[{"status":"public","type":"journal_article","author":[{"id":"0eed2d40-3d48-11ec-8d38-f789cc2e40b2","last_name":"Feitosa Tomé","full_name":"Feitosa Tomé, Douglas","first_name":"Douglas"},{"last_name":"Zhang","full_name":"Zhang, Ying","first_name":"Ying"},{"last_name":"Aida","full_name":"Aida, Tomomi","first_name":"Tomomi"},{"full_name":"Mosto, Olivia","first_name":"Olivia","last_name":"Mosto"},{"first_name":"Yifeng","full_name":"Lu, Yifeng","last_name":"Lu"},{"last_name":"Chen","first_name":"Mandy","full_name":"Chen, Mandy"},{"full_name":"Sadeh, Sadra","first_name":"Sadra","last_name":"Sadeh"},{"full_name":"Roy, Dheeraj S.","first_name":"Dheeraj S.","last_name":"Roy"},{"last_name":"Clopath","full_name":"Clopath, Claudia","first_name":"Claudia"}],"month":"01","publication_identifier":{"issn":["1097-6256"],"eissn":["1546-1726"]},"main_file_link":[{"open_access":"1","url":"https://doi.org/10.1038/s41593-023-01551-w"}],"oa_version":"Published Version","day":"19","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","language":[{"iso":"eng"}],"publication":"Nature Neuroscience","oa":1,"date_updated":"2024-01-29T09:22:00Z","article_processing_charge":"Yes (in subscription journal)","title":"Dynamic and selective engrams emerge with memory consolidation","isi":1,"scopus_import":"1","publisher":"Springer Nature","date_published":"2024-01-19T00:00:00Z","department":[{"_id":"TiVo"}],"quality_controlled":"1","publication_status":"epub_ahead","external_id":{"isi":["001145442300001"]},"abstract":[{"text":"Episodic memories are encoded by experience-activated neuronal ensembles that remain necessary and sufficient for recall. However, the temporal evolution of memory engrams after initial encoding is unclear. In this study, we employed computational and experimental approaches to examine how the neural composition and selectivity of engrams change with memory consolidation. Our spiking neural network model yielded testable predictions: memories transition from unselective to selective as neurons drop out of and drop into engrams; inhibitory activity during recall is essential for memory selectivity; and inhibitory synaptic plasticity during memory consolidation is critical for engrams to become selective. Using activity-dependent labeling, longitudinal calcium imaging and a combination of optogenetic and chemogenetic manipulations in mouse dentate gyrus, we conducted contextual fear conditioning experiments that supported our model’s predictions. Our results reveal that memory engrams are dynamic and that changes in engram composition mediated by inhibitory plasticity are crucial for the emergence of memory selectivity.","lang":"eng"}],"article_type":"original","_id":"14887","doi":"10.1038/s41593-023-01551-w","acknowledgement":"We thank S. Erisken from Inscopix for helping us establish in vivo one-photon calcium imaging for this work. We thank K. Su at Tsinghua University for assistance with this work. This work was funded by the President’s PhD Scholarship from Imperial College London (D.F.T.), the Wellcome Trust (225412/Z/22/Z) (S.S.), the Biotechnology and Biological Sciences Research Council (BB/N013956/1 and BB/N019008/1) (C.C.), the Wellcome Trust (200790/Z/16/Z) (C.C.), the Simons Foundation (564408) (C.C.) and the Engineering and Physical Sciences Research Council (EP/R035806/1) (CC). The School of Life Sciences and the IDG/McGovern Institute for Brain Research supported Y.Z. The Warren Alpert Distinguished Scholar Award and National Institutes of Health 1K99NS125131-01 supported D.S.R.","year":"2024","date_created":"2024-01-28T23:01:43Z","citation":{"short":"D. Feitosa Tomé, Y. Zhang, T. Aida, O. Mosto, Y. Lu, M. Chen, S. Sadeh, D.S. Roy, C. Clopath, Nature Neuroscience (2024).","ieee":"D. Feitosa Tomé <i>et al.</i>, “Dynamic and selective engrams emerge with memory consolidation,” <i>Nature Neuroscience</i>. Springer Nature, 2024.","ama":"Feitosa Tomé D, Zhang Y, Aida T, et al. Dynamic and selective engrams emerge with memory consolidation. <i>Nature Neuroscience</i>. 2024. doi:<a href=\"https://doi.org/10.1038/s41593-023-01551-w\">10.1038/s41593-023-01551-w</a>","mla":"Feitosa Tomé, Douglas, et al. “Dynamic and Selective Engrams Emerge with Memory Consolidation.” <i>Nature Neuroscience</i>, Springer Nature, 2024, doi:<a href=\"https://doi.org/10.1038/s41593-023-01551-w\">10.1038/s41593-023-01551-w</a>.","chicago":"Feitosa Tomé, Douglas, Ying Zhang, Tomomi Aida, Olivia Mosto, Yifeng Lu, Mandy Chen, Sadra Sadeh, Dheeraj S. Roy, and Claudia Clopath. “Dynamic and Selective Engrams Emerge with Memory Consolidation.” <i>Nature Neuroscience</i>. Springer Nature, 2024. <a href=\"https://doi.org/10.1038/s41593-023-01551-w\">https://doi.org/10.1038/s41593-023-01551-w</a>.","ista":"Feitosa Tomé D, Zhang Y, Aida T, Mosto O, Lu Y, Chen M, Sadeh S, Roy DS, Clopath C. 2024. Dynamic and selective engrams emerge with memory consolidation. Nature Neuroscience.","apa":"Feitosa Tomé, D., Zhang, Y., Aida, T., Mosto, O., Lu, Y., Chen, M., … Clopath, C. (2024). Dynamic and selective engrams emerge with memory consolidation. <i>Nature Neuroscience</i>. Springer Nature. <a href=\"https://doi.org/10.1038/s41593-023-01551-w\">https://doi.org/10.1038/s41593-023-01551-w</a>"},"related_material":{"record":[{"status":"public","relation":"research_data","id":"14892"}]}},{"language":[{"iso":"eng"}],"publication":"Nature Neuroscience","date_updated":"2023-10-04T11:41:05Z","oa":1,"article_processing_charge":"Yes (in subscription journal)","title":"Panoramic visual statistics shape retina-wide organization of receptive fields","isi":1,"intvolume":"        26","has_accepted_license":"1","scopus_import":"1","pmid":1,"status":"public","type":"journal_article","author":[{"first_name":"Divyansh","full_name":"Gupta, Divyansh","orcid":"0000-0001-7400-6665","id":"2A485EBE-F248-11E8-B48F-1D18A9856A87","last_name":"Gupta"},{"last_name":"Mlynarski","id":"358A453A-F248-11E8-B48F-1D18A9856A87","full_name":"Mlynarski, Wiktor F","first_name":"Wiktor F"},{"orcid":"0000-0002-4792-1881","last_name":"Sumser","id":"3320A096-F248-11E8-B48F-1D18A9856A87","full_name":"Sumser, Anton L","first_name":"Anton L"},{"orcid":"0000-0003-2012-9947","last_name":"Symonova","id":"3C0C7BC6-F248-11E8-B48F-1D18A9856A87","full_name":"Symonova, Olga","first_name":"Olga"},{"full_name":"Svaton, Jan","first_name":"Jan","last_name":"Svaton","id":"f7f724c3-9d6f-11ed-9f44-e5c5f3a5bee2","orcid":"0000-0002-6198-2939"},{"id":"2BD278E6-F248-11E8-B48F-1D18A9856A87","last_name":"Jösch","orcid":"0000-0002-3937-1330","full_name":"Jösch, Maximilian A","first_name":"Maximilian A"}],"month":"04","publication_identifier":{"issn":["1097-6256"],"eissn":["1546-1726"]},"day":"01","oa_version":"Published Version","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","file":[{"checksum":"a33d91e398e548f34003170e10988368","file_id":"14395","file_name":"2023_NatureNeuroscience_Gupta.pdf","success":1,"date_updated":"2023-10-04T11:40:51Z","date_created":"2023-10-04T11:40:51Z","creator":"dernst","access_level":"open_access","content_type":"application/pdf","file_size":6144866,"relation":"main_file"}],"file_date_updated":"2023-10-04T11:40:51Z","article_type":"original","_id":"12349","acknowledged_ssus":[{"_id":"ScienComp"},{"_id":"PreCl"},{"_id":"LifeSc"},{"_id":"Bio"}],"doi":"10.1038/s41593-023-01280-0","acknowledgement":"We thank Hiroki Asari for sharing the dataset of naturalistic images, Anton Sumser for sharing visual stimulus code, Yoav Ben Simon for initial explorative work with the generation of AAVs, and Tomas Vega-Zuñiga for help with immunostainings. We also thank Gasper Tkacik and members of the Neuroethology group for their comments on the manuscript. This research was supported by the Scientific Service Units of IST Austria through resources provided by Scientific Computing, the Preclinical Facility, the Lab Support Facility, and the Imaging and Optics Facility. This work was supported by European Union Horizon 2020 Marie Skłodowska-Curie grant 665385 (DG), Austrian Science Fund (FWF) stand-alone grant P 34015 (WM), Human Frontiers Science Program LT000256/2018-L (AS), EMBO ALTF 1098-2017 (AS) and the European Research Council Starting Grant 756502 (MJ).","year":"2023","date_created":"2023-01-23T14:14:19Z","citation":{"chicago":"Gupta, Divyansh, Wiktor F Mlynarski, Anton L Sumser, Olga Symonova, Jan Svaton, and Maximilian A Jösch. “Panoramic Visual Statistics Shape Retina-Wide Organization of Receptive Fields.” <i>Nature Neuroscience</i>. Springer Nature, 2023. <a href=\"https://doi.org/10.1038/s41593-023-01280-0\">https://doi.org/10.1038/s41593-023-01280-0</a>.","mla":"Gupta, Divyansh, et al. “Panoramic Visual Statistics Shape Retina-Wide Organization of Receptive Fields.” <i>Nature Neuroscience</i>, vol. 26, Springer Nature, 2023, pp. 606–14, doi:<a href=\"https://doi.org/10.1038/s41593-023-01280-0\">10.1038/s41593-023-01280-0</a>.","ista":"Gupta D, Mlynarski WF, Sumser AL, Symonova O, Svaton J, Jösch MA. 2023. Panoramic visual statistics shape retina-wide organization of receptive fields. Nature Neuroscience. 26, 606–614.","short":"D. Gupta, W.F. Mlynarski, A.L. Sumser, O. Symonova, J. Svaton, M.A. Jösch, Nature Neuroscience 26 (2023) 606–614.","ama":"Gupta D, Mlynarski WF, Sumser AL, Symonova O, Svaton J, Jösch MA. Panoramic visual statistics shape retina-wide organization of receptive fields. <i>Nature Neuroscience</i>. 2023;26:606-614. doi:<a href=\"https://doi.org/10.1038/s41593-023-01280-0\">10.1038/s41593-023-01280-0</a>","ieee":"D. Gupta, W. F. Mlynarski, A. L. Sumser, O. Symonova, J. Svaton, and M. A. Jösch, “Panoramic visual statistics shape retina-wide organization of receptive fields,” <i>Nature Neuroscience</i>, vol. 26. Springer Nature, pp. 606–614, 2023.","apa":"Gupta, D., Mlynarski, W. F., Sumser, A. L., Symonova, O., Svaton, J., &#38; Jösch, M. A. (2023). Panoramic visual statistics shape retina-wide organization of receptive fields. <i>Nature Neuroscience</i>. Springer Nature. <a href=\"https://doi.org/10.1038/s41593-023-01280-0\">https://doi.org/10.1038/s41593-023-01280-0</a>"},"ec_funded":1,"related_material":{"record":[{"status":"public","relation":"research_data","id":"12370"}]},"project":[{"name":"International IST Doctoral Program","call_identifier":"H2020","_id":"2564DBCA-B435-11E9-9278-68D0E5697425","grant_number":"665385"},{"_id":"626c45b5-2b32-11ec-9570-e509828c1ba6","grant_number":"P34015","name":"Efficient coding with biophysical realism"},{"grant_number":"756502","_id":"2634E9D2-B435-11E9-9278-68D0E5697425","call_identifier":"H2020","name":"Circuits of Visual Attention"},{"_id":"266D407A-B435-11E9-9278-68D0E5697425","grant_number":"LT000256","name":"Neuronal networks of salience and spatial detection in the murine superior colliculus"},{"_id":"264FEA02-B435-11E9-9278-68D0E5697425","grant_number":"ALTF 1098-2017","name":"Connecting sensory with motor processing in the superior colliculus"}],"publisher":"Springer Nature","date_published":"2023-04-01T00:00:00Z","license":"https://creativecommons.org/licenses/by/4.0/","page":"606-614","department":[{"_id":"GradSch"},{"_id":"MaJö"}],"quality_controlled":"1","volume":26,"publication_status":"published","ddc":["570"],"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)","image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"external_id":{"isi":["000955258300002"],"pmid":["36959418"]},"abstract":[{"text":"Statistics of natural scenes are not uniform - their structure varies dramatically from ground to sky. It remains unknown whether these non-uniformities are reflected in the large-scale organization of the early visual system and what benefits such adaptations would confer. Here, by relying on the efficient coding hypothesis, we predict that changes in the structure of receptive fields across visual space increase the efficiency of sensory coding. We show experimentally that, in agreement with our predictions, receptive fields of retinal ganglion cells change their shape along the dorsoventral retinal axis, with a marked surround asymmetry at the visual horizon. Our work demonstrates that, according to principles of efficient coding, the panoramic structure of natural scenes is exploited by the retina across space and cell-types.","lang":"eng"}]},{"pmid":1,"type":"journal_article","status":"public","author":[{"full_name":"Colombo, Gloria","first_name":"Gloria","orcid":"0000-0001-9434-8902","last_name":"Colombo","id":"3483CF6C-F248-11E8-B48F-1D18A9856A87"},{"orcid":"0000-0003-0002-1867","id":"850B2E12-9CD4-11E9-837F-E719E6697425","last_name":"Cubero","first_name":"Ryan J","full_name":"Cubero, Ryan J"},{"last_name":"Kanari","first_name":"Lida","full_name":"Kanari, Lida"},{"orcid":"0000-0003-2356-9403","id":"41CB84B2-F248-11E8-B48F-1D18A9856A87","last_name":"Venturino","first_name":"Alessandro","full_name":"Venturino, Alessandro"},{"first_name":"Rouven","full_name":"Schulz, Rouven","last_name":"Schulz","id":"4C5E7B96-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-5297-733X"},{"last_name":"Scolamiero","first_name":"Martina","full_name":"Scolamiero, Martina"},{"last_name":"Agerberg","first_name":"Jens","full_name":"Agerberg, Jens"},{"full_name":"Mathys, Hansruedi","first_name":"Hansruedi","last_name":"Mathys"},{"last_name":"Tsai","full_name":"Tsai, Li-Huei","first_name":"Li-Huei"},{"first_name":"Wojciech","full_name":"Chachólski, Wojciech","last_name":"Chachólski"},{"first_name":"Kathryn","full_name":"Hess, Kathryn","last_name":"Hess"},{"orcid":"0000-0001-8635-0877","id":"36ACD32E-F248-11E8-B48F-1D18A9856A87","last_name":"Siegert","full_name":"Siegert, Sandra","first_name":"Sandra"}],"oa_version":"Published Version","day":"01","user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","file":[{"relation":"main_file","access_level":"open_access","content_type":"application/pdf","file_size":23789835,"creator":"dernst","date_created":"2023-01-30T08:06:56Z","date_updated":"2023-01-30T08:06:56Z","success":1,"checksum":"28431146873096f52e0107b534f178c9","file_id":"12437","file_name":"2022_NatureNeuroscience_Colombo.pdf"}],"month":"10","publication_identifier":{"issn":["1097-6256"],"eissn":["1546-1726"]},"language":[{"iso":"eng"}],"publication":"Nature Neuroscience","title":"A tool for mapping microglial morphology, morphOMICs, reveals brain-region and sex-dependent phenotypes","oa":1,"date_updated":"2024-03-25T23:30:10Z","article_processing_charge":"No","issue":"10","intvolume":"        25","has_accepted_license":"1","scopus_import":"1","isi":1,"project":[{"grant_number":"754411","_id":"260C2330-B435-11E9-9278-68D0E5697425","name":"ISTplus - Postdoctoral Fellowships","call_identifier":"H2020"},{"grant_number":"715571","_id":"25D4A630-B435-11E9-9278-68D0E5697425","name":"Microglia action towards neuronal circuit formation and function in health and disease","call_identifier":"H2020"}],"department":[{"_id":"SaSi"}],"page":"1379-1393","volume":25,"quality_controlled":"1","publisher":"Springer Nature","date_published":"2022-10-01T00:00:00Z","publication_status":"published","external_id":{"pmid":["36180790"],"isi":["000862214700001"]},"abstract":[{"lang":"eng","text":"Environmental cues influence the highly dynamic morphology of microglia. Strategies to characterize these changes usually involve user-selected morphometric features, which preclude the identification of a spectrum of context-dependent morphological phenotypes. Here we develop MorphOMICs, a topological data analysis approach, which enables semiautomatic mapping of microglial morphology into an atlas of cue-dependent phenotypes and overcomes feature-selection biases and biological variability. We extract spatially heterogeneous and sexually dimorphic morphological phenotypes for seven adult mouse brain regions. This sex-specific phenotype declines with maturation but increases over the disease trajectories in two neurodegeneration mouse models, with females showing a faster morphological shift in affected brain regions. Remarkably, microglia morphologies reflect an adaptation upon repeated exposure to ketamine anesthesia and do not recover to control morphologies. Finally, we demonstrate that both long primary processes and short terminal processes provide distinct insights to morphological phenotypes. MorphOMICs opens a new perspective to characterize microglial morphology."}],"ddc":["570"],"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)","image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"acknowledged_ssus":[{"_id":"PreCl"},{"_id":"Bio"},{"_id":"ScienComp"}],"file_date_updated":"2023-01-30T08:06:56Z","article_type":"original","_id":"12244","doi":"10.1038/s41593-022-01167-6","citation":{"mla":"Colombo, Gloria, et al. “A Tool for Mapping Microglial Morphology, MorphOMICs, Reveals Brain-Region and Sex-Dependent Phenotypes.” <i>Nature Neuroscience</i>, vol. 25, no. 10, Springer Nature, 2022, pp. 1379–93, doi:<a href=\"https://doi.org/10.1038/s41593-022-01167-6\">10.1038/s41593-022-01167-6</a>.","chicago":"Colombo, Gloria, Ryan J Cubero, Lida Kanari, Alessandro Venturino, Rouven Schulz, Martina Scolamiero, Jens Agerberg, et al. “A Tool for Mapping Microglial Morphology, MorphOMICs, Reveals Brain-Region and Sex-Dependent Phenotypes.” <i>Nature Neuroscience</i>. Springer Nature, 2022. <a href=\"https://doi.org/10.1038/s41593-022-01167-6\">https://doi.org/10.1038/s41593-022-01167-6</a>.","ista":"Colombo G, Cubero RJ, Kanari L, Venturino A, Schulz R, Scolamiero M, Agerberg J, Mathys H, Tsai L-H, Chachólski W, Hess K, Siegert S. 2022. A tool for mapping microglial morphology, morphOMICs, reveals brain-region and sex-dependent phenotypes. Nature Neuroscience. 25(10), 1379–1393.","ieee":"G. Colombo <i>et al.</i>, “A tool for mapping microglial morphology, morphOMICs, reveals brain-region and sex-dependent phenotypes,” <i>Nature Neuroscience</i>, vol. 25, no. 10. Springer Nature, pp. 1379–1393, 2022.","ama":"Colombo G, Cubero RJ, Kanari L, et al. A tool for mapping microglial morphology, morphOMICs, reveals brain-region and sex-dependent phenotypes. <i>Nature Neuroscience</i>. 2022;25(10):1379-1393. doi:<a href=\"https://doi.org/10.1038/s41593-022-01167-6\">10.1038/s41593-022-01167-6</a>","short":"G. Colombo, R.J. Cubero, L. Kanari, A. Venturino, R. Schulz, M. Scolamiero, J. Agerberg, H. Mathys, L.-H. Tsai, W. Chachólski, K. Hess, S. Siegert, Nature Neuroscience 25 (2022) 1379–1393.","apa":"Colombo, G., Cubero, R. J., Kanari, L., Venturino, A., Schulz, R., Scolamiero, M., … Siegert, S. (2022). A tool for mapping microglial morphology, morphOMICs, reveals brain-region and sex-dependent phenotypes. <i>Nature Neuroscience</i>. Springer Nature. <a href=\"https://doi.org/10.1038/s41593-022-01167-6\">https://doi.org/10.1038/s41593-022-01167-6</a>"},"date_created":"2023-01-16T09:53:07Z","keyword":["General Neuroscience"],"acknowledgement":"We thank the scientific service units at ISTA, in particular M. Schunn’s team at the preclinical facility, and especially our colony manager S. Haslinger, for excellent support. We are also grateful to the ISTA Imaging & Optics Facility, and in particular C. Sommer for helping with the data file conversions. We thank R. Erhart from the ISTA Scientific Computing Unit for improving the script performance. We thank M. Maes, B. Nagy, S. Oakeley and M. Benevento and all members of the Siegert group for constant feedback on the project and on the manuscript. This research was supported by the European Union Horizon 2020 research and innovation program under the Marie Skłodowska-Curie Actions program (754411 to R.J.A.C.), and by the European Research Council (grant no. 715571 to S.S.). L.K. was supported by funding to the Blue Brain Project, a research center of the École polytechnique fédérale de Lausanne, from the Swiss government’s ETH Board of the Swiss Federal Institutes of Technology. L.-H.T. was supported by NIH (grant no. R37NS051874) and by the JPB Foundation. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.","year":"2022","ec_funded":1,"related_material":{"record":[{"status":"public","id":"12378","relation":"dissertation_contains"}],"link":[{"description":"News on ISTA website","url":"https://ista.ac.at/en/news/morphomics-revealing-the-hidden-meaning-of-microglia-shape/","relation":"press_release"}]}},{"oa":1,"date_updated":"2023-08-04T10:49:44Z","article_processing_charge":"Yes","title":"Identification of neural oscillations and epileptiform changes in human brain organoids","isi":1,"intvolume":"        24","language":[{"iso":"eng"}],"author":[{"last_name":"Samarasinghe","first_name":"Ranmal A.","full_name":"Samarasinghe, Ranmal A."},{"orcid":"0000-0001-6618-6889","id":"862A3C56-A8BF-11E9-B4FA-D9E3E5697425","last_name":"Miranda","first_name":"Osvaldo","full_name":"Miranda, Osvaldo"},{"full_name":"Buth, Jessie E.","first_name":"Jessie E.","last_name":"Buth"},{"first_name":"Simon","full_name":"Mitchell, Simon","last_name":"Mitchell"},{"first_name":"Isabella","full_name":"Ferando, Isabella","last_name":"Ferando"},{"full_name":"Watanabe, Momoko","first_name":"Momoko","last_name":"Watanabe"},{"last_name":"Kurdian","full_name":"Kurdian, Arinnae","first_name":"Arinnae"},{"last_name":"Golshani","first_name":"Peyman","full_name":"Golshani, Peyman"},{"full_name":"Plath, Kathrin","first_name":"Kathrin","last_name":"Plath"},{"full_name":"Lowry, William E.","first_name":"William E.","last_name":"Lowry"},{"last_name":"Parent","full_name":"Parent, Jack M.","first_name":"Jack M."},{"last_name":"Mody","full_name":"Mody, Istvan","first_name":"Istvan"},{"last_name":"Novitch","full_name":"Novitch, Bennett G.","first_name":"Bennett G."}],"month":"08","publication_identifier":{"eissn":["1546-1726"],"issn":["1097-6256"]},"oa_version":"Published Version","main_file_link":[{"open_access":"1","url":"https://doi.org/10.1038/s41593-021-00906-5"}],"day":"23","user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","pmid":1,"alternative_title":["Nature Neuroscience"],"type":"technical_report","status":"public","acknowledgement":"We thank S. Butler, T. Carmichael and members of the laboratory of B.G.N. for helpful discussions and comments on the manuscript; N. Vishlaghi and F. Turcios-Hernandez for technical assistance, and J. Lee, S.-K. Lee, H. Shinagawa and K. Yoshikawa for valuable reagents. We also thank the UCLA Eli and Edythe Broad Stem Cell Research Center (BSCRC) and Intellectual and Developmental Disabilities Research Center microscopy cores for access to imaging facilities. This work was supported by grants from the California Institute for Regenerative Medicine (CIRM) (DISC1-08819 to B.G.N.), the National Institute of Health (R01NS089817, R01DA051897 and P50HD103557 to B.G.N.; K08NS119747 to R.A.S.; K99HD096105 to M.W.; R01MH123922, R01MH121521 and P50HD103557 to M.J.G.; R01GM099134 to K.P.; R01NS103788 to W.E.L.; R01NS088571 to J.M.P.; R01NS030549 and R01AG050474 to I.M.), and research awards from the UCLA Jonsson Comprehensive Cancer Center and BSCRC Ablon Scholars Program (to B.G.N.), the BSCRC Innovation Program (to B.G.N., K.P. and W.E.L.), the UCLA BSCRC Steffy Brain Aging Research Fund (to B.G.N. and W.E.L.) and the UCLA Clinical and Translational Science Institute (to B.G.N.), Paul Allen Family Foundation Frontiers Group (to K.P. and W.E.L.), the March of Dimes Foundation (to W.E.L.) and the Simons Foundation Autism Research Initiative Bridge to Independence Program (to R.A.S. and M.J.G.). R.A.S. was also supported by the UCLA/NINDS Translational Neuroscience Training Grant (R25NS065723), a Research and Training Fellowship from the American Epilepsy Society, a Taking Flight Award from CURE Epilepsy and a Clinician Scientist training award from the UCLA BSCRC. J.E.B. was supported by the UCLA BSCRC Rose Hills Foundation Graduate Scholarship Training Program. M.W. was supported by postdoctoral training awards provided by the UCLA BSCRC and the Uehara Memorial Foundation. O.A.M. and A.K. were supported in part by the UCLA-California State University Northridge CIRM-Bridges training program (EDUC2-08411). We also acknowledge the support of the IDDRC Cells, Circuits and Systems Analysis, Microscopy and Genetics and Genomics Cores of the Semel Institute of Neuroscience at UCLA, which are supported by the NICHD (U54HD087101 and P50HD10355701). We lastly acknowledge support from a Quantitative and Computational Biosciences Collaboratory Postdoctoral Fellowship to S.M. and the Quantitative and Computational Biosciences Collaboratory community, directed by M. Pellegrini.","year":"2021","date_created":"2019-11-10T11:23:58Z","citation":{"chicago":"Samarasinghe, Ranmal A., Osvaldo Miranda, Jessie E. Buth, Simon Mitchell, Isabella Ferando, Momoko Watanabe, Arinnae Kurdian, et al. <i>Identification of Neural Oscillations and Epileptiform Changes in Human Brain Organoids</i>. Vol. 24. Springer Nature, 2021. <a href=\"https://doi.org/10.1038/s41593-021-00906-5\">https://doi.org/10.1038/s41593-021-00906-5</a>.","ista":"Samarasinghe RA, Miranda O, Buth JE, Mitchell S, Ferando I, Watanabe M, Kurdian A, Golshani P, Plath K, Lowry WE, Parent JM, Mody I, Novitch BG. 2021. Identification of neural oscillations and epileptiform changes in human brain organoids, Springer Nature, 32p.","mla":"Samarasinghe, Ranmal A., et al. <i>Identification of Neural Oscillations and Epileptiform Changes in Human Brain Organoids</i>. Vol. 24, Springer Nature, 2021, doi:<a href=\"https://doi.org/10.1038/s41593-021-00906-5\">10.1038/s41593-021-00906-5</a>.","ama":"Samarasinghe RA, Miranda O, Buth JE, et al. <i>Identification of Neural Oscillations and Epileptiform Changes in Human Brain Organoids</i>. Vol 24. Springer Nature; 2021. doi:<a href=\"https://doi.org/10.1038/s41593-021-00906-5\">10.1038/s41593-021-00906-5</a>","ieee":"R. A. Samarasinghe <i>et al.</i>, <i>Identification of neural oscillations and epileptiform changes in human brain organoids</i>, vol. 24. Springer Nature, 2021.","short":"R.A. Samarasinghe, O. Miranda, J.E. Buth, S. Mitchell, I. Ferando, M. Watanabe, A. Kurdian, P. Golshani, K. Plath, W.E. Lowry, J.M. Parent, I. Mody, B.G. Novitch, Identification of Neural Oscillations and Epileptiform Changes in Human Brain Organoids, Springer Nature, 2021.","apa":"Samarasinghe, R. A., Miranda, O., Buth, J. E., Mitchell, S., Ferando, I., Watanabe, M., … Novitch, B. G. (2021). <i>Identification of neural oscillations and epileptiform changes in human brain organoids</i> (Vol. 24). Springer Nature. <a href=\"https://doi.org/10.1038/s41593-021-00906-5\">https://doi.org/10.1038/s41593-021-00906-5</a>"},"_id":"6995","doi":"10.1038/s41593-021-00906-5","publication_status":"published","external_id":{"pmid":["34426698 "],"isi":["000687516300001"]},"abstract":[{"text":"Human brain organoids represent a powerful tool for the study of human neurological diseases particularly those that impact brain growth and structure. However, many neurological diseases lack obvious anatomical abnormalities, yet significantly impact neural network functions, raising the question of whether organoids possess sufficient neural network architecture and complexity to model these conditions. Here, we explore the network level functions of brain organoids using calcium sensor imaging and extracellular recording approaches that together reveal the existence of complex oscillatory network behaviors reminiscent of intact brain preparations. We further demonstrate strikingly abnormal epileptiform network activity in organoids derived from a Rett Syndrome patient despite only modest anatomical differences from isogenically matched controls, and rescue with an unconventional neuromodulatory drug Pifithrin-α. Together, these findings provide an essential foundation for the utilization of human brain organoids to study intact and disordered human brain network formation and illustrate their utility in therapeutic discovery.","lang":"eng"}],"publisher":"Springer Nature","date_published":"2021-08-23T00:00:00Z","department":[{"_id":"GradSch"},{"_id":"SiHi"}],"page":"32","volume":24},{"_id":"9439","article_type":"original","doi":"10.1038/s41593-021-00846-0","date_created":"2021-05-30T22:01:24Z","citation":{"apa":"Mlynarski, W. F., &#38; Hermundstad, A. M. (2021). Efficient and adaptive sensory codes. <i>Nature Neuroscience</i>. Springer Nature. <a href=\"https://doi.org/10.1038/s41593-021-00846-0\">https://doi.org/10.1038/s41593-021-00846-0</a>","mla":"Mlynarski, Wiktor F., and Ann M. Hermundstad. “Efficient and Adaptive Sensory Codes.” <i>Nature Neuroscience</i>, vol. 24, Springer Nature, 2021, pp. 998–1009, doi:<a href=\"https://doi.org/10.1038/s41593-021-00846-0\">10.1038/s41593-021-00846-0</a>.","ista":"Mlynarski WF, Hermundstad AM. 2021. Efficient and adaptive sensory codes. Nature Neuroscience. 24, 998–1009.","chicago":"Mlynarski, Wiktor F, and Ann M. Hermundstad. “Efficient and Adaptive Sensory Codes.” <i>Nature Neuroscience</i>. Springer Nature, 2021. <a href=\"https://doi.org/10.1038/s41593-021-00846-0\">https://doi.org/10.1038/s41593-021-00846-0</a>.","short":"W.F. Mlynarski, A.M. Hermundstad, Nature Neuroscience 24 (2021) 998–1009.","ieee":"W. F. Mlynarski and A. M. Hermundstad, “Efficient and adaptive sensory codes,” <i>Nature Neuroscience</i>, vol. 24. Springer Nature, pp. 998–1009, 2021.","ama":"Mlynarski WF, Hermundstad AM. Efficient and adaptive sensory codes. <i>Nature Neuroscience</i>. 2021;24:998-1009. doi:<a href=\"https://doi.org/10.1038/s41593-021-00846-0\">10.1038/s41593-021-00846-0</a>"},"year":"2021","acknowledgement":"We thank D. Kastner and T. Münch for generously providing figures from their work. We also thank V. Jayaraman, M. Noorman, T. Ma, and K. Krishnamurthy for useful discussions and feedback on the manuscript. W.F.M. was funded by the European Union’s Horizon 2020 Research and Innovation Programme under Marie Skłodowska-Curie Grant Agreement No. 754411. A.M.H. was supported by the Howard Hughes Medical Institute.","ec_funded":1,"project":[{"call_identifier":"H2020","name":"ISTplus - Postdoctoral Fellowships","_id":"260C2330-B435-11E9-9278-68D0E5697425","grant_number":"754411"}],"quality_controlled":"1","volume":24,"page":"998-1009","department":[{"_id":"GaTk"}],"date_published":"2021-05-20T00:00:00Z","publisher":"Springer Nature","publication_status":"published","abstract":[{"lang":"eng","text":"The ability to adapt to changes in stimulus statistics is a hallmark of sensory systems. Here, we developed a theoretical framework that can account for the dynamics of adaptation from an information processing perspective. We use this framework to optimize and analyze adaptive sensory codes, and we show that codes optimized for stationary environments can suffer from prolonged periods of poor performance when the environment changes. To mitigate the adversarial effects of these environmental changes, sensory systems must navigate tradeoffs between the ability to accurately encode incoming stimuli and the ability to rapidly detect and adapt to changes in the distribution of these stimuli. We derive families of codes that balance these objectives, and we demonstrate their close match to experimentally observed neural dynamics during mean and variance adaptation. Our results provide a unifying perspective on adaptation across a range of sensory systems, environments, and sensory tasks."}],"external_id":{"isi":["000652577300003"]},"language":[{"iso":"eng"}],"publication":"Nature Neuroscience","title":"Efficient and adaptive sensory codes","article_processing_charge":"No","date_updated":"2023-08-08T13:51:14Z","oa":1,"intvolume":"        24","scopus_import":"1","isi":1,"status":"public","type":"journal_article","author":[{"first_name":"Wiktor F","full_name":"Mlynarski, Wiktor F","id":"358A453A-F248-11E8-B48F-1D18A9856A87","last_name":"Mlynarski"},{"full_name":"Hermundstad, Ann M.","first_name":"Ann M.","last_name":"Hermundstad"}],"user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","day":"20","oa_version":"Preprint","main_file_link":[{"open_access":"1","url":"https://doi.org/10.1101/669200 "}],"month":"05","publication_identifier":{"eissn":["1546-1726"],"issn":["1097-6256"]}},{"author":[{"last_name":"Stroud","full_name":"Stroud, Jake P.","first_name":"Jake P."},{"last_name":"Porter","full_name":"Porter, Mason A.","first_name":"Mason A."},{"full_name":"Hennequin, Guillaume","first_name":"Guillaume","last_name":"Hennequin"},{"first_name":"Tim P","full_name":"Vogels, Tim P","id":"CB6FF8D2-008F-11EA-8E08-2637E6697425","last_name":"Vogels","orcid":"0000-0003-3295-6181"}],"publication_identifier":{"issn":["1097-6256","1546-1726"]},"month":"12","day":"01","oa_version":"Submitted Version","main_file_link":[{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6276991/","open_access":"1"}],"user_id":"D865714E-FA4E-11E9-B85B-F5C5E5697425","pmid":1,"type":"journal_article","status":"public","date_updated":"2021-01-12T08:16:46Z","oa":1,"article_processing_charge":"No","issue":"12","title":"Motor primitives in space and time via targeted gain modulation in cortical networks","intvolume":"        21","language":[{"iso":"eng"}],"publication":"Nature Neuroscience","publication_status":"published","external_id":{"pmid":["30482949"]},"abstract":[{"lang":"eng","text":"Motor cortex (M1) exhibits a rich repertoire of neuronal activities to support the generation of complex movements. Although recent neuronal-network models capture many qualitative aspects of M1 dynamics, they can generate only a few distinct movements. Additionally, it is unclear how M1 efficiently controls movements over a wide range of shapes and speeds. We demonstrate that modulation of neuronal input–output gains in recurrent neuronal-network models with a fixed architecture can dramatically reorganize neuronal activity and thus downstream muscle outputs. Consistent with the observation of diffuse neuromodulatory projections to M1, a relatively small number of modulatory control units provide sufficient flexibility to adjust high-dimensional network activity using a simple reward-based learning rule. Furthermore, it is possible to assemble novel movements from previously learned primitives, and one can separately change movement speed while preserving movement shape. Our results provide a new perspective on the role of modulatory systems in controlling recurrent cortical activity."}],"publisher":"Springer Nature","date_published":"2018-12-01T00:00:00Z","extern":"1","page":"1774-1783","volume":21,"quality_controlled":"1","year":"2018","date_created":"2020-06-30T13:18:02Z","citation":{"apa":"Stroud, J. P., Porter, M. A., Hennequin, G., &#38; Vogels, T. P. (2018). Motor primitives in space and time via targeted gain modulation in cortical networks. <i>Nature Neuroscience</i>. Springer Nature. <a href=\"https://doi.org/10.1038/s41593-018-0276-0\">https://doi.org/10.1038/s41593-018-0276-0</a>","ama":"Stroud JP, Porter MA, Hennequin G, Vogels TP. Motor primitives in space and time via targeted gain modulation in cortical networks. <i>Nature Neuroscience</i>. 2018;21(12):1774-1783. doi:<a href=\"https://doi.org/10.1038/s41593-018-0276-0\">10.1038/s41593-018-0276-0</a>","ieee":"J. P. Stroud, M. A. Porter, G. Hennequin, and T. P. Vogels, “Motor primitives in space and time via targeted gain modulation in cortical networks,” <i>Nature Neuroscience</i>, vol. 21, no. 12. Springer Nature, pp. 1774–1783, 2018.","short":"J.P. Stroud, M.A. Porter, G. Hennequin, T.P. Vogels, Nature Neuroscience 21 (2018) 1774–1783.","mla":"Stroud, Jake P., et al. “Motor Primitives in Space and Time via Targeted Gain Modulation in Cortical Networks.” <i>Nature Neuroscience</i>, vol. 21, no. 12, Springer Nature, 2018, pp. 1774–83, doi:<a href=\"https://doi.org/10.1038/s41593-018-0276-0\">10.1038/s41593-018-0276-0</a>.","chicago":"Stroud, Jake P., Mason A. Porter, Guillaume Hennequin, and Tim P Vogels. “Motor Primitives in Space and Time via Targeted Gain Modulation in Cortical Networks.” <i>Nature Neuroscience</i>. Springer Nature, 2018. <a href=\"https://doi.org/10.1038/s41593-018-0276-0\">https://doi.org/10.1038/s41593-018-0276-0</a>.","ista":"Stroud JP, Porter MA, Hennequin G, Vogels TP. 2018. Motor primitives in space and time via targeted gain modulation in cortical networks. Nature Neuroscience. 21(12), 1774–1783."},"related_material":{"link":[{"url":"https://doi.org/10.1038/s41593-018-0307-x","relation":"erratum"}]},"_id":"8073","article_type":"original","doi":"10.1038/s41593-018-0276-0"},{"publication_status":"published","abstract":[{"text":"Tonic receptors convey stimulus duration and intensity and are implicated in homeostatic control. However, how tonic homeostatic signals are generated and how they reconfigure neural circuits and modify animal behavior is poorly understood. Here we show that Caenorhabditis elegans O2-sensing neurons are tonic receptors that continuously signal ambient [O2] to set the animal's behavioral state. Sustained signaling relied on a Ca2+ relay involving L-type voltage-gated Ca2+ channels, the ryanodine and the inositol-1,4,5-trisphosphate receptors. Tonic activity evoked continuous neuropeptide release, which helps elicit the enduring behavioral state associated with high [O2]. Sustained O2 receptor signaling was propagated to downstream neural circuits, including the hub interneuron RMG. O2 receptors evoked similar locomotory states at particular O2 concentrations, regardless of previous d[O2]/dt. However, a phasic component of the URX receptors' response to high d[O2]/dt, as well as tonic-to-phasic transformations in downstream interneurons, enabled transient reorientation movements shaped by d[O2]/dt. Our results highlight how tonic homeostatic signals can generate both transient and enduring behavioral change.","lang":"eng"}],"external_id":{"pmid":["22388961"]},"volume":15,"quality_controlled":"1","page":"581-591","extern":"1","date_published":"2012-03-04T00:00:00Z","publisher":"Springer Nature","date_created":"2019-03-20T14:23:30Z","citation":{"apa":"Busch, K. E., Laurent, P., Soltesz, Z., Murphy, R. J., Faivre, O., Hedwig, B., … de Bono, M. (2012). Tonic signaling from O2 sensors sets neural circuit activity and behavioral state. <i>Nature Neuroscience</i>. Springer Nature. <a href=\"https://doi.org/10.1038/nn.3061\">https://doi.org/10.1038/nn.3061</a>","mla":"Busch, Karl Emanuel, et al. “Tonic Signaling from O2 Sensors Sets Neural Circuit Activity and Behavioral State.” <i>Nature Neuroscience</i>, vol. 15, no. 4, Springer Nature, 2012, pp. 581–91, doi:<a href=\"https://doi.org/10.1038/nn.3061\">10.1038/nn.3061</a>.","chicago":"Busch, Karl Emanuel, Patrick Laurent, Zoltan Soltesz, Robin Joseph Murphy, Olivier Faivre, Berthold Hedwig, Martin Thomas, Heather L Smith, and Mario de Bono. “Tonic Signaling from O2 Sensors Sets Neural Circuit Activity and Behavioral State.” <i>Nature Neuroscience</i>. Springer Nature, 2012. <a href=\"https://doi.org/10.1038/nn.3061\">https://doi.org/10.1038/nn.3061</a>.","ista":"Busch KE, Laurent P, Soltesz Z, Murphy RJ, Faivre O, Hedwig B, Thomas M, Smith HL, de Bono M. 2012. Tonic signaling from O2 sensors sets neural circuit activity and behavioral state. Nature Neuroscience. 15(4), 581–591.","short":"K.E. Busch, P. Laurent, Z. Soltesz, R.J. Murphy, O. Faivre, B. Hedwig, M. Thomas, H.L. Smith, M. de Bono, Nature Neuroscience 15 (2012) 581–591.","ieee":"K. E. Busch <i>et al.</i>, “Tonic signaling from O2 sensors sets neural circuit activity and behavioral state,” <i>Nature Neuroscience</i>, vol. 15, no. 4. Springer Nature, pp. 581–591, 2012.","ama":"Busch KE, Laurent P, Soltesz Z, et al. Tonic signaling from O2 sensors sets neural circuit activity and behavioral state. <i>Nature Neuroscience</i>. 2012;15(4):581-591. doi:<a href=\"https://doi.org/10.1038/nn.3061\">10.1038/nn.3061</a>"},"year":"2012","_id":"6136","doi":"10.1038/nn.3061","author":[{"last_name":"Busch","first_name":"Karl Emanuel","full_name":"Busch, Karl Emanuel"},{"last_name":"Laurent","full_name":"Laurent, Patrick","first_name":"Patrick"},{"full_name":"Soltesz, Zoltan","first_name":"Zoltan","last_name":"Soltesz"},{"last_name":"Murphy","full_name":"Murphy, Robin Joseph","first_name":"Robin Joseph"},{"last_name":"Faivre","full_name":"Faivre, Olivier","first_name":"Olivier"},{"full_name":"Hedwig, Berthold","first_name":"Berthold","last_name":"Hedwig"},{"last_name":"Thomas","first_name":"Martin","full_name":"Thomas, Martin"},{"first_name":"Heather L","full_name":"Smith, Heather L","last_name":"Smith"},{"first_name":"Mario","full_name":"de Bono, Mario","last_name":"de Bono","id":"4E3FF80E-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-8347-0443"}],"user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","oa_version":"Submitted Version","main_file_link":[{"open_access":"1","url":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3564487/"}],"day":"04","month":"03","publication_identifier":{"issn":["1097-6256","1546-1726"]},"status":"public","type":"journal_article","pmid":1,"title":"Tonic signaling from O2 sensors sets neural circuit activity and behavioral state","issue":"4","oa":1,"date_updated":"2021-01-12T08:06:17Z","intvolume":"        15","language":[{"iso":"eng"}],"publication":"Nature Neuroscience"},{"doi":"10.1038/nn.2276","article_type":"original","_id":"8026","year":"2009","citation":{"apa":"Vogels, T. P., &#38; Abbott, L. F. (2009). Gating multiple signals through detailed balance of excitation and inhibition in spiking networks. <i>Nature Neuroscience</i>. Springer Nature. <a href=\"https://doi.org/10.1038/nn.2276\">https://doi.org/10.1038/nn.2276</a>","mla":"Vogels, Tim P., and L. F. Abbott. “Gating Multiple Signals through Detailed Balance of Excitation and Inhibition in Spiking Networks.” <i>Nature Neuroscience</i>, vol. 12, no. 4, Springer Nature, 2009, pp. 483–91, doi:<a href=\"https://doi.org/10.1038/nn.2276\">10.1038/nn.2276</a>.","chicago":"Vogels, Tim P, and L F Abbott. “Gating Multiple Signals through Detailed Balance of Excitation and Inhibition in Spiking Networks.” <i>Nature Neuroscience</i>. Springer Nature, 2009. <a href=\"https://doi.org/10.1038/nn.2276\">https://doi.org/10.1038/nn.2276</a>.","ista":"Vogels TP, Abbott LF. 2009. Gating multiple signals through detailed balance of excitation and inhibition in spiking networks. Nature Neuroscience. 12(4), 483–491.","short":"T.P. Vogels, L.F. Abbott, Nature Neuroscience 12 (2009) 483–491.","ieee":"T. P. Vogels and L. F. Abbott, “Gating multiple signals through detailed balance of excitation and inhibition in spiking networks,” <i>Nature Neuroscience</i>, vol. 12, no. 4. Springer Nature, pp. 483–491, 2009.","ama":"Vogels TP, Abbott LF. Gating multiple signals through detailed balance of excitation and inhibition in spiking networks. <i>Nature Neuroscience</i>. 2009;12(4):483-491. doi:<a href=\"https://doi.org/10.1038/nn.2276\">10.1038/nn.2276</a>"},"date_created":"2020-06-25T13:10:55Z","date_published":"2009-04-01T00:00:00Z","publisher":"Springer Nature","quality_controlled":"1","volume":12,"page":"483-491","extern":"1","abstract":[{"text":"Recent theoretical work has provided a basic understanding of signal propagation in networks of spiking neurons, but mechanisms for gating and controlling these signals have not been investigated previously. Here we introduce an idea for the gating of multiple signals in cortical networks that combines principles of signal propagation with aspects of balanced networks. Specifically, we studied networks in which incoming excitatory signals are normally cancelled by locally evoked inhibition, leaving the targeted layer unresponsive. Transmission can be gated 'on' by modulating excitatory and inhibitory gains to upset this detailed balance. We illustrate gating through detailed balance in large networks of integrate-and-fire neurons. We show successful gating of multiple signals and study failure modes that produce effects reminiscent of clinically observed pathologies. Provided that the individual signals are detectable, detailed balance has a large capacity for gating multiple signals.","lang":"eng"}],"external_id":{"pmid":["19305402"]},"publication_status":"published","publication":"Nature Neuroscience","language":[{"iso":"eng"}],"intvolume":"        12","issue":"4","article_processing_charge":"No","date_updated":"2021-01-12T08:16:36Z","oa":1,"title":"Gating multiple signals through detailed balance of excitation and inhibition in spiking networks","status":"public","type":"journal_article","pmid":1,"month":"04","publication_identifier":{"issn":["1097-6256","1546-1726"]},"user_id":"D865714E-FA4E-11E9-B85B-F5C5E5697425","oa_version":"Submitted Version","main_file_link":[{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2693069/","open_access":"1"}],"day":"01","author":[{"first_name":"Tim P","full_name":"Vogels, Tim P","orcid":"0000-0003-3295-6181","last_name":"Vogels","id":"CB6FF8D2-008F-11EA-8E08-2637E6697425"},{"last_name":"Abbott","full_name":"Abbott, L F","first_name":"L F"}]},{"date_updated":"2021-01-12T08:06:25Z","year":"2003","issue":"11","date_created":"2019-03-21T09:47:53Z","citation":{"chicago":"Rogers, Candida, Vincenzina Reale, Kyuhyung Kim, Heather Chatwin, Chris Li, Peter Evans, and Mario de Bono. “Inhibition of Caenorhabditis Elegans Social Feeding by FMRFamide-Related Peptide Activation of NPR-1.” <i>Nature Neuroscience</i>. Springer Nature, 2003. <a href=\"https://doi.org/10.1038/nn1140\">https://doi.org/10.1038/nn1140</a>.","ista":"Rogers C, Reale V, Kim K, Chatwin H, Li C, Evans P, de Bono M. 2003. Inhibition of Caenorhabditis elegans social feeding by FMRFamide-related peptide activation of NPR-1. Nature Neuroscience. 6(11), 1178–1185.","mla":"Rogers, Candida, et al. “Inhibition of Caenorhabditis Elegans Social Feeding by FMRFamide-Related Peptide Activation of NPR-1.” <i>Nature Neuroscience</i>, vol. 6, no. 11, Springer Nature, 2003, pp. 1178–85, doi:<a href=\"https://doi.org/10.1038/nn1140\">10.1038/nn1140</a>.","ama":"Rogers C, Reale V, Kim K, et al. Inhibition of Caenorhabditis elegans social feeding by FMRFamide-related peptide activation of NPR-1. <i>Nature Neuroscience</i>. 2003;6(11):1178-1185. doi:<a href=\"https://doi.org/10.1038/nn1140\">10.1038/nn1140</a>","ieee":"C. Rogers <i>et al.</i>, “Inhibition of Caenorhabditis elegans social feeding by FMRFamide-related peptide activation of NPR-1,” <i>Nature Neuroscience</i>, vol. 6, no. 11. Springer Nature, pp. 1178–1185, 2003.","short":"C. Rogers, V. Reale, K. Kim, H. Chatwin, C. Li, P. Evans, M. de Bono, Nature Neuroscience 6 (2003) 1178–1185.","apa":"Rogers, C., Reale, V., Kim, K., Chatwin, H., Li, C., Evans, P., &#38; de Bono, M. (2003). Inhibition of Caenorhabditis elegans social feeding by FMRFamide-related peptide activation of NPR-1. <i>Nature Neuroscience</i>. Springer Nature. <a href=\"https://doi.org/10.1038/nn1140\">https://doi.org/10.1038/nn1140</a>"},"title":"Inhibition of Caenorhabditis elegans social feeding by FMRFamide-related peptide activation of NPR-1","intvolume":"         6","language":[{"iso":"eng"}],"_id":"6156","publication":"Nature Neuroscience","doi":"10.1038/nn1140","publication_status":"published","author":[{"full_name":"Rogers, Candida","first_name":"Candida","last_name":"Rogers"},{"last_name":"Reale","first_name":"Vincenzina","full_name":"Reale, Vincenzina"},{"first_name":"Kyuhyung","full_name":"Kim, Kyuhyung","last_name":"Kim"},{"full_name":"Chatwin, Heather","first_name":"Heather","last_name":"Chatwin"},{"first_name":"Chris","full_name":"Li, Chris","last_name":"Li"},{"full_name":"Evans, Peter","first_name":"Peter","last_name":"Evans"},{"full_name":"de Bono, Mario","first_name":"Mario","last_name":"de Bono","id":"4E3FF80E-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-8347-0443"}],"publication_identifier":{"issn":["1097-6256","1546-1726"]},"month":"10","day":"12","oa_version":"None","external_id":{"pmid":["14555955"]},"abstract":[{"lang":"eng","text":"Social and solitary feeding in natural Caenorhabditis elegans isolates are associated with two alleles of the orphan G-protein-coupled receptor (GPCR) NPR-1: social feeders contain NPR-1 215F, whereas solitary feeders contain NPR-1 215V. Here we identify FMRFamide-related neuropeptides (FaRPs) encoded by the flp-18 and flp-21 genes as NPR-1 ligands and show that these peptides can differentially activate the NPR-1 215F and NPR-1 215V receptors. Multicopy overexpression of flp-21 transformed wild social animals into solitary feeders. Conversely, a flp-21 deletion partially phenocopied the npr-1(null) phenotype, which is consistent with NPR-1 activation by FLP-21 in vivo but also implicates other ligands for NPR-1. Phylogenetic studies indicate that the dominant npr-1 215V allele likely arose from an ancestral npr-1 215F gene in C. elegans. Our data suggest a model in which solitary feeding evolved in an ancestral social strain of C. elegans by a gain-of-function mutation that modified the response of NPR-1 to FLP-18 and FLP-21 ligands."}],"user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","publisher":"Springer Nature","pmid":1,"status":"public","type":"journal_article","date_published":"2003-10-12T00:00:00Z","page":"1178-1185","extern":"1","volume":6,"quality_controlled":"1"},{"date_updated":"2023-07-25T09:02:48Z","article_processing_charge":"No","issue":"11","title":"Polarized and compartment-dependent distribution of HCN1 in pyramidal cell dendrites","intvolume":"         5","scopus_import":"1","language":[{"iso":"eng"}],"publication":"Nature Neuroscience","author":[{"first_name":"Andrea","full_name":"Lörincz, Andrea","last_name":"Lörincz"},{"last_name":"Notomi","first_name":"Takuya","full_name":"Notomi, Takuya"},{"first_name":"Gábor","full_name":"Tamás, Gábor","last_name":"Tamás"},{"id":"499F3ABC-F248-11E8-B48F-1D18A9856A87","last_name":"Shigemoto","orcid":"0000-0001-8761-9444","full_name":"Shigemoto, Ryuichi","first_name":"Ryuichi"},{"last_name":"Nusser","full_name":"Nusser, Zoltán","first_name":"Zoltán"}],"month":"11","publication_identifier":{"issn":["1097-6256"]},"oa_version":"None","day":"01","user_id":"ea97e931-d5af-11eb-85d4-e6957dddbf17","pmid":1,"type":"journal_article","status":"public","acknowledgement":"Z.N. received grants from the Hungarian Science Foundation (T032309), the Howard Hughes Medical Institute, the James S. McDonnell Foundation, the Wellcome Trust and the Boehringer Ingelheim Fund. Z.N. and R.S. received grants from CREST—Japan Science and Technology Corporation. G.T. is funded by the Wellcome Trust.","year":"2002","date_created":"2018-12-11T11:58:43Z","citation":{"chicago":"Lörincz, Andrea, Takuya Notomi, Gábor Tamás, Ryuichi Shigemoto, and Zoltán Nusser. “Polarized and Compartment-Dependent Distribution of HCN1 in Pyramidal Cell Dendrites.” <i>Nature Neuroscience</i>. Nature Publishing Group, 2002. <a href=\"https://doi.org/10.1038/nn962\">https://doi.org/10.1038/nn962</a>.","mla":"Lörincz, Andrea, et al. “Polarized and Compartment-Dependent Distribution of HCN1 in Pyramidal Cell Dendrites.” <i>Nature Neuroscience</i>, vol. 5, no. 11, Nature Publishing Group, 2002, pp. 1185–93, doi:<a href=\"https://doi.org/10.1038/nn962\">10.1038/nn962</a>.","ista":"Lörincz A, Notomi T, Tamás G, Shigemoto R, Nusser Z. 2002. Polarized and compartment-dependent distribution of HCN1 in pyramidal cell dendrites. Nature Neuroscience. 5(11), 1185–1193.","ieee":"A. Lörincz, T. Notomi, G. Tamás, R. Shigemoto, and Z. Nusser, “Polarized and compartment-dependent distribution of HCN1 in pyramidal cell dendrites,” <i>Nature Neuroscience</i>, vol. 5, no. 11. Nature Publishing Group, pp. 1185–1193, 2002.","ama":"Lörincz A, Notomi T, Tamás G, Shigemoto R, Nusser Z. Polarized and compartment-dependent distribution of HCN1 in pyramidal cell dendrites. <i>Nature Neuroscience</i>. 2002;5(11):1185-1193. doi:<a href=\"https://doi.org/10.1038/nn962\">10.1038/nn962</a>","short":"A. Lörincz, T. Notomi, G. Tamás, R. Shigemoto, Z. Nusser, Nature Neuroscience 5 (2002) 1185–1193.","apa":"Lörincz, A., Notomi, T., Tamás, G., Shigemoto, R., &#38; Nusser, Z. (2002). Polarized and compartment-dependent distribution of HCN1 in pyramidal cell dendrites. <i>Nature Neuroscience</i>. Nature Publishing Group. <a href=\"https://doi.org/10.1038/nn962\">https://doi.org/10.1038/nn962</a>"},"publist_id":"4278","_id":"2620","article_type":"original","doi":"10.1038/nn962","publication_status":"published","external_id":{"pmid":["12389030"]},"abstract":[{"text":"An ion channel's function depends largely on its location and density on neurons. Here we used high-resolution immunolocalization to determine the subcellular distribution of the hyperpolarization-activated and cyclic-nucleotide-gated channel subunit 1 (HCN1) in rat brain. Light microscopy revealed graded HCN1 immunoreactivity in apical dendrites of hippocampal, subicular and neocortical layer-5 pyramidal cells. Quantitative comparison of immunogold densities showed a 60-fold increase from somatic to distal apical dendritic membranes. Distal dendritic shafts had 16 times more HCN1 labeling than proximal dendrites of similar diameters. At the same distance from the soma, the density of HCN1 was significantly higher in dendritic shafts than in spines. Our results reveal the complex cell surface distribution of voltage-gated ion-channels, and predict its role in increasing the computational power of single neurons via subcellular domain and input-specific mechanisms.","lang":"eng"}],"publisher":"Nature Publishing Group","date_published":"2002-11-01T00:00:00Z","page":"1185 - 1193","extern":"1","quality_controlled":"1","volume":5}]