Remodeling the light-adapted electroretinogram using a bayesian statistical approach - Marek Brabec; Fernando Marmolejo-Ramos; Lynne Loh; Irene O. Lee; Mikhail Kulyabin; Aleksei Zhdanov; Hugo Posada-Quintero; Dorothy A. Thompson; Paul A. Constable (BMC Research Notes)
Abstract Objective To present a remodeling of the electroretinogram waveform using a covariance matrix to identify regions of interest and distinction between a control and attention deficit/hyperactivity disorder (ADHD) group. Electroretinograms were recorded in n = 25 ADHD (16 male; age 11.9 ± 2.7 years) and n = 38 (8 male; age 10.4 ± 2.8 years neurotypical control participants as part of a broad study into the determining if the electroretinogram could be a biomarker for ADHD. Flash strengths of 0.6 and 1.2 log cd.s.m− 2 on a white 40 cd.m− 2 background were used. Averaged waveforms from each eye and flash strength were analyzed with Bayesian regularization of the covariance matrices using 100 equal length time intervals. The eigenvalues of the covariance matrices were ranked for each group to indicate the degree of complexity within the regularized waveforms. Results The correlation matrices indicated less correlation within the waveforms for the ADHD group in time intervals beyond 70 msec. The eigenvalue plots suggest more complexity within the ADHD group compared to the control group. Consideration of the correlation structure between ERG waveforms from different populations may reveal additional features for identifying group differences in clinical populations.