Editorial: Complex network dynamics in consciousness.
Front Comput Neurosci November 1, 2023 Francisco J. Esteban, Antonio Ibáñez-Molina, Sergio Iglesias-Parro et al. 1 citation
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2 papers in the library · 1 citation · publishing 2023-2026
Front Comput Neurosci November 1, 2023 Francisco J. Esteban, Antonio Ibáñez-Molina, Sergio Iglesias-Parro et al. 1 citation
No Summary
Applied Sciences January 27, 2026 Francisco J. Esteban, Eva Vargas, José A. Langa et al.
Consciousness can be understood through a dynamical view of brain processing that combines three complementary frameworks: continuous formulations of Integrated Information Theory, attractor-landscape modeling of brain-state transitions, and perturbational complexity metrics from TMS-EEG. Consciousness emerges near criticality, where metastable attractors allow flexible transitions between partially synchronized states. Perturbational-complexity indices quantify the brain's capacity for integration and differentiation even without behavioral responsiveness. Across anesthesia, disorders of consciousness, epilepsy, and neurodegeneration, TMS-EEG biomarkers show reduced complexity and altered synchronization consistent with structural and functional disconnection. Integrating multimodal data supports individualized modeling of consciousness-related dynamics.