A large-scale dataset of functional mouse ganglion cell layer responses

We present the AO_SCPLOWLLC_SCPLOW-GCL dataset, a large-scale resource of functional two-photon Ca2+-imaging recordings with rich meta-data information from more than 80,000 cells in the ganglion cell layer (GCL) of the ex vivo mouse retina. Collected over nine years across more than 139 experimental sessions, the dataset provides recordings of light-evoked responses to various stimuli, including a shared set of core stimuli. To enable cell-type-specific analyses, cells are probabilistically assigned to 46 previously characterized functional groups, including retinal ganglion cells and displaced amacrine cells. Further, we assessed the influence of experimental and biological factors on the functional responses and found only small batch effects across experimenters, setups, and recording sessions, highlighting the datasets consistency. The AO_SCPLOWLLC_SCPLOW-GCL dataset offers a comprehensive and standardised reference for studying retinal computation at scale. It supports population-level analyses, computational modelling, and the development of machine learning approaches for biological time-series data. Future releases will expand the dataset with additional mouse lines and light stimuli, creating a growing resource for the vision science community.