--- _id: '10816' abstract: - lang: eng text: Pattern separation is a fundamental brain computation that converts small differences in input patterns into large differences in output patterns. Several synaptic mechanisms of pattern separation have been proposed, including code expansion, inhibition and plasticity; however, which of these mechanisms play a role in the entorhinal cortex (EC)–dentate gyrus (DG)–CA3 circuit, a classical pattern separation circuit, remains unclear. Here we show that a biologically realistic, full-scale EC–DG–CA3 circuit model, including granule cells (GCs) and parvalbumin-positive inhibitory interneurons (PV+-INs) in the DG, is an efficient pattern separator. Both external gamma-modulated inhibition and internal lateral inhibition mediated by PV+-INs substantially contributed to pattern separation. Both local connectivity and fast signaling at GC–PV+-IN synapses were important for maximum effectiveness. Similarly, mossy fiber synapses with conditional detonator properties contributed to pattern separation. By contrast, perforant path synapses with Hebbian synaptic plasticity and direct EC–CA3 connection shifted the network towards pattern completion. Our results demonstrate that the specific properties of cells and synapses optimize higher-order computations in biological networks and might be useful to improve the deep learning capabilities of technical networks. acknowledged_ssus: - _id: SSU acknowledgement: We thank A. Aertsen, N. Kopell, W. Maass, A. Roth, F. Stella and T. Vogels for critically reading earlier versions of the manuscript. We are grateful to F. Marr and C. Altmutter for excellent technical assistance, E. Kralli-Beller for manuscript editing, and the Scientific Service Units of IST Austria for efficient support. Finally, we thank T. Carnevale, L. Erdös, M. Hines, D. Nykamp and D. Schröder for useful discussions, and R. Friedrich and S. Wiechert for sharing unpublished data. This project received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement no. 692692, P.J.) and the Fond zur Förderung der Wissenschaftlichen Forschung (Z 312-B27, Wittgenstein award to P.J. and P 31815 to S.J.G.). article_processing_charge: No article_type: original author: - first_name: José full_name: Guzmán, José id: 30CC5506-F248-11E8-B48F-1D18A9856A87 last_name: Guzmán orcid: 0000-0003-2209-5242 - first_name: Alois full_name: Schlögl, Alois id: 45BF87EE-F248-11E8-B48F-1D18A9856A87 last_name: Schlögl orcid: 0000-0002-5621-8100 - first_name: 'Claudia ' full_name: 'Espinoza Martinez, Claudia ' id: 31FFEE2E-F248-11E8-B48F-1D18A9856A87 last_name: Espinoza Martinez orcid: 0000-0003-4710-2082 - first_name: Xiaomin full_name: Zhang, Xiaomin id: 423EC9C2-F248-11E8-B48F-1D18A9856A87 last_name: Zhang - first_name: Benjamin full_name: Suter, Benjamin id: 4952F31E-F248-11E8-B48F-1D18A9856A87 last_name: Suter orcid: 0000-0002-9885-6936 - first_name: Peter M full_name: Jonas, Peter M id: 353C1B58-F248-11E8-B48F-1D18A9856A87 last_name: Jonas orcid: 0000-0001-5001-4804 citation: ama: Guzmán J, Schlögl A, Espinoza Martinez C, Zhang X, Suter B, Jonas PM. How connectivity rules and synaptic properties shape the efficacy of pattern separation in the entorhinal cortex–dentate gyrus–CA3 network. Nature Computational Science. 2021;1(12):830-842. doi:10.1038/s43588-021-00157-1 apa: Guzmán, J., Schlögl, A., Espinoza Martinez, C., Zhang, X., Suter, B., & Jonas, P. M. (2021). How connectivity rules and synaptic properties shape the efficacy of pattern separation in the entorhinal cortex–dentate gyrus–CA3 network. Nature Computational Science. Springer Nature. https://doi.org/10.1038/s43588-021-00157-1 chicago: Guzmán, José, Alois Schlögl, Claudia Espinoza Martinez, Xiaomin Zhang, Benjamin Suter, and Peter M Jonas. “How Connectivity Rules and Synaptic Properties Shape the Efficacy of Pattern Separation in the Entorhinal Cortex–Dentate Gyrus–CA3 Network.” Nature Computational Science. Springer Nature, 2021. https://doi.org/10.1038/s43588-021-00157-1. ieee: J. Guzmán, A. Schlögl, C. Espinoza Martinez, X. Zhang, B. Suter, and P. M. Jonas, “How connectivity rules and synaptic properties shape the efficacy of pattern separation in the entorhinal cortex–dentate gyrus–CA3 network,” Nature Computational Science, vol. 1, no. 12. Springer Nature, pp. 830–842, 2021. ista: Guzmán J, Schlögl A, Espinoza Martinez C, Zhang X, Suter B, Jonas PM. 2021. How connectivity rules and synaptic properties shape the efficacy of pattern separation in the entorhinal cortex–dentate gyrus–CA3 network. Nature Computational Science. 1(12), 830–842. mla: Guzmán, José, et al. “How Connectivity Rules and Synaptic Properties Shape the Efficacy of Pattern Separation in the Entorhinal Cortex–Dentate Gyrus–CA3 Network.” Nature Computational Science, vol. 1, no. 12, Springer Nature, 2021, pp. 830–42, doi:10.1038/s43588-021-00157-1. short: J. Guzmán, A. Schlögl, C. Espinoza Martinez, X. Zhang, B. Suter, P.M. Jonas, Nature Computational Science 1 (2021) 830–842. date_created: 2022-03-04T08:32:36Z date_published: 2021-12-16T00:00:00Z date_updated: 2023-08-10T22:30:10Z day: '16' ddc: - '610' department: - _id: PeJo doi: 10.1038/s43588-021-00157-1 ec_funded: 1 file: - access_level: open_access checksum: 9fec5b667909ef52be96d502e4f8c2ae content_type: application/pdf creator: patrickd date_created: 2022-06-02T12:51:07Z date_updated: 2022-06-18T22:30:03Z embargo: 2022-06-17 file_id: '11430' file_name: Guzmanetal2021.pdf file_size: 1699466 relation: main_file - access_level: open_access checksum: 52a005b13a114e3c3a28fa6bbe8b1a8d content_type: application/pdf creator: patrickd date_created: 2022-06-02T12:53:47Z date_updated: 2022-06-18T22:30:03Z embargo: 2022-06-17 file_id: '11431' file_name: Guzmanetal2021Suppl.pdf file_size: 3005651 relation: supplementary_material title: Supplementary Material file_date_updated: 2022-06-18T22:30:03Z has_accepted_license: '1' intvolume: ' 1' issue: '12' keyword: - general medicine language: - iso: eng main_file_link: - open_access: '1' url: https://www.biorxiv.org/content/10.1101/647800 month: '12' oa: 1 oa_version: Submitted Version page: 830-842 project: - _id: 25B7EB9E-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '692692' name: Biophysics and circuit function of a giant cortical glumatergic synapse - _id: 25C5A090-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: Z00312 name: The Wittgenstein Prize publication: Nature Computational Science publication_identifier: issn: - 2662-8457 publication_status: published publisher: Springer Nature quality_controlled: '1' related_material: link: - relation: press_release url: https://ista.ac.at/en/news/spot-the-difference/ record: - id: '10110' relation: software status: public scopus_import: '1' status: public title: How connectivity rules and synaptic properties shape the efficacy of pattern separation in the entorhinal cortex–dentate gyrus–CA3 network type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 1 year: '2021' ...