Simulated and recorded responses of mouse retinal bipolar cells to the chirp stimulus

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Data: Removing Inter-Experimental Variability from Functional Data in Systems Neuroscience

This repository hosts the data of Gonschorek, Höfling et al. (2021), Removing Inter-Experimental Variability from Functional Data in Systems Neuroscience, NeurIPS 2021. The corresponding code for the implementation can be found on GitHub.

The files contain the following data and information:

bio/bc_dataset_A (pickle):
- This file contains the preprocessed bipolar cell data in response to the local and full-field chirp, their IPL (inner plexiform layer) depths and cell type labels obtained from Franke, Berens et al. (2017), Inhibition decorrelates visual feature representation in the inner retina, Nature. This dataset is licensed under the CC0 1.0 Universal (CC0 1.0) Public Domain Dedication and can be downloaded in full (incl. raw data) at datadryad
bio/bc_dataset_B (pickle)
- This file contains the preprocessed bipolar cell data in response to the local and full-field chirp and their IPL depths obtained from Zhao, Klindt et al. (2020), The temporal structure of the inner retina at a single glance, Scientific Reports.
ipl/BC_Profiles_Helmstaedter (txt)
- This file contains electron-microscopy (EM) data of axonal stratification profiles of bipolar cell types.
- array of shape 400x14, array[d, t] = p(IPL depth = d|BC type = t)
ipl/ipl (mat)
- Matlab file containing a dictionary with keys "d" and "prior"; d: 400x1 array, IPL depth samples; prior: 400 x 14 array, with array[d, t] = p(BC type = t|IPL depth = d).
silico/sim_dataset (pickle)
- This file contains the dataset object of bipolar cell responses to the chirp stimulus simulated using the model described in Schröder, Klindt et al. (2020), System Identification with Biophysical Constraints: A Circuit Model of the Inner Retina, NeurIPS 2020.

datacite.yml
Title	Simulated and recorded responses of mouse retinal bipolar cells to the chirp stimulus
Authors	Gonschorek,Dominic;University of Tübingen Höfling,Larissa;University of Tübingen Szatko,Klaudia;University of Tübingen Franke,Katrin;University of Tübingen Schubert,Timm;University of Tübingen Dunn,Benjamin;Norwegian University of Science and Technology Berens,Philipp;University of Tübingen Klindt,David;University of Tübingen Euler,Thomas;University of Tübingen
Description	Simulated and recorded responses of mouse retinal bipolar cells to the chirp stimulus
License	Creative Commons CC BY-NC-SA (https://creativecommons.org/licenses/by-nc-sa/4.0/)
References	Removing Inter-Experimental Variability from Functional Data in Systems Neuroscience (2021) Dominic Gonschorek, Larissa Hoefling, Klaudia P Szatko, Katrin Franke, Timm Schubert, Benjamin Dunn, Philipp Berens, David A Klindt, Thomas Euler bioRxiv 2021.10.29.466492; doi: https://doi.org/10.1101/2021.10.29.466492 [doi:10.1101/2021.10.29.466492 ] (IsSupplementTo) Franke, K., Berens, P., Schubert, T., Bethge, M., Euler, T., & Baden, T. (2017). Inhibition decorrelates visual feature representations in the inner retina. Nature, 542(7642), 439–444. https://doi.org/10.1038/nature21394 [10.1038/nature21394] (IsSupplementTo) Zhao, Z., Klindt, D. A., Maia Chagas, A., Szatko, K. P., Rogerson, L., Protti, D. A., … Euler, T. (2020). The temporal structure of the inner retina at a single glance. Scientific Reports, 10(1), 4399. https://doi.org/10.1038/s41598-020-60214-z [10.1038/s41598-020-60214-z] (IsSupplementTo) Helmstaedter, M., Briggman, K. L., Turaga, S. C., Jain, V., Seung, H. S., & Denk, W. (2013). Connectomic reconstruction of the inner plexiform layer in the mouse retina. Nature, 500(7461), 168–174. https://doi.org/10.1038/nature12346 [10.1038/nature12346] (IsDescribedBy) Behrens, C., Schubert, T., Haverkamp, S., Euler, T., & Berens, P. (2016). Connectivity map of bipolar cells and photoreceptors in the mouse retina. ELife, 5(NOVEMBER2016), 1–20. https://doi.org/10.7554/eLife.20041 [10.7554/eLife.20041] (IsDescribedBy)
Funding	DFG, 335549539/GRK2381 DFG, 276693517/CRC1233 DFG, Machine Learning Cluster of Excellence, EXC number 2064/1 - Project #390727645 BMBF, Tübingen AI Center, FKZ: 01IS18039A Research Council of Norway, 90532703/FRIPRO
Keywords	neuroscience retina bipolar cells two-photon microscopy synthetic data inter-experimental variability
Resource Type	Dataset

README.md

Data: Removing Inter-Experimental Variability from Functional Data in Systems Neuroscience