Real-time reconstruction of evoked potentials using a new two-dimensional filter method.

Abstract

Standard techniques for evoked potential recording extract a stimulus-locked event from accompanying noise by averaging a large number of sequentially obtained responses. This approach is valid only to the extent that the nervous system's electrical response to successive stimuli is identical. The technique is suboptimal for recording unstable evoked potentials which vary with the subject's state and attention. Similarly, standard methods are suboptimal for efficiently analyzing rapid changes such as may be seen in the operating room. We developed an evoked potential recording method that reconstructs the individual evoked responses (or small subaverages of evoked potentials) to a series of stimuli. First, the raw data from an entire series of one to several hundred responses are recorded digitally. Using a frequency domain two-dimensional filter, the data are then filtered twice, once along the data sequence axis for each trial, and again along the cross-trial sequence axis for comparable frequency coefficients in sequential trials. The reconstructed filtered evoked potentials are plotted, with successive responses stacked for easy tracking of component changes.