A model based decomposition method for temporally overlapping evoked potential components

The authors present a robust model-based decomposition method for temporally overlapping evoked potential (EP) components. The model assumes linear superposition of the EP constituent components, and Gaussian distributed firing instants of the neuronal population associated with each component. The decomposition provides a loss-less description of the EP complex, which is demonstrated via computer simulations as robust to violations of the model assumptions. The decomposition method is applied to experimental data, demonstrating its separation performance of severely overlapping EP components.