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.

Behavioural and Brain Sciences Unit Population Policy and Practice Programme Great Ormond Street Institute of Child Health University College London University College London London UK

Biomedical Engineering Department University of Connecticut Storrs CT 06269 USA

College of Education Psychology and Social Work Flinders University Adelaide Australia

College of Nursing and Health Sciences Flinders University Caring Futures Institute Adelaide Australia

Great Ormond Street Institute for Child Health University College London University College London London UK

Institute of Computer Science Czech Academy of Sciences Pod Vodarenskou Vezi 2 Prague 8 182 00 Czech Republic

National Institute of Public Health Srobarova 48 Prague 10 100 00 Czech Republic

Pattern Recognition Lab Department of Computer Science Friedrich Alexander Universitat Erlangen Nurnberg 91058 Erlangen Germany

Tony Kriss Visual Electrophysiology Unit Clinical and Academic Department of Ophthalmology Great Ormond Street Hospital for Children NHS Foundation Trust London UK

VisioMed AI Moscow Russia

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