--- _id: '9438' abstract: - lang: eng text: Rigorous investigation of synaptic transmission requires analysis of unitary synaptic events by simultaneous recording from presynaptic terminals and postsynaptic target neurons. However, this has been achieved at only a limited number of model synapses, including the squid giant synapse and the mammalian calyx of Held. Cortical presynaptic terminals have been largely inaccessible to direct presynaptic recording, due to their small size. Here, we describe a protocol for improved subcellular patch-clamp recording in rat and mouse brain slices, with the synapse in a largely intact environment. Slice preparation takes ~2 h, recording ~3 h and post hoc morphological analysis 2 d. Single presynaptic hippocampal mossy fiber terminals are stimulated minimally invasively in the bouton-attached configuration, in which the cytoplasmic content remains unperturbed, or in the whole-bouton configuration, in which the cytoplasmic composition can be precisely controlled. Paired pre–postsynaptic recordings can be integrated with biocytin labeling and morphological analysis, allowing correlative investigation of synapse structure and function. Paired recordings can be obtained from mossy fiber terminals in slices from both rats and mice, implying applicability to genetically modified synapses. Paired recordings can also be performed together with axon tract stimulation or optogenetic activation, allowing comparison of unitary and compound synaptic events in the same target cell. Finally, paired recordings can be combined with spontaneous event analysis, permitting collection of miniature events generated at a single identified synapse. In conclusion, the subcellular patch-clamp techniques detailed here should facilitate analysis of biophysics, plasticity and circuit function of cortical synapses in the mammalian central nervous system. acknowledged_ssus: - _id: M-Shop 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 to P.J.) and the Fond zur Förderung der Wissenschaftlichen Forschung (Z 312-B27, Wittgenstein award to P.J., V 739-B27 to C.B.M.). We are grateful to F. Marr and C. Altmutter for excellent technical assistance and cell reconstruction, E. Kralli-Beller for manuscript editing, and the Scientific Service Units of IST Austria, especially T. Asenov and Miba machine shop, for maximally efficient 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: Yuji full_name: Okamoto, Yuji id: 3337E116-F248-11E8-B48F-1D18A9856A87 last_name: Okamoto orcid: 0000-0003-0408-6094 - 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: Victor M full_name: Vargas Barroso, Victor M id: 2F55A9DE-F248-11E8-B48F-1D18A9856A87 last_name: Vargas Barroso - 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: Vandael DH, Okamoto Y, Borges Merjane C, Vargas Barroso VM, Suter B, Jonas PM. Subcellular patch-clamp techniques for single-bouton stimulation and simultaneous pre- and postsynaptic recording at cortical synapses. Nature Protocols. 2021;16(6):2947–2967. doi:10.1038/s41596-021-00526-0 apa: Vandael, D. H., Okamoto, Y., Borges Merjane, C., Vargas Barroso, V. M., Suter, B., & Jonas, P. M. (2021). Subcellular patch-clamp techniques for single-bouton stimulation and simultaneous pre- and postsynaptic recording at cortical synapses. Nature Protocols. Springer Nature. https://doi.org/10.1038/s41596-021-00526-0 chicago: Vandael, David H, Yuji Okamoto, Carolina Borges Merjane, Victor M Vargas Barroso, Benjamin Suter, and Peter M Jonas. “Subcellular Patch-Clamp Techniques for Single-Bouton Stimulation and Simultaneous Pre- and Postsynaptic Recording at Cortical Synapses.” Nature Protocols. Springer Nature, 2021. https://doi.org/10.1038/s41596-021-00526-0. ieee: D. H. Vandael, Y. Okamoto, C. Borges Merjane, V. M. Vargas Barroso, B. Suter, and P. M. Jonas, “Subcellular patch-clamp techniques for single-bouton stimulation and simultaneous pre- and postsynaptic recording at cortical synapses,” Nature Protocols, vol. 16, no. 6. Springer Nature, pp. 2947–2967, 2021. ista: Vandael DH, Okamoto Y, Borges Merjane C, Vargas Barroso VM, Suter B, Jonas PM. 2021. Subcellular patch-clamp techniques for single-bouton stimulation and simultaneous pre- and postsynaptic recording at cortical synapses. Nature Protocols. 16(6), 2947–2967. mla: Vandael, David H., et al. “Subcellular Patch-Clamp Techniques for Single-Bouton Stimulation and Simultaneous Pre- and Postsynaptic Recording at Cortical Synapses.” Nature Protocols, vol. 16, no. 6, Springer Nature, 2021, pp. 2947–2967, doi:10.1038/s41596-021-00526-0. short: D.H. Vandael, Y. Okamoto, C. Borges Merjane, V.M. Vargas Barroso, B. Suter, P.M. Jonas, Nature Protocols 16 (2021) 2947–2967. date_created: 2021-05-30T22:01:24Z date_published: 2021-06-01T00:00:00Z date_updated: 2023-08-10T22:30:51Z day: '01' ddc: - '570' department: - _id: PeJo doi: 10.1038/s41596-021-00526-0 ec_funded: 1 external_id: isi: - '000650528700003' pmid: - '33990799' file: - access_level: open_access checksum: 7eb580abd8893cdb0b410cf41bc8c263 content_type: application/pdf creator: cziletti date_created: 2021-07-08T12:27:55Z date_updated: 2021-12-02T23:30:05Z embargo: 2021-12-01 file_id: '9639' file_name: VandaeletalAuthorVersion2021.pdf file_size: 38574802 relation: main_file file_date_updated: 2021-12-02T23:30:05Z has_accepted_license: '1' intvolume: ' 16' isi: 1 issue: '6' language: - iso: eng month: '06' oa: 1 oa_version: Submitted Version page: 2947–2967 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: Nature Protocols publication_identifier: eissn: - '17502799' issn: - '17542189' publication_status: published publisher: Springer Nature quality_controlled: '1' scopus_import: '1' status: public title: Subcellular patch-clamp techniques for single-bouton stimulation and simultaneous pre- and postsynaptic recording at cortical synapses type: journal_article user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 16 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: '7405' abstract: - lang: eng text: Biophysical modeling of neuronal networks helps to integrate and interpret rapidly growing and disparate experimental datasets at multiple scales. The NetPyNE tool (www.netpyne.org) provides both programmatic and graphical interfaces to develop data-driven multiscale network models in NEURON. NetPyNE clearly separates model parameters from implementation code. Users provide specifications at a high level via a standardized declarative language, for example connectivity rules, to create millions of cell-to-cell connections. NetPyNE then enables users to generate the NEURON network, run efficiently parallelized simulations, optimize and explore network parameters through automated batch runs, and use built-in functions for visualization and analysis – connectivity matrices, voltage traces, spike raster plots, local field potentials, and information theoretic measures. NetPyNE also facilitates model sharing by exporting and importing standardized formats (NeuroML and SONATA). NetPyNE is already being used to teach computational neuroscience students and by modelers to investigate brain regions and phenomena. article_number: e44494 article_processing_charge: No article_type: original author: - first_name: Salvador full_name: Dura-Bernal, Salvador last_name: Dura-Bernal - first_name: Benjamin full_name: Suter, Benjamin id: 4952F31E-F248-11E8-B48F-1D18A9856A87 last_name: Suter orcid: 0000-0002-9885-6936 - first_name: Padraig full_name: Gleeson, Padraig last_name: Gleeson - first_name: Matteo full_name: Cantarelli, Matteo last_name: Cantarelli - first_name: Adrian full_name: Quintana, Adrian last_name: Quintana - first_name: Facundo full_name: Rodriguez, Facundo last_name: Rodriguez - first_name: David J full_name: Kedziora, David J last_name: Kedziora - first_name: George L full_name: Chadderdon, George L last_name: Chadderdon - first_name: Cliff C full_name: Kerr, Cliff C last_name: Kerr - first_name: Samuel A full_name: Neymotin, Samuel A last_name: Neymotin - first_name: Robert A full_name: McDougal, Robert A last_name: McDougal - first_name: Michael full_name: Hines, Michael last_name: Hines - first_name: Gordon MG full_name: Shepherd, Gordon MG last_name: Shepherd - first_name: William W full_name: Lytton, William W last_name: Lytton citation: ama: Dura-Bernal S, Suter B, Gleeson P, et al. NetPyNE, a tool for data-driven multiscale modeling of brain circuits. eLife. 2019;8. doi:10.7554/elife.44494 apa: Dura-Bernal, S., Suter, B., Gleeson, P., Cantarelli, M., Quintana, A., Rodriguez, F., … Lytton, W. W. (2019). NetPyNE, a tool for data-driven multiscale modeling of brain circuits. ELife. eLife Sciences Publications. https://doi.org/10.7554/elife.44494 chicago: Dura-Bernal, Salvador, Benjamin Suter, Padraig Gleeson, Matteo Cantarelli, Adrian Quintana, Facundo Rodriguez, David J Kedziora, et al. “NetPyNE, a Tool for Data-Driven Multiscale Modeling of Brain Circuits.” ELife. eLife Sciences Publications, 2019. https://doi.org/10.7554/elife.44494. ieee: S. Dura-Bernal et al., “NetPyNE, a tool for data-driven multiscale modeling of brain circuits,” eLife, vol. 8. eLife Sciences Publications, 2019. ista: Dura-Bernal S, Suter B, Gleeson P, Cantarelli M, Quintana A, Rodriguez F, Kedziora DJ, Chadderdon GL, Kerr CC, Neymotin SA, McDougal RA, Hines M, Shepherd GM, Lytton WW. 2019. NetPyNE, a tool for data-driven multiscale modeling of brain circuits. eLife. 8, e44494. mla: Dura-Bernal, Salvador, et al. “NetPyNE, a Tool for Data-Driven Multiscale Modeling of Brain Circuits.” ELife, vol. 8, e44494, eLife Sciences Publications, 2019, doi:10.7554/elife.44494. short: S. Dura-Bernal, B. Suter, P. Gleeson, M. Cantarelli, A. Quintana, F. Rodriguez, D.J. Kedziora, G.L. Chadderdon, C.C. Kerr, S.A. Neymotin, R.A. McDougal, M. Hines, G.M. Shepherd, W.W. Lytton, ELife 8 (2019). date_created: 2020-01-30T09:08:01Z date_published: 2019-05-31T00:00:00Z date_updated: 2023-09-07T14:27:52Z day: '31' ddc: - '570' department: - _id: PeJo doi: 10.7554/elife.44494 external_id: isi: - '000468968400001' pmid: - '31025934' file: - access_level: open_access checksum: 7014189c11c10a12feeeae37f054871d content_type: application/pdf creator: dernst date_created: 2020-02-04T08:41:47Z date_updated: 2020-07-14T12:47:57Z file_id: '7444' file_name: 2019_eLife_DuraBernal.pdf file_size: 6182359 relation: main_file file_date_updated: 2020-07-14T12:47:57Z has_accepted_license: '1' intvolume: ' 8' isi: 1 language: - iso: eng month: '05' oa: 1 oa_version: Published Version pmid: 1 publication: eLife publication_identifier: issn: - 2050-084X publication_status: published publisher: eLife Sciences Publications quality_controlled: '1' scopus_import: '1' status: public title: NetPyNE, a tool for data-driven multiscale modeling of brain circuits 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: 8 year: '2019' ...