Modeling Electrophysiological Diversity

Variations in morphology and ionchannel expression largely determine the electrophysiological properties of neurons. To investigate whether such variations are sufficient to explain the electrophysiological variability of globus pallidus neurons recorded in brain slices, Günay et al. created 100,000 computer models using three realistic morphologies and variable levels of nine ionic conductances. The models’ properties (e.g., spike threshold, waveform, afterhyperpolarization, firing rate) largely replicated the variability recorded in real neurons. Most properties were influenced by multiple conductances, and most conductances influenced multiple properties. Furthermore, complex interactions between conductances produced great variability in the magnitude of the effect produced by changing a single conductance; even the sign of the effect could change, depending on the density of the other conductances in a model. Impressively, the authors validated the model approach by using low doses of channel blockers to decrease conductance density in real neurons and produce the variability predicted by the model.