated yet. In this work, pairwise and higher-order predictability measures based on the concepts of Granger Causality (GC) and partial information decomposition (PID) were applied on time series of electroencephalographic (EEG) brain wave amplitude and heart rate variability (HRV) in order to investigate directed brain-heart interactions associated with the occurrence of focal epilepsy.HRV and the envelopes ofandEEG activity recorded from ipsilateral (ipsi-EEG) and contralateral (contra-EEG) scalp regions were analyzed in 18 children suffering from temporal lobe epilepsy monitored during pre-ictal, ictal and post-ictal periods. After linear parametric model identification, we compared pairwise GC measures computed between HRV and a single EEG component with PID measures quantifying the unique, redundant and synergistic information transferred from ipsi-EEG and contra-EEG to HRV.The analysis of GC revealed a dominance of the information transfer from EEG to HRV and negligible transfer from HRV to EEG, suggesting that CNS activities drive the ANS modulation of the heart rhythm, but did not evidence clear differences betweenandrhythms, ipsi-EEG and contra-EEG, or pre- and post-ictal periods. On the contrary, PID revealed that epileptic seizures induce a reorganization of the interactions from brain to heart, as the unique predictability of HRV originated from the ipsi-EEG for thewaves and from the contra-EEG for thewaves in the pre-ictal phase, while these patterns were reversed after the seizure.These results highlight the importance of considering higher-order interactions elicited by PID for the study of the neuro-autonomic effects of focal epilepsy, and may have neurophysiological and clinical implications.
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http://dx.doi.org/10.1088/1741-2552/ac7fba | DOI Listing |
Heart
September 2025
Population Health Research Institute, Hamilton, Ontario, Canada.
Background: Composite outcomes in cardiovascular trials often group events of unequal clinical importance, and conventional analyses may obscure treatment trade-offs. Generalised pairwise comparisons (GPC), expressed as a win ratio (WR), allow for hierarchical ranking of events and incorporation of recurrent outcomes, providing a potentially more intuitive assessment of benefit-risk.
Methods: In a prespecified exploratory analysis of the 2×2 factorial, randomised CLEAR (Colchicine and Spironolactone in Patients with Myocardial Infarction) trial (7062 patients within 72 hours of acute myocardial infarction (MI) and percutaneous coronary intervention), we applied both time-to-first and recurrent-event GPC to reassess low-dose colchicine (0.
Chaos
September 2025
Department of Condensed Matter Physics, University of Zaragoza, 50009 Zaragoza, Spain.
Human behaviors in social systems are often shaped by group pressure and collective norms, especially since the rise of social media platforms. However, in the context of adopting misbehaviors, most existing contagion models rely on pairwise interactions and thus fail to capture group-level dynamics. To fill this gap, we introduce a higher-order extension of the honesty-corruption-ostracism model to study the emergence of systemic corruption in populations where individuals interact through group structures.
View Article and Find Full Text PDFChaos
September 2025
Complex Systems Lab, Department of Physics, Indian Institute of Technology Indore, Khandwa Road, Simrol, Indore 453552, India.
Watanabe-Strogatz theory provides a low-dimensional description of identical Kuramoto oscillators via the framework of the Möbius transformation. Here, using the Watanabe-Strogatz theory, we provide a unifying description for a broad class of identical Kuramoto oscillator models with pairwise and higher-order interactions and their corresponding higher harmonics. We show that the dynamics of the Watanabe-Strogatz parameters are the same as those of the mean-field parameters.
View Article and Find Full Text PDFJ Math Biol
August 2025
Institute of Mathematics, Eötvös Loránd University, Budapest, Hungary.
Complex contagion models that involve contagion along higher-order structures, such as simplicial complexes and hypergraphs, yield new classes of mean-field models. Interestingly, the differential equations arising from many such models often exhibit a similar form, resulting in qualitatively comparable global bifurcation patterns. Motivated by this observation, we investigate a generalised mean-field-type model that provides a unified framework for analysing a range of different models.
View Article and Find Full Text PDFPhys Rev E
July 2025
University of Zaragoza, University of Zaragoza, Institute for Biocomputation and Physics of Complex Systems, 50018 Zaragoza, Spain; Department of Theoretical Physics, 50018 Zaragoza, Spain; and Centai Institute, Turin, Italy.
Modeling human behavior is essential to accurately predict epidemic spread, with behaviors like vaccine hesitancy complicating control efforts. While epidemic spread is often treated as a simple contagion, vaccine uptake may follow complex contagion dynamics, where individuals' decisions depend on multiple social contacts. Recently, the concept of complex contagion has received strong theoretical underpinnings thanks to the generalization of spreading phenomena from pairwise to higher-order interactions.
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