Multi-Electrode Contact Electroretinography (MECE)
Team Members Heading link
- Maram Dohal
- Iram Hameeduddin
- Khushal Shah
- Natalie Vazquez
Advisors: Anthony E. Felder, PhD, Miiri Kotche, PhD
Sponsor: John Hetling, PhD, of RetMap
Project Description Heading link
Electroretinography (ERG) is a diagnostic test performed to evaluate retinal function by measuring the electrical potential generated in the retina in response to a flash of light. The Contact Lens Electrode Array (CLEAr Lens), an existing ERG recording system created by John Hetling, analyzes spatial differences on the retina using multiple fluid channel electrodes on the cornea. While versions of CLEar Lens exist for both humans and rats, with 32 and 25 electrodes respectively, this technology has not been developed for mice, despite their popularity as animal models used in research. Mice are preferred due to their lower cost, shorter time to reach maturity, and a wider availability of genetic strains; however, with a corneal diameter of approximately 2.8 mm, a mouse cornea is too small to simply scale down the existing CLEar Lens design.
As such, a revised ERG recording lens, named the Multi-Electrode Contact Electroretinography (MECE) was developed to accommodate the size constraints of a mouse eye, for our project sponsor, Dr. Hetling, and our corporate sponsor, Ocuscience. The MECE Lens consists of a silicone-filled tube with an LED, a PCB to connect the electrodes to a data acquisition system, and five gold wires to contact the eye directly. Recording electrical signals is an important design requirement the MECE lens must fulfill, and in order to do so, the contact surface was molded to conform to the natural shape of the average mouse cornea using silicone, with gold wires placed in five specific corneal locations. Future testing will involve measuring impedance values across each pairing of electrodes, to ensure a proper fit, and recording electrical potential in response to the light stimulus to ultimately compare with expected ERG data and models.
See supporting documentation in the team’s Box drive.