Behrens, C., Schubert, T., Haverkamp, S., Euler, T., & Berens, P. (2016). Connectivity map of bipolar cells and photoreceptors in the mouse retina. https://doi.org/10.1101/065722
Collaboration: All (Philipp Berens) and Neural (Christian Behrens).

Rogerson, L. E., Behrens, C., Euler, T., Berens, P., & Schubert, T. (2017). Connectomics of synaptic microcircuits: lessons from the outer retina. The Journal of Physiology, 595(16), 5517–5524. Portico. https://doi.org/10.1113/jp273671
Collaboration: All (Philipp Berens) and Neural (Christian Behrens, Luke Rogerson).

Leibig, C., Allken, V., Ayhan, M. S., Berens, P., & Wahl, S. (2017). Leveraging uncertainty information from deep neural networks for disease detection. Scientific Reports, 7(1). https://doi.org/10.1038/s41598-017-17876-z
Collaboration: All (Philipp Berens) and MedML (Murat Seçkin Ayhan).

Chapot, C. A., Behrens, C., Rogerson, L. E., Baden, T., Pop, S., Berens, P., Euler, T., & Schubert, T. (2017). Local signals in mouse horizontal cell dendrites. https://doi.org/10.1101/143909
Collaboration: All (Philipp Berens) and Neural (Christian Behrens, Luke Rogerson).

Nonnenmacher, M., Behrens, C., Berens, P., Bethge, M., & Macke, J. H. (2017). Signatures of criticality arise from random subsampling in simple population models. PLOS Computational Biology, 13(10), e1005718. https://doi.org/10.1371/journal.pcbi.1005718
Collaboration: All (Philipp Berens) and Neural (Christian Behrens).

Berens, P., Freeman, J., Deneux, T., Chenkov, N., McColgan, T., Speiser, A., Macke, J. H., Turaga, S. C., Mineault, P., Rupprecht, P., Gerhard, S., Friedrich, R. W., Friedrich, J., Paninski, L., Pachitariu, M., Harris, K. D., Bolte, B., Machado, T. A., Ringach, D., … Bethge, M. (2018). Community-based benchmarking improves spike rate inference from two-photon calcium imaging data. PLOS Computational Biology, 14(5), e1006157. https://doi.org/10.1371/journal.pcbi.1006157
Collaboration: All (Philipp Berens) and Neural (Luke Rogerson).

Diamantaki, M., Coletta, S., Nasr, K., Zeraati, R., Laturnus, S., Berens, P., Preston-Ferrer, P., & Burgalossi, A. (2018). Manipulating Hippocampal Place Cell Activity by Single-Cell Stimulation in Freely Moving Mice. Cell Reports, 23(1), 32–38. https://doi.org/10.1016/j.celrep.2018.03.031
Collaboration: All (Philipp Berens) and Neural (Sophie Laturnus).

Rogerson, L. E., Zhao, Z., Franke, K., Euler, T., & Berens, P. (2019). Bayesian hypothesis testing and experimental design for two-photon imaging data. PLOS Computational Biology, 15(8), e1007205. https://doi.org/10.1371/journal.pcbi.1007205
Collaboration: All (Philipp Berens) and Neural (Luke Rogerson).

Scala, F., Kobak, D., Shan, S., Bernaerts, Y., Laturnus, S., Cadwell, C. R., Hartmanis, L., Froudarakis, E., Castro, J. R., Tan, Z. H., Papadopoulos, S., Patel, S. S., Sandberg, R., Berens, P., Jiang, X., & Tolias, A. S. (2019). Layer 4 of mouse neocortex differs in cell types and circuit organization between sensory areas. Nature Communications, 10(1). https://doi.org/10.1038/s41467-019-12058-z
Collaboration: All (Philipp Berens), Embedding (Dmitry Kobak), and Neural (Yves Bernaerts, Sophie Laturnus).

Berens, P., & Ayhan, M. S. (2019). Proprietary data formats block health research. Nature, 565(7740), 429–429. https://doi.org/10.1038/d41586-019-00231-9
Collaboration: All (Philipp Berens) and MedML (Murat Seçkin Ayhan).

Kobak, D., & Berens, P. (2019). The art of using t-SNE for single-cell transcriptomics. Nature Communications, 10(1). https://doi.org/10.1038/s41467-019-13056-x
Collaboration: All (Philipp Berens) and Embedding (Dmitry Kobak).

Laturnus, S., Kobak, D., & Berens, P. (2020). A Systematic Evaluation of Interneuron Morphology Representations for Cell Type Discrimination. Neuroinformatics, 18(4), 591–609. https://doi.org/10.1007/s12021-020-09461-z
Collaboration: All (Philipp Berens), Embedding (Dmitry Kobak), and Neural (Sophie Laturnus).

Oesterle, J., Behrens, C., Schröder, C., Herrmann, T., Euler, T., Franke, K., Smith, R. G., Zeck, G., & Berens, P. (2020). Bayesian inference for biophysical neuron models enables stimulus optimization for retinal neuroprosthetics. https://doi.org/10.1101/2020.01.08.898759
Collaboration: All (Philipp Berens) and Neural (Christian Behrens, Jonathan Oesterle).

Cadwell, C. R., Scala, F., Fahey, P. G., Kobak, D., Mulherkar, S., Sinz, F. H., Papadopoulos, S., Tan, Z. H., Johnsson, P., Hartmanis, L., Li, S., Cotton, R. J., Tolias, K. F., Sandberg, R., Berens, P., Jiang, X., & Tolias, A. S. (2020). Cell type composition and circuit organization of clonally related excitatory neurons in the juvenile mouse neocortex. ELife, 9. CLOCKSS. https://doi.org/10.7554/elife.52951
Collaboration: All (Philipp Berens) and Embedding (Dmitry Kobak).

Ayhan, M. S., Kühlewein, L., Aliyeva, G., Inhoffen, W., Ziemssen, F., & Berens, P. (2020). Expert-validated estimation of diagnostic uncertainty for deep neural networks in diabetic retinopathy detection. Medical Image Analysis, 64, 101724. https://doi.org/10.1016/j.media.2020.101724
Collaboration: All (Philipp Berens) and MedML (Murat Seçkin Ayhan).

Laturnus, S., von Daranyi, A., Huang, Z., & Berens, P. (2020). MorphoPy: A python package for feature extraction of neural morphologies. Journal of Open Source Software, 5(52), 2339. https://doi.org/10.21105/joss.02339
Collaboration: All (Philipp Berens, Ziwei Huang) and Neural (Sophie Laturnus).

Höfling, L., Oesterle, J., Berens, P., & Zeck, G. (2020). Probing and predicting ganglion cell responses to smooth electrical stimulation in healthy and blind mouse retina. Scientific Reports, 10(1). https://doi.org/10.1038/s41598-020-61899-y
Collaboration: All (Philipp Berens) and Neural (Jonathan Oesterle).

Schröder, C., Klindt, D., Strauss, S., Franke, K., Bethge, M., Euler, T., & Berens, P. (2020). System Identification with Biophysical Constraints: A Circuit Model of the Inner Retina. https://doi.org/10.1101/2020.06.16.154203
Collaboration: All (Philipp Berens) and Neural (Sarah Strauß).

Zhao, Z., Klindt, D. A., Maia Chagas, A., Szatko, K. P., Rogerson, L., Protti, D. A., Behrens, C., Dalkara, D., Schubert, T., Bethge, M., Franke, K., Berens, P., Ecker, A. S., & Euler, T. (2020). The temporal structure of the inner retina at a single glance. Scientific Reports, 10(1). https://doi.org/10.1038/s41598-020-60214-z
Collaboration: All (Philipp Berens) and Neural (Christian Behrens, Luke Rogerson).

Lause, J., Berens, P., & Kobak, D. (2021). Analytic Pearson residuals for normalization of single-cell RNA-seq UMI data. Genome Biology, 22(1). https://doi.org/10.1186/s13059-021-02451-7
Collaboration: All (Philipp Berens) and Embedding (Dmitry Kobak, Jan Lause).

Strauss, S., Korympidou, M. M., Ran, Y., Franke, K., Schubert, T., Baden, T., Berens, P., Euler, T., & Vlasits, A. L. (2021). Center-surround interactions underlie bipolar cell motion sensing in the mouse retina. https://doi.org/10.1101/2021.05.31.446404
Collaboration: All (Philipp Berens) and Neural (Sarah Strauß).

Schröder, C., Oesterle, J., Berens, P., Yoshimatsu, T., & Baden, T. (2021). Distinct Synaptic Transfer Functions in Same-Type Photoreceptors. https://doi.org/10.1101/2021.02.24.432674
Collaboration: All (Philipp Berens) and Neural (Jonathan Oesterle).

Huang, Z., Ran, Y., Euler, T., & Berens, P. (2021). Estimating smooth and sparse neural receptive fields with a flexible spline basis. https://doi.org/10.1101/2021.03.31.437831
Collaboration: All (Philipp Berens, Ziwei Huang) and Neural (Jonathan Oesterle).

Ilanchezian, I., Kobak, D., Faber, H., Ziemssen, F., Berens, P., & Ayhan, M. S. (2021). Interpretable gender classification from retinal fundus images using BagNets. https://doi.org/10.1101/2021.06.21.21259243
Collaboration: All (Philipp Berens), Embedding (Dmitry Kobak), and MedML (Murat Seçkin Ayhan, Indu Ilanchezian).

Laturnus, S., & Berens, P. (2021). MorphVAE: Generating Neural Morphologies from 3D-Walks using a Variational Autoencoder with Spherical Latent Space. https://doi.org/10.1101/2021.06.14.448271
Collaboration: All (Philipp Berens) and Neural (Sophie Laturnus).

Kobak, D., Bernaerts, Y., Weis, M. A., Scala, F., Tolias, A. S., & Berens, P. (2021). Sparse Reduced-Rank Regression for Exploratory Visualisation of Paired Multivariate Data. Journal of the Royal Statistical Society Series C: Applied Statistics, 70(4), 980–1000. https://doi.org/10.1111/rssc.12494
Collaboration: All (Philipp Berens), Embedding (Dmitry Kobak), and Neural (Yves Bernaerts).

Strauss, S., Korympidou, M. M., Ran, Y., Franke, K., Schubert, T., Baden, T., Berens, P., Euler, T., & Vlasits, A. L. (2022). Center-surround interactions underlie bipolar cell motion sensitivity in the mouse retina. Nature Communications, 13(1). https://doi.org/10.1038/s41467-022-32762-7
Collaboration: All (Philipp Berens) and Neural (Sarah Strauß).

Ayhan, M. S., Kümmerle, L. B., Kühlewein, L., Inhoffen, W., Aliyeva, G., Ziemssen, F., & Berens, P. (2022). Clinical validation of saliency maps for understanding deep neural networks in ophthalmology. Medical Image Analysis, 77, 102364. https://doi.org/10.1016/j.media.2022.102364
Collaboration: All (Philipp Berens) and MedML (Murat Seçkin Ayhan).

Oesterle, J., Krämer, N., Hennig, P., & Berens, P. (2022). Probabilistic solvers enable a straight-forward exploration of numerical uncertainty in neuroscience models. Journal of Computational Neuroscience, 50(4), 485–503. https://doi.org/10.1007/s10827-022-00827-7
Collaboration: All (Philipp Berens) and Neural (Jonathan Oesterle).

Behrens, C., Yadav, S. C., Korympidou, M. M., Zhang, Y., Haverkamp, S., Irsen, S., Schaedler, A., Lu, X., Liu, Z., Lause, J., St-Pierre, F., Franke, K., Vlasits, A., Dedek, K., Smith, R. G., Euler, T., Berens, P., & Schubert, T. (2022). Retinal horizontal cells use different synaptic sites for global feedforward and local feedback signaling. Current Biology, 32(3), 545-558.e5. https://doi.org/10.1016/j.cub.2021.11.055
Collaboration: All (Philipp Berens), Embedding (Jan Lause), and Neural (Christian Behrens).

Boreiko, V., Ilanchezian, I., Seçkin Ayhan, M., Müller, S., Koch, L. M., Faber, H., Berens, P., & Hein, M. (2022). Visual explanations for the detection of diabetic retinopathy from retinal fundus images. https://doi.org/10.1101/2022.07.06.22276633
Collaboration: All (Philipp Berens) and MedML (Murat Seçkin Ayhan, Indu Ilanchezian, Lisa Koch, Sarah Müller).

Ayhan, M. S., Faber, H., Kühlewein, L., Inhoffen, W., Aliyeva, G., Ziemssen, F., & Berens, P. (2023). Multitask Learning for Activity Detection in Neovascular Age-Related Macular Degeneration. Translational Vision Science &amp; Technology, 12(4), 12. https://doi.org/10.1167/tvst.12.4.12
Collaboration: All (Philipp Berens) and MedML (Murat Seçkin Ayhan).

Congiu, M., Mondoloni, S., Zouridis, I. S., Schmors, L., Lecca, S., Lalive, A. L., Ginggen, K., Deng, F., Berens, P., Paolicelli, R. C., Li, Y., Burgalossi, A., & Mameli, M. (2023). Plasticity of neuronal dynamics in the lateral habenula for cue-punishment associative learning. Molecular Psychiatry, 28(12), 5118–5127. https://doi.org/10.1038/s41380-023-02155-3
Collaboration: All (Philipp Berens) and Neural (Lisa Schmors).

Donteu Djoumessi, K. R., Ilanchezian, I., Kühlewein, L., Faber, H., Baumgartner, C. F., Bah, B., Berens, P., & Koch, L. M. (2023). Sparse Activations for Interpretable Disease Grading. https://doi.org/10.1101/2023.03.07.23286895
Collaboration: All (Philipp Berens) and MedML (Kerol Djoumessi, Indu Ilanchezian, Lisa Koch).

Höfling, L., Szatko, K. P., Behrens, C., Deng, Y., Qiu, Y., Klindt, D. A., Jessen, Z., Schwartz, G. W., Bethge, M., Berens, P., Franke, K., Ecker, A. S., & Euler, T. (2024). A chromatic feature detector in the retina signals visual context changes. ELife, 13. CLOCKSS. https://doi.org/10.7554/elife.86860
Collaboration: All (Philipp Berens) and Neural (Christian Behrens).

Zouridis, I. S., Schmors, L., Lecca, S., Congiu, M., Mameli, M., Berens, P., & Burgalossi, A. (2024). Aversion encoding and behavioral state modulation of lateral habenula neurons. https://doi.org/10.1101/2024.09.09.612004
Collaboration: All (Philipp Berens) and Neural (Lisa Schmors).

Müller, S., Fay, L., Koch, L. M., Gatidis, S., Küstner, T., & Berens, P. (2024). Benchmarking Dependence Measures to Prevent Shortcut Learning in Medical Imaging. Machine Learning in Medical Imaging, 53–62. https://doi.org/10.1007/978-3-031-73290-4_6
Collaboration: All (Philipp Berens) and MedML (Lisa Koch, Sarah Müller).

Deistler, M., Kadhim, K. L., Pals, M., Beck, J., Huang, Z., Gloeckler, M., Lappalainen, J. K., Schröder, C., Berens, P., Gonçalves, P. J., & Macke, J. H. (2024). Jaxley: Differentiable simulation enables large-scale training of detailed biophysical models of neural dynamics. https://doi.org/10.1101/2024.08.21.608979
Collaboration: All (Philipp Berens, Ziwei Huang) and Neural (Jonas Beck, Kyra Kadhim).

Koch, L. M., Baumgartner, C. F., & Berens, P. (2024). Distribution shift detection for the postmarket surveillance of medical AI algorithms: a retrospective simulation study. Npj Digital Medicine, 7(1). https://doi.org/10.1038/s41746-024-01085-w
Collaboration: All (Philipp Berens) and MedML (Lisa Koch).

Varghese, J., Schuster, A., Poschkamp, B., Yildirim, K., Oehm, J., Berens, P., Müller, S., Gervelmeyer, J., Koch, L., Hoffmann, K., Sedlmayr, M., Kakkassery, V., Kohlbacher, O., Merle, D., Bartz-Schmidt, K. U., Ueffing, M., Stahl, D., Leddig, T., Bialke, M., … Eter, N. (2024). EyeMatics: An Ophthalmology Use Case Within the German Medical Informatics Initiative. JMIR Medical Informatics, 12, e60851–e60851. https://doi.org/10.2196/60851
Collaboration: All (Philipp Berens) and MedML (Julius Gervelmeyer, Lisa Koch, Sarah Müller).

Gervelmeyer, J., Müller, S., Djoumessi, K., Merle, D., Clark, S. J., Koch, L., & Berens, P. (2024). Interpretable-by-design Deep Survival Analysis for Disease Progression Modeling. https://doi.org/10.1101/2024.07.11.24310270
Collaboration: All (Philipp Berens) and MedML (Kerol Djoumessi, Julius Gervelmeyer, Lisa Koch, Sarah Müller).

Ayhan, M. S., Neubauer, J., Uzel, M. M., Gelisken, F., & Berens, P. (2024). Interpretable detection of epiretinal membrane from optical coherence tomography with deep neural networks. Scientific Reports, 14(1). https://doi.org/10.1038/s41598-024-57798-1
Collaboration: All (Philipp Berens) and MedML (Murat Seçkin Ayhan).

González-Márquez, R., Berens, P., & Kobak, D. (2024). Meet the authors: Rita González-Márquez, Philipp Berens, and Dmitry Kobak. Patterns, 5(6), 100993. https://doi.org/10.1016/j.patter.2024.100993
Collaboration: All (Philipp Berens) and Embedding (Rita González Márquez).

Lause, J., Kobak, D., & Berens, P. (2024). The art of seeing the elephant in the room: 2D embeddings of single-cell data do make sense. https://doi.org/10.1101/2024.03.26.586728
Collaboration: All (Philipp Berens) and Embedding (Dmitry Kobak, Jan Lause).

Djoumessi, K., Bah, B., Kühlewein, L., Berens, P., & Koch, L. (2024). This Actually Looks Like that: Proto-BagNets for Local and Global Interpretability-by-Design. Medical Image Computing and Computer Assisted Intervention – MICCAI 2024, 718–728. https://doi.org/10.1007/978-3-031-72117-5_67
Collaboration: All (Philipp Berens) and MedML (Kerol Djoumessi, Lisa Koch).

Damrich, S., Klockow, M. V., Berens, P., Hamprecht, F. A., & Kobak, D. (2024). Visualizing single-cell data with the neighbor embedding spectrum. https://doi.org/10.1101/2024.04.26.590867
Collaboration: All (Philipp Berens) and Embedding (Sebastian Damrich, Dmitry Kobak).

Djoumessi, K., Huang, Z., Kühlewein, L., Rickmann, A., Simon, N., Koch, L. M., & Berens, P. (2025). An inherently interpretable AI model improves screening speed and accuracy for early diabetic retinopathy. PLOS Digital Health, 4(5), e0000831. https://doi.org/10.1371/journal.pdig.0000831
Collaboration: All (Philipp Berens, Ziwei Huang) and MedML (Kerol Djoumessi, Lisa Koch).

Mensah, S. O., Neubauer, J., Ayhan, M. S., Djoumessi, K., Koch, L., Uzel, M. M., Gelisken, F., & Berens, P. (2025). Clinically Interpretable Deep Learning via Sparse BagNets for Epiretinal Membrane and Related Pathology Detection. https://doi.org/10.1101/2025.06.05.25329045
Collaboration: All (Philipp Berens) and MedML (Murat Seçkin Ayhan, Kerol Djoumessi, Lisa Koch, Samuel Ofosu Mensah).

Bernaerts, Y., Deistler, M., Gonçalves, P. J., Beck, J., Stimberg, M., Scala, F., Tolias, A. S., Macke, J. H., Kobak, D., & Berens, P. (2025). Combined statistical-biophysical modeling links ion channel genes to physiology of cortical neuron types. Patterns, 101323. https://doi.org/10.1016/j.patter.2025.101323
Collaboration: All (Philipp Berens), Embedding (Dmitry Kobak), and Neural (Jonas Beck, Yves Bernaerts).

Ilanchezian, I., Boreiko, V., Kühlewein, L., Huang, Z., Seçkin Ayhan, M., Hein, M., Koch, L., & Berens, P. (2025). Development and validation of an AI algorithm to generate realistic and meaningful counterfactuals for retinal imaging based on diffusion models. PLOS Digital Health, 4(5), e0000853. https://doi.org/10.1371/journal.pdig.0000853
Collaboration: All (Philipp Berens, Ziwei Huang) and MedML (Murat Seçkin Ayhan, Indu Ilanchezian, Lisa Koch).

Müller, S., Koch, L. M., Lensch, H. P. A., & Berens, P. (2025). Disentangling representations of retinal images with generative models. Medical Image Analysis, 105, 103628. https://doi.org/10.1016/j.media.2025.103628
Collaboration: All (Philipp Berens) and MedML (Lisa Koch, Sarah Müller).

Schmors, L., Kotkat, A. H., Bauer, Y., Huang, Z., Crombie, D., Meyerolbersleben, L. S., Sokoloski, S., Berens, P., & Busse, L. (2025). Effects of corticothalamic feedback depend on visual responsiveness and stimulus type. IScience, 28(6), 112481. https://doi.org/10.1016/j.isci.2025.112481
Collaboration: All (Philipp Berens, Ziwei Huang) and Neural (Lisa Schmors, Sacha Sokoloski).

Gervelmeyer, J., Müller, S., Huang, Z., & Berens, P. (2025). Fundus Image Toolbox: A Python package for fundus image processing. Journal of Open Source Software, 10(108), 7101. https://doi.org/10.21105/joss.07101
Collaboration: All (Philipp Berens, Ziwei Huang) and MedML (Julius Gervelmeyer, Sarah Müller).

Schmidt, G., Heidrich, H., Berens, P., & Müller, S. (2025). Learning Disease State from Noisy Ordinal Disease Progression Labels. Medical Image Computing and Computer Assisted Intervention – MICCAI 2025, 284–293. https://doi.org/10.1007/978-3-032-04971-1_27
Collaboration: All (Philipp Berens) and MedML (Sarah Müller).

Ofosu Mensah, S., Djoumessi, K., & Berens, P. (2025). Prototype-Guided and Lightweight Adapters for Inherent Interpretation and Generalisation in Federated Learning. Medical Image Computing and Computer Assisted Intervention – MICCAI 2025, 464–473. https://doi.org/10.1007/978-3-032-04981-0_44
Collaboration: All (Philipp Berens) and MedML (Kerol Djoumessi, Samuel Ofosu Mensah).

Oesterle, J., Ran, Y., Stahr, P., Kerr, J. N. D., Schubert, T., Berens, P., & Euler, T. (2025). Task-specific regional circuit adaptations in distinct mouse retinal ganglion cells. Science Advances, 11(17). https://doi.org/10.1126/sciadv.adp7075
Collaboration: All (Philipp Berens) and Neural (Jonathan Oesterle).