ANID Fondecyt Regular 1241202: Analysis of electrophysiological retinal signals using biological complexity in Alzheimer's disease patients

Max Chacón, Leo Medina, Ruth Pérez, Jean Landerretche
Last updated on Jan 21, 2025 Current Projects
Fondecyt Retina Neurodegenerative Diseases Alzheimer's Disease ERG Complexity Entropy
Max Chacón
Leo Medina
Leo Medina
Principal Investigator

Leo teaches engineering courses at Usach, and his research interests are in the neural engineering and computational neuroscience fields. His work has contributed to understand how nerve fibers respond to electrical stimulation.

Publications

Interpretable machine learning of micro-ERG reveals muted retinal gain tracking in 5xFAD mice
Background. Inexpensive, scalable biomarkers of early Alzheimer’s disease (AD) remain an unmet need, and the retina, as a developmental …
Cite Project Project DOI DOI

Events

Interpretable machine learning of micro-ERG reveals muted retinal gain tracking in 5xFAD mice
Presented a poster on using interpretable machine learning on micro-ERG signals to discriminate WT from 5xFAD retinas, identifying muted gain tracking as a key biomarker.
Aug 31, 2026 — Sep 3, 2026 Centro de Extensión UC - Alameda
Project Project