ArticleScientific reports2023
Complexity synchronization: a measure of interaction between the brain, heart and lungs.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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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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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The Self and Its Intersubjective Synchrony in Psychotherapy: A Systematic Review.Clinical psychology & psychotherapyPooled it
- Principles Entailed by Complexity, Crucial Events, and Multifractal Dimensionality.Entropy (Basel, Switzerland) · 2025Article
- Analyzing EEG data during opium addiction treatment using a fuzzy logic-based machine learning model.Frontiers in psychiatry · 2025Article
- Complexity synchronization analysis of neurophysiological data: Theory and methods.Frontiers in network physiology · 2025Article
- Complexity synchronization in emergent intelligence.Scientific reports · 2024Article
- Complexity synchronization in living matter: a mini review.Frontiers in network physiology · 2024Review
- Complexity Synchronization of Organ Networks.Entropy (Basel, Switzerland) · 2023Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Herein we address the measurable consequences of the network effect (NE) on time series generated by different parts of the brain, heart, and lung organ-networks (ONs), which are directly related to their inter-network and intra-network interactions. Moreover, these same physiologic ONs have been shown to generate crucial event (CE) time series, and herein are shown, using modified diffusion entropy analysis (MDEA) to have scaling indices with quasiperiodic changes in complexity, as measured by scaling indices, over time. Such time series are generated by different parts of the brain, heart, and lung ONs, and the results do not depend on the underlying coherence properties of the associated time series but demonstrate a generalized synchronization of complexity. This high-order synchrony among the scaling indices of EEG (brain), ECG (heart), and respiratory time series is governed by the quantitative interdependence of the multifractal behavior of the various physiological ONs' dynamics. This consequence of the NE opens the door for an entirely general characterization of the dynamics of complex networks in terms of complexity synchronization (CS) independently of the scientific, engineering, or technological context. CS is truly a transdisciplinary effect.
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Registered trials
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