Models of Electrical Activity: Calibration and Prediction Testing on the Same Cell
Maurizio Tomaiuolo, Richard Bertram, Gareth Leng, Joel Tabak
Mathematical models are increasingly important in biology, and testability is becoming a critical issue. One limitation is that one model simulation tests a parameter set representing one instance of the biological counterpart, while biological systems are heterogeneous in their properties and behavior, and a model often is fitted to represent an ideal average. This is also true for models of a cell's electrical activity; even within a narrowly defined population there can be considerable variation in electrophysiological phenotype. Here, we describe a computational-experimental approach for parameterizing a model of the electrical activity of a cell in real time. We combine the inexpensive parallel computational power of a programmable graphics processing unit with the flexibility of the dynamic clamp method. The approach involves: 1) recording a cell's electrical activity, 2) parameterizing a model to the recording, 3) generating predictions and 4) testing the predictions on the same cell used for the calibration. We demonstrate the experimental feasibility of our approach using a cell line (GH4C1). These cells are electrically active, and display tonic spiking or bursting. We use our approach to predict parameter changes that can convert one pattern to the other.