A hierarchical decision module based on multiple neural networks

A new approach to source localization in the human brain, an important problem of neuroscience, is presented. A multiple neural network-based hierarchical decision-making system is developed. Each network is assigned to an independent model, and the output is evaluated in the higher level of the decision-making system. Utility functions are designed in the framework of decision-making. The network with the highest utility value is selected as the best network, representing the best model in EEG based inverse mapping. Simulation results show that the multiple neural network based decision-making system has successfully produced preferred decisions in source localization