Instantaneous characterization of time-varying systems [neurological surgery]

A nonlinear system may be characterized by an orthogonal functional power series (FPS) computed from cross correlations between input and output variables. “Does the response change over the course of the experiment?” is a fundamental question encountered in the analysis of both FPS and evoked responses (EECs). Regression on closed-form functions of time produces a time-varying FPS or ER. Evaluation of these functions at a specified time point produces a system characterization for that instant. In an important subset of surgical procedures, the procedure itself poses a significant threat to the patient´s nervous system. In order to reduce this threat, neurophysiological function of the structures at risk may be monitored during surgery using time locked sensory or motor ER´s. By fitting polynomial functions of time to capture time variations in the evoked response, ^SIGNAL_NOISE enhancement comparable to that of averaging is obtained. More importantly a considerable improvement in time resolution is gained