A computational model of a human single sinoatrial node cell.

Area of Science:

• Computational biology
• Cardiovascular physiology
• Biophysics

Background:

• Cardiac neuromodulation aims to regulate heart rate (HR).
• Accurate sinoatrial node (SAN) cell models are crucial for developing effective neuromodulation strategies.
• Existing models may not fully capture human SAN cell behavior for targeted HR reduction.

Purpose of the Study:

• To formulate a human sinoatrial node (SAN) cell model for investigating spontaneous rhythmical activity.
• To establish a hardware-in-the-loop system for analyzing optimal neurostimulation patterns to decrease elevated HR.
• To validate the model against experimental data and human studies.

Main Methods:

• Adopted base model structures from rabbit SAN cell models.
• Utilized Hodgkin-Huxley-type model equations for ion channel dynamics.
• Incorporated 15 ion currents responsible for action potential (AP) generation.
• Validated the model using simulations of ivabradine's effect and parasympathetic stimulation.

Main Results:

• The human SAN cell model reproduces AP frequencies equivalent to isolated human SAN cells (HR of 71.8 bpm).
• Model simulations of ivabradine's inhibitory effect align with human experimental results.
• Model validation for HR effects upon parasympathetic stimulation matches human trial data.

Conclusions:

• The developed human SAN cell model accurately represents physiological heart rate and response to neuromodulation.
• This model serves as a valuable tool for designing and testing neurostimulation systems for HR control.
• The hardware-in-the-loop system facilitates the analysis of optimal stimulation patterns for cardiac neuromodulation.