Spike train data from mouse retinal ganglion cells under stimulation with natural images

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code_for_stim_reconstruction 6bc4c25c0d Updated .raw files, added code for stimulus reconstruction 3 anos atrás
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README.md

Karamanlis_Gollisch_2021_RGC_spiketrains_natural_image_encoding

Spike train data from mouse retinal ganglion cells under stimulation with natural images.

Accompanying the paper:

Karamanlis D and Gollisch T (2021) Nonlinear spatial integration underlies the diversity of retinal ganglion cell responses to natural images. J Neurosci 41:3479-3498.

Pubmed link: https://pubmed.ncbi.nlm.nih.gov/33664129/

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.

datacite.yml
Title Dataset - Mouse retinal ganglion cell responses to natural images and spatial-integration analysis
Authors Karamanlis,Dimokratis;University Medical Center Göttingen;ORCID:0000-0002-9469-5020
Gollisch,Tim;University Medical Center Göttingen;ORCID:0000-0003-3998-533X
Description Data sets accompanying Karamanlis and Gollisch, Journal of Neuroscience 2021: Nonlinear spatial integration underlies the diversity of retinal ganglion cell responses to natural images.
License Creative Commons Attribution-ShareAlike 4.0 International (https://creativecommons.org/licenses/by-sa/4.0/)
References Karamanlis D, Gollisch T (2021), Nonlinear spatial integration underlies the diversity of retinal ganglion cell responses to natural images, J Neurosci 41:3479-3498 [doi:10.1523/JNEUROSCI.3075-20.2021] (IsSupplementTo)
Funding DFG, 154113120
DFG, 432680300
EU, ERC.724822
Boehringer Ingelheim Fonds
Keywords Neuroscience
Electrophysiology
Multielectrode Arrays
Retina
Ganglion Cells
Spike trains
Mouse
Spatial integration
Resource Type Dataset