A facile and comprehensive algorithm for electrical response identification in mouse retinal ganglion cells.

Area of Science:

• Neuroscience
• Biomedical Engineering
• Ophthalmology

Background:

• Retinal prostheses aim to restore vision in degenerative diseases by electrically stimulating retinal ganglion cells (RGCs).
• Current stimulation methods face challenges with unstable effects and imprecise positioning.
• Optimizing electrical pulse parameters is essential for safe and effective RGC stimulation.

Purpose of the Study:

• To determine optimal pulse parameters for precise and safe electrical stimulation of RGCs.
• To develop and validate an automated algorithm for electrophysiological data processing and response identification.
• To enhance the efficacy of neural prostheses for vision restoration.

Main Methods:

• Ex vivo stimulation of wild-type mouse RGCs using a microelectrode array (MEA) system.
• Application of biphasic voltages (cathode-first) with a 25 ms pulse width and varying amplitudes.
• Development of an algorithm for automated spike-sorting and electrical response identification.

Main Results:

• Identified an optimal pulse amplitude range of 0.43 V to 1.3 V for RGC stimulation.
• Recorded from a total of 1193 RGC units, with 151 units responsive to stimulation.
• The proposed automated algorithm demonstrated high consistency with manual data processing.

Conclusions:

• The developed algorithm significantly speeds up electrophysiological data analysis.
• Optimized pulse parameters enhance the precision and safety of neural prosthesis stimulation.
• This approach holds promise for improving visual function restoration in patients with retinal degeneration.