Real-time GPU-accelerated coupled cardiac system: Integrating bidirectional interactions between living optogenetic monolayers and computational simulations.
Y, V., A, K., F, F., & G, B. (2026). Real-time GPU-accelerated coupled cardiac system: Integrating bidirectional interactions between living optogenetic monolayers and computational simulations.. PLoS computational biology. https://doi.org/10.1371/journal.pcbi.1014590
Y V, A K, F F, G B. Real-time GPU-accelerated coupled cardiac system: Integrating bidirectional interactions between living optogenetic monolayers and computational simulations.. PLoS computational biology. 2026; doi: 10.1371/journal.pcbi.1014590
Y V, A K, F F, et al. Real-time GPU-accelerated coupled cardiac system: Integrating bidirectional interactions between living optogenetic monolayers and computational simulations.[J]. PLoS computational biology. 2026. DOI: 10.1371/journal.pcbi.1014590.
@article{y2026,
author = {Valibeigi Y and Kaboudian A and Fenton F and Bub G},
title = {Real-time GPU-accelerated coupled cardiac system: Integrating bidirectional interactions between living optogenetic monolayers and computational simulations.},
journal = {PLoS computational biology},
year = {2026},
doi = {10.1371/journal.pcbi.1014590},
note = {PMID: 42546041},
}
TY - JOUR AU - Valibeigi Y AU - Kaboudian A AU - Fenton F AU - Bub G TI - Real-time GPU-accelerated coupled cardiac system: Integrating bidirectional interactions between living optogenetic monolayers and computational simulations. T2 - PLoS computational biology PY - 2026 DO - 10.1371/journal.pcbi.1014590 AN - PMID:42546041 ER -
OBJECTIVE: Reentrant arrhythmias are life-threatening cardiac events that are difficult to study due to limited experimental control over the complex circuit dynamics. We present a real-time coupled cardiac system that allows in real-time dynamic manipulation of reentrant pathways in vitro using physiologically relevant simulations. METHODS: We designed a closed-feedback loop system that couples a cultured cardiac monolayer with a two-dimensional computational simulation of cardiac tissue. The simulation, based on GPU-accelerated models (e.g., cellular automata), predicts wave propagation in real-time using the Abubu.js library. Optical mapping captures monolayer activation patterns, and simulation outputs are converted into light-based stimulation via optogenetics, using LEDs and microcontrollers to depolarize cardiac tissue. RESULTS: Our platform is capable of accurately detecting and responding to electrical waves in real-time, enabling interactive modulation of reentrant circuits. The system replaces traditional fixed-delay stimulation protocols with computationally guided interventions, better mimicking physiological conduction dynamics. CONCLUSION: This coupled system provides a novel and responsive method to study reentrant arrhythmias. Its integration of optical stimulation, real-time modeling, and tissue feedback enables the construction of user-defined reentry pathways and dynamic interaction with reentrant circuit behavior. SIGNIFICANCE: By merging computational and biological systems, this work introduces a versatile experimental framework for investigating arrhythmias. Built from inexpensive and accessible components, it lowers technical and financial barriers, increasing accessibility across a broad range of researchers and research environments. The platform may inform future control and anti-arrhythmic strategies and pave the way for personalized cardiac electrophysiology studies.