Key result
State-dependent network models with mechano-electric feedback extend cardiomyocyte synchronization length ~10-fold over static coupling.
Why the study?
Standard dipole models predict only short-range phase coherence due to the 1/r3 decay of mechanical interactions, leaving tissue-scale coordination of cardiomyocytes unexplained.
Mechano-electric feedback provides a physical mechanism for long-range synchronization of cardiomyocytes in systems with short-range elastic interactions.
Should not yet change clinical practice; leaves open mechano-electric feedback as a mechanism for long-range cardiomyocyte synchronization.
Long-range synchronization of cardiomyocytes via purely elastic substrates is limited by the 1/r3 decay of mechanical interactions. Standard dipole models therefore predict only short-range phase coherence, leaving tissue-scale coordination unexplained. In this work, we introduce a state-dependent network model in which local phase coherence enhances contractile force through mechano-electric feedback. Numerical simulations on a 1D chain show that this feedback extends the spatial correlation length by roughly an order of magnitude, enabling coherence over distances far beyond nearest-neighbour coupling. The feedback also substantially widens the synchronizable stiffness window and produces initial-condition sensitivity absent in static coupling models. Finite-size analysis confirms that the coherence extension persists as system size increases. These results provide a physical mechanism for long-range synchronization in systems with short-range elastic interactions.
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Hiroyuki Morimura (2026) studied Cardiomyocyte synchronization. State-dependent network model with mechano-electric feedback vs. Static coupling models was evaluated on Spatial correlation length / coherence extension. A state-dependent network model incorporating mechano-electric feedback extended the spatial correlation length of cardiomyocyte synchronization by roughly an order of magnitude over static coupling.
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