Resumo

Functional evaluation by measuring the electrophysiological integrity of a nerve after injury and recuperation can be challenging due to difficulties in interpreting electrophysiological responses, particularly if responses are fragmented, incoherent and dispersed over various latencies. Our objective was to develop and test an algorithm based on cross-correlation for quantifying compound action potential responses. The algorithm detects and measures events automatically, and works by comparing evoked responses to a generic standardized signal, measuring the magnitude of each event as an arbitrary unit of energy for each point in time. To test the algorithm, we obtained data from injured and intact male rat sciatic nerve (CNAP) and tibialis anterior muscle (CMAP) responses of varying magnitudes that were elicited by altering stimulus intensity (nerve) or following frequency (muscle). We compared these responses evaluated by our algorithm to the most widely used method used for quantifying such signals, i.e., the peak-to-peak amplitude. Our algorithm was able to successfully detect and quantified normal as well as greatly attenuated CMAPs and CNAPs, and has several advantages over traditional methods of quantification, such as it is automatic, objective, does not rely on the observer to identify and/or measure peaks, and can detect small responses that occur within background noise levels that is typical of such responses during regeneration. This algorithm therefore serves as a useful tool for studying evoked compound action potentials in regeneration studies.