Model based fitting of pattern reversal visually evoked potentials provides a reliable characterization of waveform components.

Objective: To introduce a novel approach to analyzing pattern reversal visual evoked potentials (prVEPs) using a difference-of-gammas model-based fitting method. Methods: prVEP was recorded from uninjured youth ages 11-19 years during pre- or postseason sports evaluation. A difference-of-gammas model fit was used to extract the amplitude, peak time, and peak width of each of four gamma components. The within session reliability and stability of fits across a 6-month period were determined. To demonstrate an application of this analysis, changes in parameters across age were determined. Results: A difference-of-gammas model consisting of four gamma functions was fit to the prVEP of 151 youth. Peak times and amplitudes of functions corresponded to standard measures of the N75, P100, and N135 components respectively, and a late gamma peak (mean peak time 219 ms). We extracted the peak width, which increased with each subsequent temporal peak. Parameter fits were reliable within sessions (correlation coefficient >0.92 for all measured parameters; good agreement on Bland-Altman calculation) and were stable between sessions separated by less than 6 months (correlation coefficient > 0.90). Standard peak analysis metrics extracted from the difference-of-gamma model fits were largely consistent with gold-standard peak analysis measurements. Conclusions: The difference-of-gammas model provides a stable and reliable within-participant representation of the global temporal variability of prVEP waveforms across a large sample of youth. Significance: Using difference-of-gammas model to characterize the global temporal variability of the prVEP waveform offers a promising direction to enhance analysis for identifying and following subtle changes in neurologic conditions.