Multi-Angular Electroretinography (maERG): Topographic Mapping of the Retinal Function Combining Real and Virtual Electrodes

• Published in: IEEE transactions on biomedical engineering Vol. 68; no. 10; pp. 3173 - 3183
• Main Authors: Gauthier, Mercedes, Brassard-Simard, Antoine, Gauvin, Mathieu, Lachapelle, Pierre, Lina, Jean-Marc
• Format: Journal Article
• Language: English
• Published: United States IEEE 01-10-2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Damage localization; Electrodes; Electroretinogram; Electroretinograms; Electroretinography; Eye; Image reconstruction; Imaging techniques; inverse problem; Inverse problems; multi-electrode; Neuroimaging; Noise levels; Retina; Retinal images; Signal to noise ratio; Skin; Spatial resolution; Topographic mapping; virtual electrodes; wavelet transform
• ISSN: 0018-9294; 1558-2531
• DOI: 10.1109/TBME.2021.3075617

Goal: The full-field electroretinogram (ffERG) is an objective tool to assess global retinal function, though as it is currently done, it is unable to localize sources of retinal dysfunction or damage. To overcome this, we have developed a new way to record multiple spatial derivations of the ERG using the rotating capability of the eye, thus creating "virtual electrodes". We have termed this the multi-angular ERG (or maERG). With only 3 real electrodes and 11 varying gaze positions, we create 33 "virtual electrodes". Methods: We created a realistic electrophysiological and anatomical eye model (i.e., forward model) to reconstruct the retinal activity (i.e., inverse problem) from the 33 virtual electrodes. We simulated 2 pathological scenarios (central and peripheral scotomas), which were compared to their respective theoretical source configurations using an Area under Receiver Operator Characteristic curve metric. Results: Our simulations show that the low-resolution brain electromagnetic tomography algorithm (LORETA) is the best method tested to reconstruct retinal sources when compared to the Minimum Norm Estimate algorithm. Furthermore, a signal to noise ratio of 50 dB is needed to accurately reconstruct the retina's functional map. Conclusion: Our proposed maERG recording method, combined with our solution to the electromagnetic inverse problem enables us to reconstruct the functional map of the human retina. Significance: We believe that this new functional retinal imaging technique will permit earlier detection of retinal malfunction and consequently optimize the clinical monitoring of patients affected with retinopathies.