--- _id: '6363' abstract: - lang: eng text: "Distinguishing between similar experiences is achieved by the brain \ in a process called pattern separation. In the hippocampus, pattern \ separation reduces the interference of memories and increases the storage capacity by decorrelating similar inputs patterns of neuronal activity into \ non-overlapping output firing patterns. Winners-take-all (WTA) mechanism \ is a theoretical model for pattern separation in which a \"winner\" \ cell suppresses the activity of the neighboring neurons through feedback inhibition. However, if the network properties of the dentate gyrus support WTA as a biologically conceivable model remains unknown. Here, we showed that the connectivity rules of PV+interneurons and their synaptic properties are optimizedfor efficient pattern separation. We found using multiple whole-cell in vitrorecordings that PV+interneurons mainly connect to granule cells (GC) through lateral inhibition, a form of feedback inhibition in which a GC inhibits other GCs but not \ itself through the activation of PV+interneurons. Thus, lateral inhibition between GC–PV+interneurons was ~10 times more abundant than recurrent connections. Furthermore, the GC–PV+interneuron connectivity was more spatially confined \ but less abundant than PV+interneurons–GC connectivity, leading to an \ asymmetrical distribution of excitatory and inhibitory connectivity. Our network model of the dentate gyrus with incorporated real connectivity rules efficiently decorrelates neuronal activity patterns using WTA as the primary mechanism. \ This process relied on lateral inhibition, fast-signaling properties of \ PV+interneurons and the asymmetrical distribution of excitatory and inhibitory connectivity. Finally, we found that silencing the activity of PV+interneurons in vivoleads to acute deficits in discrimination between similar environments, suggesting that PV+interneuron networks are necessary for behavioral relevant computations. Our results demonstrate that PV+interneurons possess unique connectivity and fast signaling properties that confer to the dentate \ gyrus network properties that allow the emergence of pattern separation. Thus, our results contribute to the knowledge of how specific forms of network organization underlie sophisticated types of information processing. \r\n" alternative_title: - ISTA Thesis article_processing_charge: No author: - first_name: 'Claudia ' full_name: 'Espinoza Martinez, Claudia ' id: 31FFEE2E-F248-11E8-B48F-1D18A9856A87 last_name: Espinoza Martinez orcid: 0000-0003-4710-2082 citation: ama: Espinoza Martinez C. Parvalbumin+ interneurons enable efficient pattern separation in hippocampal microcircuits. 2019. doi:10.15479/AT:ISTA:6363 apa: Espinoza Martinez, C. (2019). Parvalbumin+ interneurons enable efficient pattern separation in hippocampal microcircuits. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:6363 chicago: Espinoza Martinez, Claudia . “Parvalbumin+ Interneurons Enable Efficient Pattern Separation in Hippocampal Microcircuits.” Institute of Science and Technology Austria, 2019. https://doi.org/10.15479/AT:ISTA:6363. ieee: C. Espinoza Martinez, “Parvalbumin+ interneurons enable efficient pattern separation in hippocampal microcircuits,” Institute of Science and Technology Austria, 2019. ista: Espinoza Martinez C. 2019. Parvalbumin+ interneurons enable efficient pattern separation in hippocampal microcircuits. Institute of Science and Technology Austria. mla: Espinoza Martinez, Claudia. Parvalbumin+ Interneurons Enable Efficient Pattern Separation in Hippocampal Microcircuits. Institute of Science and Technology Austria, 2019, doi:10.15479/AT:ISTA:6363. short: C. Espinoza Martinez, Parvalbumin+ Interneurons Enable Efficient Pattern Separation in Hippocampal Microcircuits, Institute of Science and Technology Austria, 2019. date_created: 2019-04-30T11:56:10Z date_published: 2019-04-30T00:00:00Z date_updated: 2023-09-15T12:03:48Z day: '30' ddc: - '570' degree_awarded: PhD department: - _id: PeJo doi: 10.15479/AT:ISTA:6363 file: - access_level: open_access checksum: 77c6c05cfe8b58c8abcf1b854375d084 content_type: application/pdf creator: cespinoza date_created: 2019-05-07T16:00:39Z date_updated: 2021-02-11T11:17:15Z embargo: 2020-05-09 file_id: '6389' file_name: Espinozathesis_all2.pdf file_size: 13966891 relation: main_file - access_level: closed checksum: f6aa819f127691a2b0fc21c76eb09746 content_type: application/vnd.openxmlformats-officedocument.wordprocessingml.document creator: cespinoza date_created: 2019-05-07T16:00:48Z date_updated: 2020-07-14T12:47:28Z embargo_to: open_access file_id: '6390' file_name: Espinoza_Thesis.docx file_size: 11159900 relation: source_file file_date_updated: 2021-02-11T11:17:15Z has_accepted_license: '1' language: - iso: eng month: '04' oa: 1 oa_version: Published Version page: '140' publication_identifier: isbn: - 978-3-99078-000-8 issn: - 2663-337X publication_status: published publisher: Institute of Science and Technology Austria related_material: record: - id: '21' relation: part_of_dissertation status: public status: public supervisor: - first_name: Peter M full_name: Jonas, Peter M id: 353C1B58-F248-11E8-B48F-1D18A9856A87 last_name: Jonas orcid: 0000-0001-5001-4804 title: Parvalbumin+ interneurons enable efficient pattern separation in hippocampal microcircuits type: dissertation user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 year: '2019' ...