Abstract
Purpose: :
It is well known that the cornea is not isopotential following full-field, homogeneous photic stimulation. It has also been shown that the distribution of activity across the retina affects the distribution of potentials across the cornea. The degree to which this phenomenon affects electroretinogram (ERG) recording is of interest, especially with regard to measurements of local retinal activity (e.g. the multi-focal ERG). To explore the relationship between local retinal activity and local corneal potentials, a detailed finite-element (FE) model of a human eye was constructed, incorporating several anatomical details relevant to the bioelectric events that shape the ERG. To validate the model, corneal potentials must be accurately measured at several locations simultaneously, referred to here as the multi-electrode electroretinogram (meERG).
Methods: :
The three-dimensional FE eye model includes all major ocular structures (including retina, RPE and choroid), adjacent extraocular tissues, and the approximate spatial distribution of rod and cone photoreceptors. A 33-channel prototype electrode array was constructed, using gold electrodes in a PMMA substrate; meERG potentials were recorded in healthy dark-adapted (DA) eyes and analyzed for a-wave amplitude. Corresponding local corneal potentials were predicted using the model. The difference at each of the 33 electrode locations is evaluated (measured - simulated); this difference is then used to optimize and validate the model.
Results: :
The 33-channel meERG was successfully recorded; measured and simulated potentials differed by < 7 % prior to model optimization.
Conclusions: :
Based on the success of the 33-channel prototype, design of a 57-channel meERG contact lens electrode array emphasizes close fit of the lens to the cornea, as well as comfort and safety for the subject. Following accumulation of additional meERG data sets, the validated eye model may be used to answer several questions related to electrode geometry and ERG signal interpretation.
Keywords: computational modeling • electroretinography: non-clinical • electroretinography: clinical