Wavelet Transform improves time-frequency characterization of the Electroretinographic Oscillatory Potentials as compared to Short-Time Fourier Transform across experimental and clinical models

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Purpose: To compare continuous wavelet transform (CWT) and short-time Fourier transform (STFT) analyses of the oscillatory potentials (OPs) of the dark-adapted full-field electroretinogram (FFERG). Methods: FFERG recordings from Royal College of Surgeons (RCS) and healthy Brown Norway (BN) rats, wild-type and Atoh7 enhancer-knockout (KO) mice, and patients with diabetic retinopathy and healthy controls were analyzed with STFT and with CWT employing the real Morlet wavelet, after 60 Hz high-pass and sharp 60 Hz notch filtering. Time- and frequency-localized OP features were quantified and the methods compared on detection of transient OP signals. Both were additionally validated using synthetic OP-like bursts of known frequency embedded in each cohort's recorded noise. Results: CWT revealed distinct time-frequency patterns and disease-specific OP alterations across all rat, mouse, and human cohorts, with improved temporal localization and frequency resolution, whereas STFT merged transient features and was more susceptible to noise. CWT-derived dominant-frequency differences reached significance in all three models; the corresponding STFT difference reached significance only in rats (separate tests; methods not directly compared). In synthetic bursts, both methods recovered injected frequencies to within 1-2.5 Hz, but only CWT resolved two bursts separated by 15 ms. Conclusions: CWT employing the real Morlet wavelet provides a robust, physiologically relevant evaluation of OPs, with improved temporal localization and reduced spectral dispersion relative to STFT in clinical and experimental settings. Translational Relevance: CWT analysis may improve the characterization of inner retinal dysfunction by preserving transient OP time-frequency structure, as illustrated in preclinical rodent models and diabetic retinopathy patients.