--- _id: '9329' abstract: - lang: eng text: "Background: To understand information coding in single neurons, it is necessary to analyze subthreshold synaptic events, action potentials (APs), and their interrelation in different behavioral states. However, detecting excitatory postsynaptic potentials (EPSPs) or currents (EPSCs) in behaving animals remains challenging, because of unfavorable signal-to-noise ratio, high frequency, fluctuating amplitude, and variable time course of synaptic events.\r\nNew method: We developed a method for synaptic event detection, termed MOD (Machine-learning Optimal-filtering Detection-procedure), which combines concepts of supervised machine learning and optimal Wiener filtering. Experts were asked to manually score short epochs of data. The algorithm was trained to obtain the optimal filter coefficients of a Wiener filter and the optimal detection threshold. Scored and unscored data were then processed with the optimal filter, and events were detected as peaks above threshold.\r\nResults: We challenged MOD with EPSP traces in vivo in mice during spatial navigation and EPSC traces in vitro in slices under conditions of enhanced transmitter release. The area under the curve (AUC) of the receiver operating characteristics (ROC) curve was, on average, 0.894 for in vivo and 0.969 for in vitro data sets, indicating high detection accuracy and efficiency.\r\nComparison with existing methods: When benchmarked using a (1 − AUC)−1 metric, MOD outperformed previous methods (template-fit, deconvolution, and Bayesian methods) by an average factor of 3.13 for in vivo data sets, but showed comparable (template-fit, deconvolution) or higher (Bayesian) computational efficacy.\r\nConclusions: MOD may become an important new tool for large-scale, real-time analysis of synaptic activity." acknowledged_ssus: - _id: SSU acknowledgement: This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement number 692692 to P.J.) and the Fond zur Förderung der Wissenschaftlichen Forschung (Z 312-B27, Wittgenstein award to P.J.). We thank Drs. Jozsef Csicsvari, Christoph Lampert, and Federico Stella for critically reading previous manuscript versions. We are also grateful to Drs. Josh Merel and Ben Shababo for their help with applying the Bayesian detection method to our data. We also thank Florian Marr for technical assistance, Eleftheria Kralli-Beller for manuscript editing, and the Scientific Service Units of IST Austria for efficient support. article_number: '109125' article_processing_charge: Yes (via OA deal) article_type: original author: - first_name: Xiaomin full_name: Zhang, Xiaomin id: 423EC9C2-F248-11E8-B48F-1D18A9856A87 last_name: Zhang - first_name: Alois full_name: Schlögl, Alois id: 45BF87EE-F248-11E8-B48F-1D18A9856A87 last_name: Schlögl orcid: 0000-0002-5621-8100 - first_name: David H full_name: Vandael, David H id: 3AE48E0A-F248-11E8-B48F-1D18A9856A87 last_name: Vandael orcid: 0000-0001-7577-1676 - 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: 'Zhang X, Schlögl A, Vandael DH, Jonas PM. MOD: A novel machine-learning optimal-filtering method for accurate and efficient detection of subthreshold synaptic events in vivo. Journal of Neuroscience Methods. 2021;357(6). doi:10.1016/j.jneumeth.2021.109125' apa: 'Zhang, X., Schlögl, A., Vandael, D. H., & Jonas, P. M. (2021). MOD: A novel machine-learning optimal-filtering method for accurate and efficient detection of subthreshold synaptic events in vivo. Journal of Neuroscience Methods. Elsevier. https://doi.org/10.1016/j.jneumeth.2021.109125' chicago: 'Zhang, Xiaomin, Alois Schlögl, David H Vandael, and Peter M Jonas. “MOD: A Novel Machine-Learning Optimal-Filtering Method for Accurate and Efficient Detection of Subthreshold Synaptic Events in Vivo.” Journal of Neuroscience Methods. Elsevier, 2021. https://doi.org/10.1016/j.jneumeth.2021.109125.' ieee: 'X. Zhang, A. Schlögl, D. H. Vandael, and P. M. Jonas, “MOD: A novel machine-learning optimal-filtering method for accurate and efficient detection of subthreshold synaptic events in vivo,” Journal of Neuroscience Methods, vol. 357, no. 6. Elsevier, 2021.' ista: 'Zhang X, Schlögl A, Vandael DH, Jonas PM. 2021. MOD: A novel machine-learning optimal-filtering method for accurate and efficient detection of subthreshold synaptic events in vivo. Journal of Neuroscience Methods. 357(6), 109125.' mla: 'Zhang, Xiaomin, et al. “MOD: A Novel Machine-Learning Optimal-Filtering Method for Accurate and Efficient Detection of Subthreshold Synaptic Events in Vivo.” Journal of Neuroscience Methods, vol. 357, no. 6, 109125, Elsevier, 2021, doi:10.1016/j.jneumeth.2021.109125.' short: X. Zhang, A. Schlögl, D.H. Vandael, P.M. Jonas, Journal of Neuroscience Methods 357 (2021). date_created: 2021-04-18T22:01:39Z date_published: 2021-03-09T00:00:00Z date_updated: 2023-08-07T14:36:14Z day: '09' ddc: - '570' department: - _id: PeJo - _id: ScienComp doi: 10.1016/j.jneumeth.2021.109125 ec_funded: 1 external_id: isi: - '000661088500005' file: - access_level: open_access checksum: 2a5800d91b96d08b525e17319dcd5e44 content_type: application/pdf creator: dernst date_created: 2021-04-19T08:30:22Z date_updated: 2021-04-19T08:30:22Z file_id: '9339' file_name: 2021_JourNeuroscienceMeth_Zhang.pdf file_size: 6924738 relation: main_file success: 1 file_date_updated: 2021-04-19T08:30:22Z has_accepted_license: '1' intvolume: ' 357' isi: 1 issue: '6' language: - iso: eng license: https://creativecommons.org/licenses/by-nc-nd/4.0/ month: '03' oa: 1 oa_version: Published Version 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: Journal of Neuroscience Methods publication_identifier: eissn: - 1872-678X issn: - 0165-0270 publication_status: published publisher: Elsevier quality_controlled: '1' scopus_import: '1' status: public title: 'MOD: A novel machine-learning optimal-filtering method for accurate and efficient detection of subthreshold synaptic events in vivo' tmp: image: /images/cc_by_nc_nd.png legal_code_url: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode name: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) short: CC BY-NC-ND (4.0) type: journal_article user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 357 year: '2021' ... --- _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' ... --- _id: '10110' 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. 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. 2021. doi:10.15479/AT:ISTA:10110 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. IST Austria. https://doi.org/10.15479/AT:ISTA:10110 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.” IST Austria, 2021. https://doi.org/10.15479/AT:ISTA:10110. 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.” IST Austria, 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, IST Austria, 10.15479/AT:ISTA:10110. 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. IST Austria, 2021, doi:10.15479/AT:ISTA:10110. short: J. Guzmán, A. Schlögl, C. Espinoza Martinez, X. Zhang, B. Suter, P.M. Jonas, (2021). date_created: 2021-10-08T06:44:22Z date_published: 2021-12-16T00:00:00Z date_updated: 2024-03-27T23:30:11Z day: '16' ddc: - '005' department: - _id: PeJo - _id: ScienComp doi: 10.15479/AT:ISTA:10110 file: - access_level: open_access checksum: f92f8931cad0aa7e411c1715337bf408 content_type: application/x-zip-compressed creator: cchlebak date_created: 2021-10-08T08:46:04Z date_updated: 2021-10-08T08:46:04Z file_id: '10114' file_name: patternseparation-main (1).zip file_size: 332990101 relation: main_file success: 1 file_date_updated: 2021-10-08T08:46:04Z has_accepted_license: '1' license: https://opensource.org/licenses/GPL-3.0 month: '12' oa: 1 publisher: IST Austria related_material: link: - description: News on IST Webpage relation: press_release url: https://ist.ac.at/en/news/spot-the-difference/ record: - id: '10816' relation: used_for_analysis_in status: public status: public title: How connectivity rules and synaptic properties shape the efficacy of pattern separation in the entorhinal cortex–dentate gyrus–CA3 network tmp: legal_code_url: https://www.gnu.org/licenses/gpl-3.0.en.html name: GNU General Public License 3.0 short: GPL 3.0 type: software user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9 year: '2021' ... --- _id: '8001' abstract: - lang: eng text: Post-tetanic potentiation (PTP) is an attractive candidate mechanism for hippocampus-dependent short-term memory. Although PTP has a uniquely large magnitude at hippocampal mossy fiber-CA3 pyramidal neuron synapses, it is unclear whether it can be induced by natural activity and whether its lifetime is sufficient to support short-term memory. We combined in vivo recordings from granule cells (GCs), in vitro paired recordings from mossy fiber terminals and postsynaptic CA3 neurons, and “flash and freeze” electron microscopy. PTP was induced at single synapses and showed a low induction threshold adapted to sparse GC activity in vivo. PTP was mainly generated by enlargement of the readily releasable pool of synaptic vesicles, allowing multiplicative interaction with other plasticity forms. PTP was associated with an increase in the docked vesicle pool, suggesting formation of structural “pool engrams.” Absence of presynaptic activity extended the lifetime of the potentiation, enabling prolonged information storage in the hippocampal network. acknowledged_ssus: - _id: SSU acknowledgement: This project received funding from the European Research Council (ERC) under the European Union Horizon 2020 Research and Innovation Program (grant agreement 692692 to P.J.) and the Fond zur Förderung der Wissenschaftlichen Forschung ( Z 312-B27 , Wittgenstein award to P.J. and V 739-B27 to C.B.-M.). We thank Drs. Jozsef Csicsvari, Jose Guzman, Erwin Neher, and Ryuichi Shigemoto for commenting on earlier versions of the manuscript. We are grateful to Walter Kaufmann, Daniel Gütl, and Vanessa Zheden for EM training; Alois Schlögl for programming; Florian Marr for excellent technical assistance and cell reconstruction; Christina Altmutter for technical help; Eleftheria Kralli-Beller for manuscript editing; Taija Makinen for providing the Prox1-CreERT2 mouse line; and the Scientific Service Units of IST Austria for support. article_processing_charge: No article_type: original author: - first_name: David H full_name: Vandael, David H id: 3AE48E0A-F248-11E8-B48F-1D18A9856A87 last_name: Vandael orcid: 0000-0001-7577-1676 - first_name: Carolina full_name: Borges Merjane, Carolina id: 4305C450-F248-11E8-B48F-1D18A9856A87 last_name: Borges Merjane orcid: 0000-0003-0005-401X - first_name: Xiaomin full_name: Zhang, Xiaomin id: 423EC9C2-F248-11E8-B48F-1D18A9856A87 last_name: Zhang - 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: Vandael DH, Borges Merjane C, Zhang X, Jonas PM. Short-term plasticity at hippocampal mossy fiber synapses is induced by natural activity patterns and associated with vesicle pool engram formation. Neuron. 2020;107(3):509-521. doi:10.1016/j.neuron.2020.05.013 apa: Vandael, D. H., Borges Merjane, C., Zhang, X., & Jonas, P. M. (2020). Short-term plasticity at hippocampal mossy fiber synapses is induced by natural activity patterns and associated with vesicle pool engram formation. Neuron. Elsevier. https://doi.org/10.1016/j.neuron.2020.05.013 chicago: Vandael, David H, Carolina Borges Merjane, Xiaomin Zhang, and Peter M Jonas. “Short-Term Plasticity at Hippocampal Mossy Fiber Synapses Is Induced by Natural Activity Patterns and Associated with Vesicle Pool Engram Formation.” Neuron. Elsevier, 2020. https://doi.org/10.1016/j.neuron.2020.05.013. ieee: D. H. Vandael, C. Borges Merjane, X. Zhang, and P. M. Jonas, “Short-term plasticity at hippocampal mossy fiber synapses is induced by natural activity patterns and associated with vesicle pool engram formation,” Neuron, vol. 107, no. 3. Elsevier, pp. 509–521, 2020. ista: Vandael DH, Borges Merjane C, Zhang X, Jonas PM. 2020. Short-term plasticity at hippocampal mossy fiber synapses is induced by natural activity patterns and associated with vesicle pool engram formation. Neuron. 107(3), 509–521. mla: Vandael, David H., et al. “Short-Term Plasticity at Hippocampal Mossy Fiber Synapses Is Induced by Natural Activity Patterns and Associated with Vesicle Pool Engram Formation.” Neuron, vol. 107, no. 3, Elsevier, 2020, pp. 509–21, doi:10.1016/j.neuron.2020.05.013. short: D.H. Vandael, C. Borges Merjane, X. Zhang, P.M. Jonas, Neuron 107 (2020) 509–521. date_created: 2020-06-22T13:29:05Z date_published: 2020-08-05T00:00:00Z date_updated: 2023-08-22T07:45:25Z day: '05' ddc: - '570' department: - _id: PeJo doi: 10.1016/j.neuron.2020.05.013 ec_funded: 1 external_id: isi: - '000556135600004' pmid: - '32492366' file: - access_level: open_access checksum: 4030b2be0c9625d54694a1e9fb00305e content_type: application/pdf creator: dernst date_created: 2020-11-25T11:23:02Z date_updated: 2020-11-25T11:23:02Z file_id: '8811' file_name: 2020_Neuron_Vandael.pdf file_size: 4390833 relation: main_file success: 1 file_date_updated: 2020-11-25T11:23:02Z has_accepted_license: '1' intvolume: ' 107' isi: 1 issue: '3' language: - iso: eng month: '08' oa: 1 oa_version: Published Version page: 509-521 pmid: 1 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 - _id: 2696E7FE-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: V00739 name: Structural plasticity at mossy fiber-CA3 synapses publication: Neuron publication_identifier: eissn: - '10974199' issn: - 0896-6273 publication_status: published publisher: Elsevier quality_controlled: '1' related_material: link: - description: News on IST Homepage relation: press_release url: https://ist.ac.at/en/news/possible-physical-trace-of-short-term-memory-found/ scopus_import: '1' status: public title: Short-term plasticity at hippocampal mossy fiber synapses is induced by natural activity patterns and associated with vesicle pool engram formation tmp: image: /images/cc_by_nc_nd.png legal_code_url: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode name: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) short: CC BY-NC-ND (4.0) type: journal_article user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 107 year: '2020' ... --- _id: '8261' abstract: - lang: eng text: Dentate gyrus granule cells (GCs) connect the entorhinal cortex to the hippocampal CA3 region, but how they process spatial information remains enigmatic. To examine the role of GCs in spatial coding, we measured excitatory postsynaptic potentials (EPSPs) and action potentials (APs) in head-fixed mice running on a linear belt. Intracellular recording from morphologically identified GCs revealed that most cells were active, but activity level varied over a wide range. Whereas only ∼5% of GCs showed spatially tuned spiking, ∼50% received spatially tuned input. Thus, the GC population broadly encodes spatial information, but only a subset relays this information to the CA3 network. Fourier analysis indicated that GCs received conjunctive place-grid-like synaptic input, suggesting code conversion in single neurons. GC firing was correlated with dendritic complexity and intrinsic excitability, but not extrinsic excitatory input or dendritic cable properties. Thus, functional maturation may control input-output transformation and spatial code conversion. acknowledged_ssus: - _id: M-Shop - _id: ScienComp - _id: PreCl acknowledgement: This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (grant agreement 692692, P.J.) and the Fond zur Förderung der Wissenschaftlichen Forschung (Z 312-B27, Wittgenstein award, P.J.). We thank Gyorgy Buzsáki, Jozsef Csicsvari, Juan Ramirez Villegas, and Federico Stella for commenting on earlier versions of this manuscript. We also thank Katie Bittner, Michael Brecht, Albert Lee, Jeffery Magee, and Alejandro Pernía-Andrade for sharing expertise in in vivo patch-clamp recording. We are grateful to Florian Marr for cell labeling, cell reconstruction, and technical assistance; Ben Suter for helpful discussions; Christina Altmutter for technical support; Eleftheria Kralli-Beller for manuscript editing; and Todor Asenov (Machine Shop) for device construction. We also thank the Scientific Service Units (SSUs) of IST Austria (Machine Shop, Scientific Computing, and Preclinical Facility) for efficient support. article_processing_charge: No article_type: original author: - first_name: Xiaomin full_name: Zhang, Xiaomin id: 423EC9C2-F248-11E8-B48F-1D18A9856A87 last_name: Zhang - first_name: Alois full_name: Schlögl, Alois id: 45BF87EE-F248-11E8-B48F-1D18A9856A87 last_name: Schlögl orcid: 0000-0002-5621-8100 - 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: Zhang X, Schlögl A, Jonas PM. Selective routing of spatial information flow from input to output in hippocampal granule cells. Neuron. 2020;107(6):1212-1225. doi:10.1016/j.neuron.2020.07.006 apa: Zhang, X., Schlögl, A., & Jonas, P. M. (2020). Selective routing of spatial information flow from input to output in hippocampal granule cells. Neuron. Elsevier. https://doi.org/10.1016/j.neuron.2020.07.006 chicago: Zhang, Xiaomin, Alois Schlögl, and Peter M Jonas. “Selective Routing of Spatial Information Flow from Input to Output in Hippocampal Granule Cells.” Neuron. Elsevier, 2020. https://doi.org/10.1016/j.neuron.2020.07.006. ieee: X. Zhang, A. Schlögl, and P. M. Jonas, “Selective routing of spatial information flow from input to output in hippocampal granule cells,” Neuron, vol. 107, no. 6. Elsevier, pp. 1212–1225, 2020. ista: Zhang X, Schlögl A, Jonas PM. 2020. Selective routing of spatial information flow from input to output in hippocampal granule cells. Neuron. 107(6), 1212–1225. mla: Zhang, Xiaomin, et al. “Selective Routing of Spatial Information Flow from Input to Output in Hippocampal Granule Cells.” Neuron, vol. 107, no. 6, Elsevier, 2020, pp. 1212–25, doi:10.1016/j.neuron.2020.07.006. short: X. Zhang, A. Schlögl, P.M. Jonas, Neuron 107 (2020) 1212–1225. date_created: 2020-08-14T09:36:05Z date_published: 2020-09-23T00:00:00Z date_updated: 2023-08-22T08:30:55Z day: '23' ddc: - '570' department: - _id: PeJo - _id: ScienComp doi: 10.1016/j.neuron.2020.07.006 ec_funded: 1 external_id: isi: - '000579698700009' pmid: - '32763145' file: - access_level: open_access checksum: 44a5960fc083a4cb3488d22224859fdc content_type: application/pdf creator: dernst date_created: 2020-12-04T09:29:21Z date_updated: 2020-12-04T09:29:21Z file_id: '8920' file_name: 2020_Neuron_Zhang.pdf file_size: 3011120 relation: main_file success: 1 file_date_updated: 2020-12-04T09:29:21Z has_accepted_license: '1' intvolume: ' 107' isi: 1 issue: '6' language: - iso: eng month: '09' oa: 1 oa_version: Published Version page: 1212-1225 pmid: 1 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: Neuron publication_identifier: issn: - 0896-6273 publication_status: published publisher: Elsevier quality_controlled: '1' related_material: link: - description: News on IST Website relation: press_release url: https://ist.ac.at/en/news/the-bouncer-in-the-brain/ status: public title: Selective routing of spatial information flow from input to output in hippocampal granule cells tmp: image: /images/cc_by_nc_nd.png legal_code_url: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode name: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) short: CC BY-NC-ND (4.0) type: journal_article user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 107 year: '2020' ... --- _id: '21' abstract: - lang: eng text: Parvalbumin-positive (PV+) GABAergic interneurons in hippocampal microcircuits are thought to play a key role in several higher network functions, such as feedforward and feedback inhibition, network oscillations, and pattern separation. Fast lateral inhibition mediated by GABAergic interneurons may implement a winner-takes-all mechanism in the hippocampal input layer. However, it is not clear whether the functional connectivity rules of granule cells (GCs) and interneurons in the dentate gyrus are consistent with such a mechanism. Using simultaneous patch-clamp recordings from up to seven GCs and up to four PV+ interneurons in the dentate gyrus, we find that connectivity is structured in space, synapse-specific, and enriched in specific disynaptic motifs. In contrast to the neocortex, lateral inhibition in the dentate gyrus (in which a GC inhibits neighboring GCs via a PV+ interneuron) is ~ 10-times more abundant than recurrent inhibition (in which a GC inhibits itself). Thus, unique connectivity rules may enable the dentate gyrus to perform specific higher-order computations acknowledgement: 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) and the Fond zur Förderung der Wissenschaftlichen Forschung (Z 312-B27, Wittgenstein award), both to P.J.. article_number: '4605' article_processing_charge: No article_type: original author: - 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: José full_name: Guzmán, José id: 30CC5506-F248-11E8-B48F-1D18A9856A87 last_name: Guzmán orcid: 0000-0003-2209-5242 - first_name: Xiaomin full_name: Zhang, Xiaomin id: 423EC9C2-F248-11E8-B48F-1D18A9856A87 last_name: Zhang - 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: Espinoza Martinez C, Guzmán J, Zhang X, Jonas PM. Parvalbumin+ interneurons obey unique connectivity rules and establish a powerful lateral-inhibition microcircuit in dentate gyrus. Nature Communications. 2018;9(1). doi:10.1038/s41467-018-06899-3 apa: Espinoza Martinez, C., Guzmán, J., Zhang, X., & Jonas, P. M. (2018). Parvalbumin+ interneurons obey unique connectivity rules and establish a powerful lateral-inhibition microcircuit in dentate gyrus. Nature Communications. Nature Publishing Group. https://doi.org/10.1038/s41467-018-06899-3 chicago: Espinoza Martinez, Claudia , José Guzmán, Xiaomin Zhang, and Peter M Jonas. “Parvalbumin+ Interneurons Obey Unique Connectivity Rules and Establish a Powerful Lateral-Inhibition Microcircuit in Dentate Gyrus.” Nature Communications. Nature Publishing Group, 2018. https://doi.org/10.1038/s41467-018-06899-3. ieee: C. Espinoza Martinez, J. Guzmán, X. Zhang, and P. M. Jonas, “Parvalbumin+ interneurons obey unique connectivity rules and establish a powerful lateral-inhibition microcircuit in dentate gyrus,” Nature Communications, vol. 9, no. 1. Nature Publishing Group, 2018. ista: Espinoza Martinez C, Guzmán J, Zhang X, Jonas PM. 2018. Parvalbumin+ interneurons obey unique connectivity rules and establish a powerful lateral-inhibition microcircuit in dentate gyrus. Nature Communications. 9(1), 4605. mla: Espinoza Martinez, Claudia, et al. “Parvalbumin+ Interneurons Obey Unique Connectivity Rules and Establish a Powerful Lateral-Inhibition Microcircuit in Dentate Gyrus.” Nature Communications, vol. 9, no. 1, 4605, Nature Publishing Group, 2018, doi:10.1038/s41467-018-06899-3. short: C. Espinoza Martinez, J. Guzmán, X. Zhang, P.M. Jonas, Nature Communications 9 (2018). date_created: 2018-12-11T11:44:12Z date_published: 2018-11-02T00:00:00Z date_updated: 2024-03-27T23:30:31Z day: '02' ddc: - '570' department: - _id: PeJo doi: 10.1038/s41467-018-06899-3 ec_funded: 1 external_id: isi: - '000449069700009' file: - access_level: open_access checksum: 9fe2a63bd95a5067d896c087d07998f3 content_type: application/pdf creator: dernst date_created: 2018-12-17T15:41:57Z date_updated: 2020-07-14T12:45:28Z file_id: '5715' file_name: 2018_NatureComm_Espinoza.pdf file_size: 4651930 relation: main_file file_date_updated: 2020-07-14T12:45:28Z has_accepted_license: '1' intvolume: ' 9' isi: 1 issue: '1' language: - iso: eng license: https://creativecommons.org/licenses/by/4.0/ month: '11' oa: 1 oa_version: Published Version 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 Communications publication_status: published publisher: Nature Publishing Group publist_id: '8034' quality_controlled: '1' related_material: link: - description: News on IST Homepage relation: press_release url: https://ist.ac.at/en/news/lateral-inhibition-keeps-similar-memories-apart/ record: - id: '6363' relation: dissertation_contains status: public scopus_import: '1' status: public title: Parvalbumin+ interneurons obey unique connectivity rules and establish a powerful lateral-inhibition microcircuit in dentate gyrus tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 9 year: '2018' ...