A method for estimating intrinsic noise in electroretinographic (ERG) signals - Zele, Andrew J.; Feigl, Beatrix; Kambhampati, Pradeep K.; Hathibelagal, Amithavikram R.; Kremers, Jan (Documenta Ophthalmologica, 2015)
To develop a signal processing paradigm for extracting ERG responses to temporal sinusoidal modulation with contrasts ranging from below perceptual threshold to suprathreshold contrasts and estimate the magnitude of intrinsic noise in ERG signals at different stimulus contrasts.Photopic test stimuli were generated using a 4-primary Maxwellian view optical system. The 4-primary lights were sinusoidally temporally modulated in-phase (36 Hz; 2.5-50 % Michelson contrast). The stimuli were presented in 1-s epochs separated by a 1-ms blank interval and repeated 160 times (160.160-s duration) during the recording of the continuous flicker ERG from the right eye using DTL fibre electrodes. After artefact rejection, the ERG signal was extracted using Fourier transforms in each of the 1-s epochs where a stimulus was presented. The signal processing allows for computation of the intrinsic noise distribution in addition to the signal-to-noise (SNR) ratio.We provide the initial report that the ERG intrinsic noise distribution is independent of stimulus contrast, whereas SNR decreases linearly with decreasing contrast until the noise limit at 2.5 %. The 1-ms blank intervals between epochs de-correlated the ERG signal at the line frequency (50 Hz) and thus increased the SNR of the averaged response. We confirm that response amplitude increases linearly with stimulus contrast. The phase response shows a shallow positive relationship with stimulus contrast.This new technique will enable recording of intrinsic noise in ERG signals above and below perceptual visual threshold and is suitable for measurement of continuous rod and cone ERGs across a range of temporal frequencies, and post-receptoral processing in the primary retinogeniculate pathways at low stimulus contrasts. The intrinsic noise distribution may have application as a biomarker for detecting changes in disease progression or treatment efficacy.
EVALuna2:21230