Multi-Electrode Arrays (MEA) tissue model for hiPSC-CM simulations

Introduction

This MATLAB (The MathWorks, Natick, MA) source code provides an implementation of a 2D Multi-Electrode Array (MEA) electrophysiology model for cardiac tissues composed of human induced pluripotent stem cell–derived cardiomyocytes (hiPSC-CMs).

The framework couples a phenotype-specific ionic model with tissue-level intra- and extracellular diffusion operators and synthetic MEA electrode measurements. It supports heterogeneous cell populations, configurable electrode layouts, and spatially localized stimulation.

The model is intended for computational cardiology, in-silico MEA experiments, and tissue simulations.

Main Contributors

• Dr. Sofia Botti (Euler Institute, USI)
• Dr. Marco Favino (Euler Institute, USI)

License

The software is provided with NO WARRANTY and is licensed under the BSD 2-Clause "Simplified" License.

Model Features

• 2D structured grid tissue discretization
• Intracellular and extracellular conductivity operators
• Mass and diffusion matrix assembly
• Configurable MEA layouts (1, 9, 64, 256 electrodes)
• Circular electrode sensing regions
• Spatial phenotype heterogeneity
• Mixed resting potentials from different parameter sets
• Localized external stimulation current
• Configurable pacing time window

Software Requirements

• MATLAB R2022a or later versions
• No mandatory external toolboxes required

Repository Structure

• main_MEA.m — main simulation script
• MEA.m — MEA simulation class
• PointGrid.m — grid and geometry utilities
• assembleMatricesH.m — mass and diffusion matrix assembly
• build_fk.m — electrode kernel builder
• codici_el/ — electrode and auxiliary functions

How to Run

• Run the main file: main_MEA.m

• The script performs:

  • grid generation and matrix assembly
  • conductivity definition
  • phenotype heterogeneity assignment
  • MEA electrode placement
  • stimulus definition
  • time integration of the coupled ionic–tissue model
  • MEA signal computation

Main Parameters (editable in main_MEA.m)

Geometry

• domain size and mesh resolution
• number of elements per direction

Conductivities

• intracellular and extracellular conductivities

Heterogeneity

• percentage of AL-type cells (percentuale_AL)

Resting Potentials

• mixed resting states from two parameter sets

Stimulation

• stimulus amplitude and start/stop time

MEA configuration

• number of electrodes (nk)
• electrode spacing
• sensing radius

Time integration

• final time
• timestep size

Output

Depending on the MEA class configuration, the simulation produces:

• transmembrane potential evolution
• extracellular potentials
• synthetic MEA electrode signals
• tissue activation maps