Chapter 3 Conclusion

Retinal degeneration — the subfield most directly concerned with understanding and treating retinal disease — has developed rapidly over the past couple decades. Nourished by both technical advances and growth of computing power, this explosion in neuroscience research has, in turn, started developments in statistical methods. We use these devices to collect, analyze, and model complex, high-dimensional neural data at the retina-level. This thesis, we hope, adds to the literature by improving the understanding of vision restoration.

We take this opportunity to outline one obvious avenue for future work: what are the effects of targeting the genes we found? Can the retina send the same amount of information after treatment? The possible method for targeting the first question is through using CRISPR techniques. This technology permits targeting genes we isolated in “fake gene therapy” to create true genetic therapies. This would give researchers access to a treatment that addresses misaligned retinal connections.

The second step is to determine whether information rate would be effective in measuring treatment progression. This is an interesting question because it contrasts the question we targeted and would determine the reliability of this physiology metric. Characterizing physiology is multidimensional, and this device would provide an interpretable and concise approach .