Karamanlis_Gollisch_2023_RGC_spiketrains_natural_movies_and_subunit_models

Karamanlis_Gollisch_2023_RGC_spiketrains_natural_movies_and_subunit_models

Spike train data from marmoset and mouse retinal ganglion cells under stimulation with natural movies, flashed and flickering gratings, and spatiotemporal white noise.

Accompanying the manuscript:

Karamanlis D, Khani MH, Schreyer HM, Zapp SJ, Mietsch M, Gollisch T: Natural stimuli drive concerted nonlinear responses in populations of retinal ganglion cells

For information about the structure of the repository, the format of the data, and the reconstruction of applied visual stimuli, see the file Manual.pdf.

If you plan to use this data for a publication, please inform us about it and don’t forget to cite the original paper (see reference above) as well as the source of the data.

Computer code for fitting subunit grid models to the data of this repository and evaluating the obtained models on natural stimuli is available here: https://github.com/dimokaramanlis/subunit_grid_model/

Contact: Tim Gollisch, Email: tim.gollisch@med.uni-goettingen.de, Website: https://www.retina.uni-goettingen.de/