Bounded Phase Coherence Maximizes Stability in Living Systems: A Kuramoto Framework Unifying Inverted-U Dynamics Across Arousal, Criticality, and Autonomic–Neuro Coupling
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| Sprache: | Englisch |
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2026
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| _version_ | 1866901175970824192 |
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| author | Phillips, Zachary Jaiamin |
| author_facet | Phillips, Zachary Jaiamin |
| contents | <p>Living systems exhibit maximal stability—defined as resilience to perturbation and rapid recovery—neither under complete disorder nor rigid synchronization, but within an intermediate regime of coordinated dynamics. Across disparate domains, including arousal–performance relationships, neural criticality, and heart-rate variability (HRV) complexity, optimal function consistently follows an inverted-U pattern with respect to order.</p> <p>Here, we propose that <strong>bounded phase coherence</strong>, quantified using the Kuramoto order parameter and its extensions, provides a unifying dynamical principle underlying these observations. We hypothesize that system-level stability is maximized at intermediate coherence (R≈0.5R \approx 0.5R≈0.5–0.80.80.8), with degradation occurring under desynchronization, hyper-synchrony, or excessive temporal jitter.</p> <p>We formalize this hypothesis using a non-autonomous, multiplex Kuramoto framework incorporating adaptive coupling, time-varying intrinsic frequencies, stochastic perturbations, and higher-order interactions. Stability is operationalized via recovery time constants, multi scale entropy (MSE), and metastability measures. Disorder dynamics are explicitly modeled to yield an inverted-U dependence on coherence.</p> <p>Falsifiable predictions include quadratic relationships between coherence and stability metrics, directional causality from coherence to recovery measured via conditional transfer entropy, moderation by biological sex, and characteristic deviations in pathological states (e.g., hyper-synchrony in autism, low coherence in anxiety).</p> <p>Simulations demonstrate self-organization toward the bounded coherence regime under stress, reproduction of inverted-U stability profiles, and hierarchical causal flow across physiological layers. This framework integrates naturally with predictive coding and active inference, where bounded coherence minimizes interoceptive prediction error by balancing precision weighting across scales.</p> <p>The theory offers a mechanistic, testable principle for physiological regulation with direct implications for biofeedback design, physiological monitoring, and adaptive self-regulation technologies.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18235945 |
| institution | Zenodo |
| language | eng |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Bounded Phase Coherence Maximizes Stability in Living Systems: A Kuramoto Framework Unifying Inverted-U Dynamics Across Arousal, Criticality, and Autonomic–Neuro Coupling Phillips, Zachary Jaiamin Phase Coherence Kuramoto model physiological synchronization inverted-U dynamics multiscale entropy complex systems theoretical neuroscience biological rhythms <p>Living systems exhibit maximal stability—defined as resilience to perturbation and rapid recovery—neither under complete disorder nor rigid synchronization, but within an intermediate regime of coordinated dynamics. Across disparate domains, including arousal–performance relationships, neural criticality, and heart-rate variability (HRV) complexity, optimal function consistently follows an inverted-U pattern with respect to order.</p> <p>Here, we propose that <strong>bounded phase coherence</strong>, quantified using the Kuramoto order parameter and its extensions, provides a unifying dynamical principle underlying these observations. We hypothesize that system-level stability is maximized at intermediate coherence (R≈0.5R \approx 0.5R≈0.5–0.80.80.8), with degradation occurring under desynchronization, hyper-synchrony, or excessive temporal jitter.</p> <p>We formalize this hypothesis using a non-autonomous, multiplex Kuramoto framework incorporating adaptive coupling, time-varying intrinsic frequencies, stochastic perturbations, and higher-order interactions. Stability is operationalized via recovery time constants, multi scale entropy (MSE), and metastability measures. Disorder dynamics are explicitly modeled to yield an inverted-U dependence on coherence.</p> <p>Falsifiable predictions include quadratic relationships between coherence and stability metrics, directional causality from coherence to recovery measured via conditional transfer entropy, moderation by biological sex, and characteristic deviations in pathological states (e.g., hyper-synchrony in autism, low coherence in anxiety).</p> <p>Simulations demonstrate self-organization toward the bounded coherence regime under stress, reproduction of inverted-U stability profiles, and hierarchical causal flow across physiological layers. This framework integrates naturally with predictive coding and active inference, where bounded coherence minimizes interoceptive prediction error by balancing precision weighting across scales.</p> <p>The theory offers a mechanistic, testable principle for physiological regulation with direct implications for biofeedback design, physiological monitoring, and adaptive self-regulation technologies.</p> |
| title | Bounded Phase Coherence Maximizes Stability in Living Systems: A Kuramoto Framework Unifying Inverted-U Dynamics Across Arousal, Criticality, and Autonomic–Neuro Coupling |
| topic | Phase Coherence Kuramoto model physiological synchronization inverted-U dynamics multiscale entropy complex systems theoretical neuroscience biological rhythms |
| url | https://doi.org/10.5281/zenodo.18235945 |