Thomas Zenkel @thomaszen.bsky.social · 23/07/2026openretina additionally includes tools for in silico analysis of trained models like stimulus optimisation, weight visualisation, response-tuning maps, and gradient-field analyses. 100
Thomas Zenkel @thomaszen.bsky.social · 23/07/2026openretina provides a reproducible training pipeline and unified evaluation metrics for benchmarking models within and across datasets. The current benchmarks also show that substantial explainable variance remains uncaptured by existing models. 100
Thomas Zenkel @thomaszen.bsky.social · 23/07/2026The models build on the widely used Core + Readout architecture: a shared Core extracts visual features, while neuron-specific Readouts map those features to predicted responses for individual retinal ganglion cells. 100
Thomas Zenkel @thomaszen.bsky.social · 23/07/2026📣 Our paper introducing openretina, a collaborative framework for retina modelling across datasets and species, is now published as an eLife Reviewed Preprint. Paper: elifesciences.org/reviewed-pre... Code: github.com/open-retina/... Docs: open-retina.org 12911
