Nonlinear system identification and overparameterization effects in multisensory evoked potential studies

Traditional signal processing techniques have not been suitable in establishing contributions from different sensory paths in multisensory evoked potentials. In this paper, a nonlinear modeling technique is proposed to demonstrate the possible mechanisms of interaction between sensory paths. The nonlinear autoregressive with exogenous inputs (NARX) model is explored to establish a relationship between electrical activities of the brain obtained by unimodal and by bimodal stimulation. The intersensory phenomenon concept is extended using nonlinear system theory and applied to show the possible interactions between the visual and auditory sensory paths. In addition, the paper addresses the compensation phenomenon caused by overparameterization in the NARX algorithm when it is applied to event-related potentials. It is hoped that the nonlinear modeling approach will generate hypotheses about the intersensory interaction phenomenon, improving and advancing its theoretical formulation.