Computational insights on drug effects on intrinsic stochasticity of mouse pacemaker cell activity

In sinoatrial node cells (SANCs), stochastic Ca²⁺ release from the sarcoplasmic reticulum (SR) interacts with membrane channels, inducing their stochastic opening and closing, leading to interbeat interval (IBI) variability (BIV). Additionally, stochastic neurotransmitter release activates cAMP/protein kinase A signaling, influencing membrane channels and SR proteins, further contributing to BIV. Most computational models produce deterministic IBIs, lacking physiological BIV. We tested three hypotheses: 1) incorporating stochastic behavior into intrinsic mechanisms mimics experimental BIV, 2) increased neurotransmitter stimulation via β-adrenergic receptor (β-AR) activation, phosphodiesterase (PDE) inhibition, or enhanced sarco/endoplasmic reticulum Ca²⁺-ATPase (SERCA) activity shortens IBIs and reduces BIV, and 3) these interventions affect BIV parameters differently at short and long timescales. To test this, we introduced the stochastic behavior of Ca²⁺ channels, ryanodine receptor (RyR), funny channel, and autonomic nervous system signaling via carbachol and isoproterenol (ISO) stimulations into our mouse coupled-clock SANC model. Kolmogorov-Smirnov tests showed that the IBI distribution of our stochastic model aligns significantly more closely with experimental data than those of the deterministic model. RyR noise maximized BIV, mainly increasing short-scale (1-10) entropy (IBI irregularity). Funny channel noise influenced short-scale entropy and low-frequency power, whereas ISO noise affected long-scale (11-20) entropy. Augmented β-AR activation or PDE inhibition shortened the IBI and reduced its standard deviation, mirroring SERCA activity enhancement. β-AR activation reduced low-frequency power, PDE inhibition decreased entropy across scales, and SERCA activation reduced power in all frequency bands. Thus, interactions among intrinsic stochastic mechanisms contribute to BIV complexity, and drug effects have different responses on BIV.