Educational model / Synthetic parameters
How a local input becomes a network response.
Change capacitance, leak, coupling and input current. Compare trajectories while keeping the assumptions in view.
Build a small passive network.
2–6 cells, cell-specific parameters and symmetric coupling. This independently implemented teaching model is not BETSE software, an Anthrobot model or an aging predictor.
Equations, provenance and limits.
V and E are in mV; time in ms; capacitance C in pF; leak and coupling conductance in nS; current in pA. Thus pF·mV/ms = pA and nS·mV = pA. Positive current depolarizes. Symmetric coupling currents cancel across an edge.
Cell-specific capacitance, leak, reversal, starting voltage and input amplitude are editable. Coupling is shared across the selected edges. With two cells, chain and ring each have one unique edge. All defaults are synthetic educational choices. No parameters are fitted to living tissue or Anthrobot data.
Reversal potentials are fixed. Pumps, ion concentrations, voltage-gated channels, gene expression, mechanics, morphology and molecular clocks are not simulated. Voltage is never translated into rejuvenation years.
V(t) = E + [V(0) − E] exp(−gL·t/C)
With zero leak and zero input, an isolated cell retains its initial voltage. With zero coupling, its neighbors have no modeled influence. RK4 integration uses a passive-rate bound and splits steps at pulse transitions. Numerical checks establish behavior of these equations; they do not validate a biological prediction.
Conceptual context: Alexis Pietak and Michael Levin’s BETSE (2016). BETSE includes richer ion transport and physiological processes. This tool uses its own simplified equations and implementation.