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Chiossi, Adaptive Hierarchical Representations in the Hippocampus, Institute of Science and Technology Austria, 2024.","ista":"Chiossi HSC. 2024. Adaptive hierarchical representations in the hippocampus. Institute of Science and Technology Austria.","chicago":"Chiossi, Heloisa S. C. “Adaptive Hierarchical Representations in the Hippocampus.” Institute of Science and Technology Austria, 2024. <a href=\"https://doi.org/10.15479/at:ista:14821\">https://doi.org/10.15479/at:ista:14821</a>.","mla":"Chiossi, Heloisa S. C. <i>Adaptive Hierarchical Representations in the Hippocampus</i>. Institute of Science and Technology Austria, 2024, doi:<a href=\"https://doi.org/10.15479/at:ista:14821\">10.15479/at:ista:14821</a>.","apa":"Chiossi, H. S. C. (2024). <i>Adaptive hierarchical representations in the hippocampus</i>. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/at:ista:14821\">https://doi.org/10.15479/at:ista:14821</a>"},"year":"2024","ec_funded":1,"degree_awarded":"PhD","file_date_updated":"2024-01-19T11:04:05Z","_id":"14821","doi":"10.15479/at:ista:14821","author":[{"full_name":"Chiossi, Heloisa","first_name":"Heloisa","last_name":"Chiossi","id":"2BBA502C-F248-11E8-B48F-1D18A9856A87"}],"day":"19","oa_version":"Published Version","user_id":"8b945eb4-e2f2-11eb-945a-df72226e66a9","file":[{"checksum":"d3fa3de1abd5af5204c13e9d55375615","file_id":"14838","file_name":"PhD_Thesis_190124.docx","date_created":"2024-01-19T11:04:05Z","date_updated":"2024-01-19T11:04:05Z","creator":"hchiossi","access_level":"closed","content_type":"application/vnd.openxmlformats-officedocument.wordprocessingml.document","file_size":8656268,"relation":"source_file"},{"embargo":"2025-01-19","checksum":"13adc8dcfb5b6b18107f89f0a98fa8bd","file_name":"PhD_Thesis_190124.pdf","file_id":"14839","date_created":"2024-01-19T11:03:59Z","date_updated":"2024-01-19T11:03:59Z","creator":"hchiossi","embargo_to":"open_access","access_level":"closed","content_type":"application/pdf","file_size":6567275,"relation":"main_file"}],"publication_identifier":{"issn":["2663 - 337X"]},"month":"01","alternative_title":["ISTA Thesis"],"type":"dissertation","status":"public","title":"Adaptive hierarchical representations in the hippocampus","date_updated":"2024-02-01T09:50:29Z","article_processing_charge":"No","has_accepted_license":"1","language":[{"iso":"eng"}]},{"title":"Genetic information and biological optimization","article_processing_charge":"No","oa":1,"date_updated":"2025-06-30T13:21:09Z","has_accepted_license":"1","language":[{"iso":"eng"}],"author":[{"last_name":"Hledik","id":"4171253A-F248-11E8-B48F-1D18A9856A87","first_name":"Michal","full_name":"Hledik, Michal"}],"file":[{"date_created":"2024-02-23T13:50:53Z","date_updated":"2024-02-23T13:50:53Z","success":1,"file_id":"15021","checksum":"b2d3da47c98d481577a4baf68944fe41","file_name":"hledik thesis pdfa 2b.pdf","relation":"main_file","access_level":"open_access","content_type":"application/pdf","file_size":7102089,"creator":"mhledik"},{"file_size":14014790,"relation":"source_file","content_type":"application/zip","access_level":"closed","creator":"mhledik","date_created":"2024-02-23T13:50:54Z","date_updated":"2024-02-23T14:20:16Z","file_id":"15022","checksum":"eda9b9430da2610fee7ce1c1419a479a","file_name":"hledik thesis source.zip"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","oa_version":"Published Version","day":"23","month":"02","publication_identifier":{"issn":["2663 - 337X"]},"status":"public","type":"dissertation","alternative_title":["ISTA Thesis"],"keyword":["Theoretical biology","Optimality","Evolution","Information"],"citation":{"apa":"Hledik, M. (2024). <i>Genetic information and biological optimization</i>. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/at:ista:15020\">https://doi.org/10.15479/at:ista:15020</a>","short":"M. Hledik, Genetic Information and Biological Optimization, Institute of Science and Technology Austria, 2024.","ieee":"M. Hledik, “Genetic information and biological optimization,” Institute of Science and Technology Austria, 2024.","ama":"Hledik M. Genetic information and biological optimization. 2024. doi:<a href=\"https://doi.org/10.15479/at:ista:15020\">10.15479/at:ista:15020</a>","mla":"Hledik, Michal. <i>Genetic Information and Biological Optimization</i>. Institute of Science and Technology Austria, 2024, doi:<a href=\"https://doi.org/10.15479/at:ista:15020\">10.15479/at:ista:15020</a>.","ista":"Hledik M. 2024. Genetic information and biological optimization. Institute of Science and Technology Austria.","chicago":"Hledik, Michal. “Genetic Information and Biological Optimization.” Institute of Science and Technology Austria, 2024. <a href=\"https://doi.org/10.15479/at:ista:15020\">https://doi.org/10.15479/at:ista:15020</a>."},"date_created":"2024-02-23T14:02:04Z","year":"2024","related_material":{"record":[{"status":"public","relation":"part_of_dissertation","id":"7553"},{"status":"public","relation":"part_of_dissertation","id":"7606"},{"id":"12081","relation":"part_of_dissertation","status":"public"}]},"ec_funded":1,"acknowledged_ssus":[{"_id":"ScienComp"}],"_id":"15020","file_date_updated":"2024-02-23T14:20:16Z","doi":"10.15479/at:ista:15020","publication_status":"published","abstract":[{"text":"This thesis consists of four distinct pieces of work within theoretical biology, with two themes in common: the concept of optimization in biological systems, and the use of information-theoretic tools to quantify biological stochasticity and statistical uncertainty.\r\nChapter 2 develops a statistical framework for studying biological systems which we believe to be optimized for a particular utility function, such as retinal neurons conveying information about visual stimuli. We formalize such beliefs as maximum-entropy Bayesian priors, constrained by the expected utility. We explore how such priors aid inference of system parameters with limited data and enable optimality hypothesis testing: is the utility higher than by chance?\r\nChapter 3 examines the ultimate biological optimization process: evolution by natural selection. As some individuals survive and reproduce more successfully than others, populations evolve towards fitter genotypes and phenotypes. We formalize this as accumulation of genetic information, and use population genetics theory to study how much such information can be accumulated per generation and maintained in the face of random mutation and genetic drift. We identify the population size and fitness variance as the key quantities that control information accumulation and maintenance.\r\nChapter 4 reuses the concept of genetic information from Chapter 3, but from a different perspective: we ask how much genetic information organisms actually need, in particular in the context of gene regulation. For example, how much information is needed to bind transcription factors at correct locations within the genome? Population genetics provides us with a refined answer: with an increasing population size, populations achieve higher fitness by maintaining more genetic information. Moreover, regulatory parameters experience selection pressure to optimize the fitness-information trade-off, i.e. minimize the information needed for a given fitness. This provides an evolutionary derivation of the optimization priors introduced in Chapter 2.\r\nChapter 5 proves an upper bound on mutual information between a signal and a communication channel output (such as neural activity). Mutual information is an important utility measure for biological systems, but its practical use can be difficult due to the large dimensionality of many biological channels. Sometimes, a lower bound on mutual information is computed by replacing the high-dimensional channel outputs with decodes (signal estimates). Our result provides a corresponding upper bound, provided that the decodes are the maximum posterior estimates of the signal.","lang":"eng"}],"ddc":["576","519"],"project":[{"call_identifier":"H2020","name":"International IST Doctoral Program","_id":"2564DBCA-B435-11E9-9278-68D0E5697425","grant_number":"665385"},{"name":"Can evolution minimize spurious signaling crosstalk to reach optimal performance?","_id":"2665AAFE-B435-11E9-9278-68D0E5697425","grant_number":"RGP0034/2018"},{"name":"Understanding the evolution of continuous genomes","grant_number":"101055327","_id":"bd6958e0-d553-11ed-ba76-86eba6a76c00"}],"department":[{"_id":"GradSch"},{"_id":"NiBa"},{"_id":"GaTk"}],"page":"158","date_published":"2024-02-23T00:00:00Z","supervisor":[{"id":"4880FE40-F248-11E8-B48F-1D18A9856A87","last_name":"Barton","orcid":"0000-0002-8548-5240","first_name":"Nicholas H","full_name":"Barton, Nicholas H"},{"full_name":"Tkačik, Gašper","first_name":"Gašper","orcid":"0000-0002-6699-1455","last_name":"Tkačik","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87"}],"publisher":"Institute of Science and Technology Austria"},{"language":[{"iso":"eng"}],"article_processing_charge":"No","oa":1,"date_updated":"2025-05-26T09:05:10Z","title":"Local adaptation, genetic load and extinction in metapopulations","has_accepted_license":"1","type":"dissertation","status":"public","alternative_title":["ISTA Thesis"],"author":[{"orcid":"0000-0003-1971-8314","id":"41AD96DC-F248-11E8-B48F-1D18A9856A87","last_name":"Olusanya","first_name":"Oluwafunmilola O","full_name":"Olusanya, Oluwafunmilola O"}],"month":"01","publication_identifier":{"issn":["2663 - 337X"]},"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","file":[{"file_id":"14730","checksum":"de179b1c6758f182ff0c70d8b38c1501","file_name":"FinalSubmission_Thesis_OLUSANYA.zip","date_updated":"2024-01-03T18:30:13Z","date_created":"2024-01-03T18:30:13Z","creator":"oolusany","access_level":"closed","relation":"source_file","content_type":"application/zip","file_size":16986244},{"creator":"oolusany","relation":"main_file","access_level":"open_access","file_size":6460403,"content_type":"application/pdf","file_id":"14731","checksum":"0e331585e3cd4823320aab4e69e64ccf","file_name":"FinalSubmission2_Thesis_OLUSANYA.pdf","success":1,"date_updated":"2024-01-03T18:31:34Z","date_created":"2024-01-03T18:31:34Z"}],"oa_version":"Published Version","day":"19","_id":"14711","file_date_updated":"2024-01-03T18:31:34Z","acknowledged_ssus":[{"_id":"SSU"}],"doi":"10.15479/at:ista:14711","year":"2024","date_created":"2023-12-26T22:49:53Z","related_material":{"record":[{"status":"public","id":"10658","relation":"part_of_dissertation"},{"status":"public","id":"10787","relation":"part_of_dissertation"},{"id":"14732","relation":"part_of_dissertation","status":"public"}]},"degree_awarded":"MS","ec_funded":1,"project":[{"name":"International IST Doctoral Program","call_identifier":"H2020","grant_number":"665385","_id":"2564DBCA-B435-11E9-9278-68D0E5697425"},{"name":"Causes and consequences of population fragmentation","grant_number":"P32896","_id":"c08d3278-5a5b-11eb-8a69-fdb09b55f4b8"},{"name":"Polygenic Adaptation in a Metapopulation","_id":"34c872fe-11ca-11ed-8bc3-8534b82131e6","grant_number":"26380"}],"supervisor":[{"full_name":"Barton, Nicholas H","first_name":"Nicholas H","last_name":"Barton","id":"4880FE40-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-8548-5240"},{"full_name":"Polechova, Jitka","first_name":"Jitka","last_name":"Polechova"},{"last_name":"Sachdeva","first_name":"Himani","full_name":"Sachdeva, Himani"}],"date_published":"2024-01-19T00:00:00Z","publisher":"Institute of Science and Technology Austria","page":"183","department":[{"_id":"NiBa"},{"_id":"GradSch"}],"publication_status":"published","tmp":{"image":"/images/cc_by_nc_sa.png","legal_code_url":"https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode","name":"Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)","short":"CC BY-NC-SA (4.0)"},"ddc":["576"],"abstract":[{"text":"In nature, different species find their niche in a range of environments, each with its unique characteristics. While some thrive in uniform (homogeneous) landscapes where environmental conditions stay relatively consistent across space, others traverse the complexities of spatially heterogeneous terrains. Comprehending how species are distributed and how they interact within these landscapes holds the key to gaining insights into their evolutionary dynamics while also informing conservation and management strategies.\r\n\r\nFor species inhabiting heterogeneous landscapes, when the rate of dispersal is low compared to spatial fluctuations in selection pressure, localized adaptations may emerge. Such adaptation in response to varying selection strengths plays an important role in the persistence of populations in our rapidly changing world. Hence, species in nature are continuously in a struggle to adapt to local environmental conditions, to ensure their continued survival. Natural populations can often adapt in time scales short enough for evolutionary changes to influence ecological dynamics and vice versa, thereby creating a feedback between evolution and demography. The analysis of this feedback and the relative contributions of gene flow, demography, drift, and natural selection to genetic variation and differentiation has remained a recurring theme in evolutionary biology. Nevertheless, the effective role of these forces in maintaining variation and shaping patterns of diversity is not fully understood. Even in homogeneous environments devoid of local adaptations, such understanding remains elusive. Understanding this feedback is crucial, for example in determining the conditions under which extinction risk can be mitigated in peripheral populations subject to deleterious mutation accumulation at the edges of species’ ranges\r\nas well as in highly fragmented populations.\r\n\r\nIn this thesis we explore both uniform and spatially heterogeneous metapopulations, investigating and providing theoretical insights into the dynamics of local adaptation in the latter and examining the dynamics of load and extinction as well as the impact of joint ecological and evolutionary (eco-evolutionary) dynamics in the former. The thesis is divided into 5 chapters.\r\n\r\nChapter 1 provides a general introduction into the subject matter, clarifying concepts and ideas used throughout the thesis. In chapter 2, we explore how fast a species distributed across a heterogeneous landscape adapts to changing conditions marked by alterations in carrying capacity, selection pressure, and migration rate.\r\n\r\nIn chapter 3, we investigate how migration selection and drift influences adaptation and the maintenance of variation in a metapopulation with three habitats, an extension of previous models of adaptation in two habitats. We further develop analytical approximations for the critical threshold required for polymorphism to persist.\r\n\r\nThe focus of chapter 4 of the thesis is on understanding the interplay between ecology and evolution as coupled processes. We investigate how eco-evolutionary feedback between migration, selection, drift, and demography influences eco-evolutionary outcomes in marginal populations subject to deleterious mutation accumulation. Using simulations as well as theoretical approximations of the coupled dynamics of population size and allele frequency, we analyze how gene flow from a large mainland source influences genetic load and population size on an island (i.e., in a marginal population) under genetically realistic assumptions. Analyses of this sort are important because small isolated populations, are repeatedly affected by complex interactions between ecological and evolutionary processes, which can lead to their death. Understanding these interactions can therefore provide an insight into the conditions under which extinction risk can be mitigated in peripheral populations thus, contributing to conservation and restoration efforts.\r\n\r\nChapter 5 extends the analysis in chapter 4 to consider the dynamics of load (due to deleterious mutation accumulation) and extinction risk in a metapopulation. We explore the role of gene flow, selection, and dominance on load and extinction risk and further pinpoint critical thresholds required for metapopulation persistence.\r\n\r\nOverall this research contributes to our understanding of ecological and evolutionary mechanisms that shape species’ persistence in fragmented landscapes, a crucial foundation for successful conservation efforts and biodiversity management.","lang":"eng"}]},{"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":{"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>","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>.","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>.","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.","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.","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>","short":"D. Gupta, W.F. Mlynarski, A.L. Sumser, O. Symonova, J. Svaton, M.A. Jösch, Nature Neuroscience 26 (2023) 606–614."},"ec_funded":1,"related_material":{"record":[{"relation":"research_data","id":"12370","status":"public"}]},"file_date_updated":"2023-10-04T11:40:51Z","_id":"12349","article_type":"original","acknowledged_ssus":[{"_id":"ScienComp"},{"_id":"PreCl"},{"_id":"LifeSc"},{"_id":"Bio"}],"doi":"10.1038/s41593-023-01280-0","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":{"pmid":["36959418"],"isi":["000955258300002"]},"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"}],"project":[{"grant_number":"665385","_id":"2564DBCA-B435-11E9-9278-68D0E5697425","call_identifier":"H2020","name":"International IST Doctoral Program"},{"grant_number":"P34015","_id":"626c45b5-2b32-11ec-9570-e509828c1ba6","name":"Efficient coding with biophysical realism"},{"_id":"2634E9D2-B435-11E9-9278-68D0E5697425","grant_number":"756502","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","department":[{"_id":"GradSch"},{"_id":"MaJö"}],"page":"606-614","volume":26,"quality_controlled":"1","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","language":[{"iso":"eng"}],"publication":"Nature Neuroscience","author":[{"last_name":"Gupta","id":"2A485EBE-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-7400-6665","full_name":"Gupta, Divyansh","first_name":"Divyansh"},{"last_name":"Mlynarski","id":"358A453A-F248-11E8-B48F-1D18A9856A87","full_name":"Mlynarski, Wiktor F","first_name":"Wiktor F"},{"first_name":"Anton L","full_name":"Sumser, Anton L","last_name":"Sumser","id":"3320A096-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-4792-1881"},{"full_name":"Symonova, Olga","first_name":"Olga","last_name":"Symonova","id":"3C0C7BC6-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-2012-9947"},{"last_name":"Svaton","id":"f7f724c3-9d6f-11ed-9f44-e5c5f3a5bee2","orcid":"0000-0002-6198-2939","full_name":"Svaton, Jan","first_name":"Jan"},{"first_name":"Maximilian A","full_name":"Jösch, Maximilian A","last_name":"Jösch","id":"2BD278E6-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-3937-1330"}],"month":"04","publication_identifier":{"eissn":["1546-1726"],"issn":["1097-6256"]},"day":"01","oa_version":"Published Version","file":[{"checksum":"a33d91e398e548f34003170e10988368","file_name":"2023_NatureNeuroscience_Gupta.pdf","file_id":"14395","success":1,"date_updated":"2023-10-04T11:40:51Z","date_created":"2023-10-04T11:40:51Z","creator":"dernst","relation":"main_file","access_level":"open_access","content_type":"application/pdf","file_size":6144866}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","pmid":1,"status":"public","type":"journal_article"},{"acknowledged_ssus":[{"_id":"ScienComp"},{"_id":"M-Shop"},{"_id":"Bio"},{"_id":"PreCl"},{"_id":"LifeSc"}],"file_date_updated":"2023-01-26T10:51:34Z","_id":"12370","doi":"10.15479/AT:ISTA:12370","title":"Research Data for: Panoramic visual statistics shape retina-wide organization of receptive fields","citation":{"mla":"Gupta, Divyansh, et al. <i>Research Data for: Panoramic Visual Statistics Shape Retina-Wide Organization of Receptive Fields</i>. Institute of Science and Technology Austria, 2023, doi:<a href=\"https://doi.org/10.15479/AT:ISTA:12370\">10.15479/AT:ISTA:12370</a>.","chicago":"Gupta, Divyansh, Anton L Sumser, and Maximilian A Jösch. “Research Data for: Panoramic Visual Statistics Shape Retina-Wide Organization of Receptive Fields.” Institute of Science and Technology Austria, 2023. <a href=\"https://doi.org/10.15479/AT:ISTA:12370\">https://doi.org/10.15479/AT:ISTA:12370</a>.","ista":"Gupta D, Sumser AL, Jösch MA. 2023. Research Data for: Panoramic visual statistics shape retina-wide organization of receptive fields, Institute of Science and Technology Austria, <a href=\"https://doi.org/10.15479/AT:ISTA:12370\">10.15479/AT:ISTA:12370</a>.","ieee":"D. Gupta, A. L. Sumser, and M. A. Jösch, “Research Data for: Panoramic visual statistics shape retina-wide organization of receptive fields.” Institute of Science and Technology Austria, 2023.","ama":"Gupta D, Sumser AL, Jösch MA. Research Data for: Panoramic visual statistics shape retina-wide organization of receptive fields. 2023. doi:<a href=\"https://doi.org/10.15479/AT:ISTA:12370\">10.15479/AT:ISTA:12370</a>","short":"D. Gupta, A.L. Sumser, M.A. Jösch, (2023).","apa":"Gupta, D., Sumser, A. L., &#38; Jösch, M. A. (2023). Research Data for: Panoramic visual statistics shape retina-wide organization of receptive fields. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/AT:ISTA:12370\">https://doi.org/10.15479/AT:ISTA:12370</a>"},"date_created":"2023-01-25T12:45:18Z","oa":1,"date_updated":"2023-10-04T11:41:04Z","year":"2023","article_processing_charge":"No","ec_funded":1,"related_material":{"record":[{"relation":"used_in_publication","id":"12349","status":"public"}]},"has_accepted_license":"1","project":[{"_id":"2564DBCA-B435-11E9-9278-68D0E5697425","grant_number":"665385","name":"International IST Doctoral Program","call_identifier":"H2020"},{"grant_number":"P34015","_id":"626c45b5-2b32-11ec-9570-e509828c1ba6","name":"Efficient coding with biophysical realism"},{"name":"Circuits of Visual Attention","call_identifier":"H2020","_id":"2634E9D2-B435-11E9-9278-68D0E5697425","grant_number":"756502"},{"grant_number":"LT000256","_id":"266D407A-B435-11E9-9278-68D0E5697425","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"}],"department":[{"_id":"GradSch"},{"_id":"MaJö"}],"publisher":"Institute of Science and Technology Austria","status":"public","type":"research_data","date_published":"2023-01-26T00:00:00Z","author":[{"last_name":"Gupta","id":"2A485EBE-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-7400-6665","first_name":"Divyansh","full_name":"Gupta, Divyansh"},{"id":"3320A096-F248-11E8-B48F-1D18A9856A87","last_name":"Sumser","orcid":"0000-0002-4792-1881","full_name":"Sumser, Anton L","first_name":"Anton L"},{"orcid":"0000-0002-3937-1330","last_name":"Jösch","id":"2BD278E6-F248-11E8-B48F-1D18A9856A87","first_name":"Maximilian A","full_name":"Jösch, Maximilian A"}],"day":"26","oa_version":"Published Version","abstract":[{"lang":"eng","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. 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Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)","short":"CC BY-NC-SA (4.0)"},"month":"01"},{"publication_status":"published","ddc":["610"],"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"},"abstract":[{"lang":"eng","text":"The brain is an exceptionally sophisticated organ consisting of billions of cells and trillions of \r\nconnections that orchestrate our cognition and behavior. To decode its complex connectivity, it is \r\npivotal to disentangle its intricate architecture spanning from cm-sized circuits down to tens of \r\nnm-small synapses.\r\nTo achieve this goal, I developed CATS – Comprehensive Analysis of nervous Tissue across \r\nScales, a versatile toolbox for obtaining a holistic view of nervous tissue context with (super\u0002resolution) fluorescence microscopy. CATS combines comprehensive labeling of the extracellular\r\nspace, that is compatible with chemical fixation, with information on molecular markers, super\u0002resolved data acquisition and machine-learning based data analysis for segmentation and synapse \r\nidentification.\r\nI used CATS to analyze key features of nervous tissue connectivity, ranging from whole tissue \r\narchitecture, neuronal in- and output-fields, down to synapse morphology.\r\nFocusing on the hippocampal circuitry, I quantified synaptic transmission properties of mossy \r\nfiber boutons and analyzed the connectivity pattern of dentate gyrus granule cells with CA3 \r\npyramidal neurons. This shows that CATS is a viable tool to study hallmarks of neuronal \r\nconnectivity with light microscopy."}],"project":[{"name":"International IST Doctoral Program","call_identifier":"H2020","grant_number":"665385","_id":"2564DBCA-B435-11E9-9278-68D0E5697425"},{"name":"Molecular Drug Targets","call_identifier":"FWF","_id":"26AA4EF2-B435-11E9-9278-68D0E5697425","grant_number":"W1232-B24"}],"publisher":"Institute of Science and Technology Austria","supervisor":[{"id":"42EFD3B6-F248-11E8-B48F-1D18A9856A87","last_name":"Danzl","orcid":"0000-0001-8559-3973","full_name":"Danzl, Johann G","first_name":"Johann G"}],"date_published":"2023-01-09T00:00:00Z","department":[{"_id":"GradSch"},{"_id":"JoDa"}],"page":"201","year":"2023","citation":{"mla":"Michalska, Julia M. <i>A Versatile Toolbox for the Comprehensive Analysis of Nervous Tissue Organization with Light Microscopy</i>. Institute of Science and Technology Austria, 2023, doi:<a href=\"https://doi.org/10.15479/at:ista:12470\">10.15479/at:ista:12470</a>.","chicago":"Michalska, Julia M. “A Versatile Toolbox for the Comprehensive Analysis of Nervous Tissue Organization with Light Microscopy.” Institute of Science and Technology Austria, 2023. <a href=\"https://doi.org/10.15479/at:ista:12470\">https://doi.org/10.15479/at:ista:12470</a>.","ista":"Michalska JM. 2023. A versatile toolbox for the comprehensive analysis of nervous tissue organization with light microscopy. Institute of Science and Technology Austria.","short":"J.M. Michalska, A Versatile Toolbox for the Comprehensive Analysis of Nervous Tissue Organization with Light Microscopy, Institute of Science and Technology Austria, 2023.","ama":"Michalska JM. A versatile toolbox for the comprehensive analysis of nervous tissue organization with light microscopy. 2023. doi:<a href=\"https://doi.org/10.15479/at:ista:12470\">10.15479/at:ista:12470</a>","ieee":"J. M. Michalska, “A versatile toolbox for the comprehensive analysis of nervous tissue organization with light microscopy,” Institute of Science and Technology Austria, 2023.","apa":"Michalska, J. M. (2023). <i>A versatile toolbox for the comprehensive analysis of nervous tissue organization with light microscopy</i>. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/at:ista:12470\">https://doi.org/10.15479/at:ista:12470</a>"},"date_created":"2023-01-31T15:10:53Z","ec_funded":1,"related_material":{"record":[{"id":"11943","relation":"part_of_dissertation","status":"public"},{"status":"public","id":"11950","relation":"part_of_dissertation"}]},"degree_awarded":"PhD","file_date_updated":"2023-07-27T22:30:54Z","_id":"12470","acknowledged_ssus":[{"_id":"Bio"},{"_id":"LifeSc"},{"_id":"PreCl"},{"_id":"EM-Fac"},{"_id":"M-Shop"},{"_id":"ScienComp"}],"doi":"10.15479/at:ista:12470","author":[{"id":"443DB6DE-F248-11E8-B48F-1D18A9856A87","last_name":"Michalska","orcid":"0000-0003-3862-1235","full_name":"Michalska, Julia M","first_name":"Julia M"}],"publication_identifier":{"isbn":[" 978-3-99078-026-8"],"issn":["2663-337X"]},"month":"01","day":"09","oa_version":"Published Version","user_id":"8b945eb4-e2f2-11eb-945a-df72226e66a9","file":[{"file_size":41771714,"access_level":"open_access","content_type":"application/pdf","relation":"main_file","creator":"cchlebak","date_updated":"2023-07-27T22:30:54Z","date_created":"2023-01-31T15:11:42Z","file_name":"20230109_PhD_thesis_JM_final.pdf","file_id":"12471","checksum":"1a2306e5f59f52df598e7ecfadf921ac","embargo":"2023-07-09"},{"embargo_to":"open_access","creator":"cchlebak","relation":"source_file","access_level":"closed","content_type":"application/vnd.openxmlformats-officedocument.wordprocessingml.document","file_size":66983464,"checksum":"0bebbdee0773443959e1f6ab8caf281f","file_name":"20230109_PhD_thesis_JM_final.docx","file_id":"12472","date_updated":"2023-07-10T22:30:04Z","date_created":"2023-01-31T15:11:51Z"}],"alternative_title":["ISTA Thesis"],"type":"dissertation","status":"public","date_updated":"2023-08-31T12:26:58Z","oa":1,"article_processing_charge":"No","title":"A versatile toolbox for the comprehensive analysis of nervous tissue organization with light microscopy","has_accepted_license":"1","language":[{"iso":"eng"}]},{"publisher":"Institute of Science and Technology Austria","date_published":"2023-04-18T00:00:00Z","supervisor":[{"first_name":"Maximilian A","full_name":"Jösch, Maximilian A","id":"2BD278E6-F248-11E8-B48F-1D18A9856A87","last_name":"Jösch","orcid":"0000-0002-3937-1330"}],"page":"106","department":[{"_id":"MaJö"},{"_id":"GradSch"}],"project":[{"name":"International IST Doctoral Program","call_identifier":"H2020","grant_number":"665385","_id":"2564DBCA-B435-11E9-9278-68D0E5697425"}],"ddc":["570","571"],"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"},"abstract":[{"lang":"eng","text":"During navigation, animals can infer the structure of the environment by computing the optic flow cues elicited by their own movements, and subsequently use this information to instruct proper locomotor actions. These computations require a panoramic assessment of the visual environment in order to disambiguate similar sensory experiences that may require distinct behavioral responses. The estimation of the global motion patterns is therefore essential for successful navigation. Yet, our understanding of the algorithms and implementations that enable coherent panoramic visual perception remains scarce. Here I pursue this problem by dissecting the functional aspects of interneuronal communication in the lobula plate tangential cell network in Drosophila melanogaster. The results presented in the thesis demonstrate that the basis for effective interpretation of the optic flow in this circuit are stereotyped synaptic connections that mediate the formation of distinct subnetworks, each extracting a particular pattern of global motion. \r\nFirstly, I show that gap junctions are essential for a correct interpretation of binocular motion cues by horizontal motion-sensitive cells. HS cells form electrical synapses with contralateral H2 neurons that are involved in detecting yaw rotation and translation. I developed an FlpStop-mediated mutant of a gap junction protein ShakB that disrupts these electrical synapses. While the loss of electrical synapses does not affect the tuning of the direction selectivity in HS neurons, it severely alters their sensitivity to horizontal motion in the contralateral side. These physiological changes result in an inappropriate integration of binocular motion cues in walking animals. While wild-type flies form a binocular perception of visual motion by non-linear integration of monocular optic flow cues, the mutant flies sum the monocular inputs linearly. These results indicate that rather than averaging signals in neighboring neurons, gap-junctions operate in conjunction with chemical synapses to mediate complex non-linear optic flow computations.\r\nSecondly, I show that stochastic manipulation of neuronal activity in the lobula plate tangential cell network is a powerful approach to study the neuronal implementation of optic flow-based navigation in flies. Tangential neurons form multiple subnetworks, each mediating course-stabilizing response to a particular global pattern of visual motion. Application of genetic mosaic techniques can provide sparse optogenetic activation of HS cells in numerous combinations. These distinct combinations of activated neurons drive an array of distinct behavioral responses, providing important insights into how visuomotor transformation is performed in the lobula plate tangential cell network. This approach can be complemented by stochastic silencing of tangential neurons, enabling direct assessment of the functional role of individual tangential neurons in the processing of specific visual motion patterns.\r\n\tTaken together, the findings presented in this thesis suggest that establishing specific activity patterns of tangential cells via stereotyped synaptic connectivity is a key to efficient optic flow-based navigation in Drosophila melanogaster."}],"publication_status":"published","doi":"10.15479/at:ista:12826","file_date_updated":"2023-04-20T09:26:51Z","_id":"12826","acknowledged_ssus":[{"_id":"Bio"},{"_id":"LifeSc"}],"ec_funded":1,"degree_awarded":"PhD","year":"2023","citation":{"mla":"Pokusaeva, Victoria. <i>Neural Control of Optic Flow-Based Navigation in Drosophila Melanogaster</i>. Institute of Science and Technology Austria, 2023, doi:<a href=\"https://doi.org/10.15479/at:ista:12826\">10.15479/at:ista:12826</a>.","chicago":"Pokusaeva, Victoria. “Neural Control of Optic Flow-Based Navigation in Drosophila Melanogaster.” Institute of Science and Technology Austria, 2023. <a href=\"https://doi.org/10.15479/at:ista:12826\">https://doi.org/10.15479/at:ista:12826</a>.","ista":"Pokusaeva V. 2023. Neural control of optic flow-based navigation in Drosophila melanogaster. Institute of Science and Technology Austria.","ieee":"V. Pokusaeva, “Neural control of optic flow-based navigation in Drosophila melanogaster,” Institute of Science and Technology Austria, 2023.","ama":"Pokusaeva V. Neural control of optic flow-based navigation in Drosophila melanogaster. 2023. doi:<a href=\"https://doi.org/10.15479/at:ista:12826\">10.15479/at:ista:12826</a>","short":"V. Pokusaeva, Neural Control of Optic Flow-Based Navigation in Drosophila Melanogaster, Institute of Science and Technology Austria, 2023.","apa":"Pokusaeva, V. (2023). <i>Neural control of optic flow-based navigation in Drosophila melanogaster</i>. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/at:ista:12826\">https://doi.org/10.15479/at:ista:12826</a>"},"date_created":"2023-04-14T14:56:04Z","alternative_title":["ISTA Thesis"],"type":"dissertation","status":"public","publication_identifier":{"issn":["2663 - 337X"]},"month":"04","day":"18","oa_version":"Published Version","file":[{"creator":"vpokusae","file_size":14507243,"relation":"source_file","access_level":"closed","content_type":"application/vnd.openxmlformats-officedocument.wordprocessingml.document","file_name":"Thesis_Pokusaeva.docx","checksum":"5f589a9af025f7eeebfd0c186209913e","file_id":"12857","date_created":"2023-04-20T09:14:38Z","date_updated":"2023-04-20T09:26:51Z"},{"creator":"vpokusae","file_size":10090711,"content_type":"application/pdf","access_level":"open_access","relation":"main_file","success":1,"file_name":"Thesis_Pokusaeva.pdf","checksum":"bbeed76db45a996b4c91a9abe12ce0ec","file_id":"12858","date_created":"2023-04-20T09:14:44Z","date_updated":"2023-04-20T09:14:44Z"}],"user_id":"8b945eb4-e2f2-11eb-945a-df72226e66a9","author":[{"first_name":"Victoria","full_name":"Pokusaeva, Victoria","id":"3184041C-F248-11E8-B48F-1D18A9856A87","last_name":"Pokusaeva","orcid":"0000-0001-7660-444X"}],"language":[{"iso":"eng"}],"has_accepted_license":"1","oa":1,"date_updated":"2023-06-23T09:47:36Z","article_processing_charge":"No","title":"Neural control of optic flow-based navigation in Drosophila melanogaster"},{"doi":"10.15479/at:ista:12885","file_date_updated":"2023-05-02T07:43:18Z","_id":"12885","acknowledged_ssus":[{"_id":"EM-Fac"},{"_id":"NanoFab"}],"ec_funded":1,"degree_awarded":"PhD","related_material":{"record":[{"status":"public","id":"10806","relation":"part_of_dissertation"},{"status":"public","relation":"part_of_dissertation","id":"10042"},{"id":"12237","relation":"part_of_dissertation","status":"public"},{"relation":"part_of_dissertation","id":"9118","status":"public"},{"status":"public","id":"10123","relation":"part_of_dissertation"}]},"year":"2023","date_created":"2023-05-02T07:58:57Z","citation":{"apa":"Calcabrini, M. (2023). <i>Nanoparticle-based semiconductor solids: From synthesis to consolidation</i>. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/at:ista:12885\">https://doi.org/10.15479/at:ista:12885</a>","ama":"Calcabrini M. Nanoparticle-based semiconductor solids: From synthesis to consolidation. 2023. doi:<a href=\"https://doi.org/10.15479/at:ista:12885\">10.15479/at:ista:12885</a>","ieee":"M. Calcabrini, “Nanoparticle-based semiconductor solids: From synthesis to consolidation,” Institute of Science and Technology Austria, 2023.","short":"M. Calcabrini, Nanoparticle-Based Semiconductor Solids: From Synthesis to Consolidation, Institute of Science and Technology Austria, 2023.","ista":"Calcabrini M. 2023. Nanoparticle-based semiconductor solids: From synthesis to consolidation. Institute of Science and Technology Austria.","chicago":"Calcabrini, Mariano. “Nanoparticle-Based Semiconductor Solids: From Synthesis to Consolidation.” Institute of Science and Technology Austria, 2023. <a href=\"https://doi.org/10.15479/at:ista:12885\">https://doi.org/10.15479/at:ista:12885</a>.","mla":"Calcabrini, Mariano. <i>Nanoparticle-Based Semiconductor Solids: From Synthesis to Consolidation</i>. Institute of Science and Technology Austria, 2023, doi:<a href=\"https://doi.org/10.15479/at:ista:12885\">10.15479/at:ista:12885</a>."},"publisher":"Institute of Science and Technology Austria","date_published":"2023-04-28T00:00:00Z","supervisor":[{"full_name":"Ibáñez, Maria","first_name":"Maria","orcid":"0000-0001-5013-2843","last_name":"Ibáñez","id":"43C61214-F248-11E8-B48F-1D18A9856A87"}],"page":"82","department":[{"_id":"GradSch"},{"_id":"MaIb"}],"project":[{"_id":"2564DBCA-B435-11E9-9278-68D0E5697425","grant_number":"665385","call_identifier":"H2020","name":"International IST Doctoral Program"}],"ddc":["546","541"],"abstract":[{"text":"High-performance semiconductors rely upon precise control of heat and charge transport. This can be achieved by precisely engineering defects in polycrystalline solids. There are multiple approaches to preparing such polycrystalline semiconductors, and the transformation of solution-processed colloidal nanoparticles is appealing because colloidal nanoparticles combine low cost with structural and compositional tunability along with rich surface chemistry. However, the multiple processes from nanoparticle synthesis to the final bulk nanocomposites are very complex. They involve nanoparticle purification, post-synthetic modifications, and finally consolidation (thermal treatments and densification). All these properties dictate the final material’s composition and microstructure, ultimately affecting its functional properties. This thesis explores the synthesis, surface chemistry and consolidation of colloidal semiconductor nanoparticles into dense solids. In particular, the transformations that take place during these processes, and their effect on the material’s transport properties are evaluated. ","lang":"eng"}],"publication_status":"published","language":[{"iso":"eng"}],"has_accepted_license":"1","date_updated":"2023-08-14T07:25:26Z","oa":1,"article_processing_charge":"No","title":"Nanoparticle-based semiconductor solids: From synthesis to consolidation","alternative_title":["ISTA Thesis"],"type":"dissertation","status":"public","publication_identifier":{"isbn":["978-3-99078-028-2"],"issn":["2663-337X"]},"month":"04","oa_version":"Published Version","day":"28","user_id":"8b945eb4-e2f2-11eb-945a-df72226e66a9","file":[{"file_name":"Thesis_Calcabrini.docx","checksum":"9347b0e09425f56fdcede5d3528404dc","file_id":"12887","date_created":"2023-05-02T07:43:18Z","date_updated":"2023-05-02T07:43:18Z","creator":"mcalcabr","relation":"source_file","file_size":99627036,"access_level":"closed","content_type":"application/vnd.openxmlformats-officedocument.wordprocessingml.document"},{"content_type":"application/pdf","relation":"main_file","access_level":"open_access","file_size":8742220,"creator":"mcalcabr","date_created":"2023-05-02T07:42:45Z","date_updated":"2023-05-02T07:42:45Z","success":1,"checksum":"2d188b76621086cd384f0b9264b0a576","file_name":"Thesis_Calcabrini_pdfa.pdf","file_id":"12888"}],"author":[{"first_name":"Mariano","full_name":"Calcabrini, Mariano","orcid":"0000-0003-4566-5877","last_name":"Calcabrini","id":"45D7531A-F248-11E8-B48F-1D18A9856A87"}]},{"publication_status":"published","abstract":[{"lang":"eng","text":"Pattern formation is of great importance for its contribution across different biological behaviours. During developmental processes for example, patterns of chemical gradients are\r\nestablished to determine cell fate and complex tissue patterns emerge to define structures such\r\nas limbs and vascular networks. Patterns are also seen in collectively migrating groups, for\r\ninstance traveling waves of density emerging in moving animal flocks as well as collectively migrating cells and tissues. To what extent these biological patterns arise spontaneously through\r\nthe local interaction of individual constituents or are dictated by higher level instructions is\r\nstill an open question however there is evidence for the involvement of both types of process.\r\nWhere patterns arise spontaneously there is a long standing interest in how far the interplay\r\nof mechanics, e.g. force generation and deformation, and chemistry, e.g. gene regulation\r\nand signaling, contributes to the behaviour. This is because many systems are able to both\r\nchemically regulate mechanical force production and chemically sense mechanical deformation,\r\nforming mechano-chemical feedback loops which can potentially become unstable towards\r\nspatio and/or temporal patterning.\r\nWe work with experimental collaborators to investigate the possibility that this type of\r\ninteraction drives pattern formation in biological systems at different scales. We focus first on\r\ntissue-level ERK-density waves observed during the wound healing response across different\r\nsystems where many previous studies have proposed that patterns depend on polarized cell\r\nmigration and arise from a mechanical flocking-like mechanism. By combining theory with\r\nmechanical and optogenetic perturbation experiments on in vitro monolayers we instead find\r\nevidence for mechanochemical pattern formation involving only scalar bilateral feedbacks\r\nbetween ERK signaling and cell contraction. We perform further modeling and experiment\r\nto study how this instability couples with polar cell migration in order to produce a robust\r\nand efficient wound healing response. In a following chapter we implement ERK-density\r\ncoupling and cell migration in a 2D active vertex model to investigate the interaction of\r\nERK-density patterning with different tissue rheologies and find that the spatio-temporal\r\ndynamics are able to both locally and globally fluidize a tissue across the solid-fluid glass\r\ntransition. In a last chapter we move towards lower spatial scales in the context of subcellular\r\npatterning of the cell cytoskeleton where we investigate the transition between phases of\r\nspatially homogeneous temporal oscillations and chaotic spatio-temporal patterning in the\r\ndynamics of myosin and ROCK activities (a motor component of the actomyosin cytoskeleton\r\nand its activator). Experimental evidence supports an intrinsic chemical oscillator which we\r\nencode in a reaction model and couple to a contractile active gel description of the cell cortex.\r\nThe model exhibits phases of chemical oscillations and contractile spatial patterning which\r\nreproduce many features of the dynamics seen in Drosophila oocyte epithelia in vivo. However,\r\nadditional pharmacological perturbations to inhibit myosin contractility leaves the role of\r\ncontractile instability unclear. We discuss alternative hypotheses and investigate the possibility\r\nof reaction-diffusion instability."}],"ddc":["530"],"tmp":{"image":"/images/cc_by_nc_sa.png","legal_code_url":"https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode","name":"Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)","short":"CC BY-NC-SA (4.0)"},"project":[{"grant_number":"665385","_id":"2564DBCA-B435-11E9-9278-68D0E5697425","call_identifier":"H2020","name":"International IST Doctoral Program"}],"page":"146","department":[{"_id":"GradSch"},{"_id":"EdHa"}],"publisher":"Institute of Science and Technology Austria","supervisor":[{"first_name":"Edouard B","full_name":"Hannezo, Edouard B","last_name":"Hannezo","id":"3A9DB764-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-6005-1561"}],"date_published":"2023-05-17T00:00:00Z","citation":{"apa":"Boocock, D. R. (2023). <i>Mechanochemical pattern formation across biological scales</i>. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/at:ista:12964\">https://doi.org/10.15479/at:ista:12964</a>","ista":"Boocock DR. 2023. Mechanochemical pattern formation across biological scales. Institute of Science and Technology Austria.","chicago":"Boocock, Daniel R. “Mechanochemical Pattern Formation across Biological Scales.” Institute of Science and Technology Austria, 2023. <a href=\"https://doi.org/10.15479/at:ista:12964\">https://doi.org/10.15479/at:ista:12964</a>.","mla":"Boocock, Daniel R. <i>Mechanochemical Pattern Formation across Biological Scales</i>. Institute of Science and Technology Austria, 2023, doi:<a href=\"https://doi.org/10.15479/at:ista:12964\">10.15479/at:ista:12964</a>.","ieee":"D. R. Boocock, “Mechanochemical pattern formation across biological scales,” Institute of Science and Technology Austria, 2023.","ama":"Boocock DR. Mechanochemical pattern formation across biological scales. 2023. doi:<a href=\"https://doi.org/10.15479/at:ista:12964\">10.15479/at:ista:12964</a>","short":"D.R. Boocock, Mechanochemical Pattern Formation across Biological Scales, Institute of Science and Technology Austria, 2023."},"date_created":"2023-05-15T14:52:36Z","year":"2023","ec_funded":1,"related_material":{"record":[{"status":"public","relation":"part_of_dissertation","id":"8602"}]},"degree_awarded":"PhD","file_date_updated":"2023-05-19T07:04:25Z","_id":"12964","doi":"10.15479/at:ista:12964","author":[{"first_name":"Daniel R","full_name":"Boocock, Daniel R","orcid":"0000-0002-1585-2631","last_name":"Boocock","id":"453AF628-F248-11E8-B48F-1D18A9856A87"}],"oa_version":"Published Version","day":"17","file":[{"embargo":"2024-05-17","checksum":"d51240675fc6dc0e3f5dc0c902695d3a","file_name":"thesis_boocock.pdf","file_id":"12988","date_created":"2023-05-17T13:39:54Z","date_updated":"2023-05-19T07:04:25Z","creator":"dboocock","embargo_to":"open_access","content_type":"application/pdf","access_level":"closed","relation":"main_file","file_size":40414730},{"creator":"dboocock","content_type":"application/zip","file_size":34338567,"relation":"source_file","access_level":"closed","file_id":"12989","checksum":"581a2313ffeb40fe77e8a122a25a7795","file_name":"thesis_boocock.zip","date_created":"2023-05-17T13:39:53Z","date_updated":"2023-05-17T14:35:13Z"}],"user_id":"8b945eb4-e2f2-11eb-945a-df72226e66a9","publication_identifier":{"isbn":["978-3-99078-032-9"],"issn":["2663-337X"]},"month":"05","alternative_title":["ISTA Thesis"],"type":"dissertation","status":"public","title":"Mechanochemical pattern formation across biological scales","date_updated":"2023-08-04T11:02:40Z","article_processing_charge":"No","has_accepted_license":"1","language":[{"iso":"eng"}]},{"alternative_title":["ISTA Thesis"],"type":"dissertation","status":"public","author":[{"id":"32D78294-F248-11E8-B48F-1D18A9856A87","last_name":"Peste","full_name":"Peste, Elena-Alexandra","first_name":"Elena-Alexandra"}],"publication_identifier":{"issn":["2663-337X"]},"month":"05","day":"23","oa_version":"Published Version","file":[{"creator":"epeste","access_level":"open_access","relation":"main_file","file_size":2152072,"content_type":"application/pdf","success":1,"file_name":"PhD_Thesis_Alexandra_Peste_final.pdf","file_id":"13087","checksum":"6b3354968403cb9d48cc5a83611fb571","date_created":"2023-05-24T16:11:16Z","date_updated":"2023-05-24T16:11:16Z"},{"relation":"source_file","access_level":"closed","content_type":"application/zip","file_size":1658293,"creator":"epeste","date_created":"2023-05-24T16:12:59Z","date_updated":"2023-05-24T16:12:59Z","checksum":"8d0df94bbcf4db72c991f22503b3fd60","file_name":"PhD_Thesis_APeste.zip","file_id":"13088"}],"user_id":"8b945eb4-e2f2-11eb-945a-df72226e66a9","language":[{"iso":"eng"}],"oa":1,"date_updated":"2023-08-04T10:33:27Z","article_processing_charge":"No","title":"Efficiency and generalization of sparse neural networks","has_accepted_license":"1","project":[{"name":"International IST Doctoral Program","call_identifier":"H2020","grant_number":"665385","_id":"2564DBCA-B435-11E9-9278-68D0E5697425"},{"name":"Elastic Coordination for Scalable Machine Learning","call_identifier":"H2020","_id":"268A44D6-B435-11E9-9278-68D0E5697425","grant_number":"805223"}],"publisher":"Institute of Science and Technology Austria","date_published":"2023-05-23T00:00:00Z","supervisor":[{"id":"40C20FD2-F248-11E8-B48F-1D18A9856A87","last_name":"Lampert","orcid":"0000-0001-8622-7887","first_name":"Christoph","full_name":"Lampert, Christoph"},{"orcid":"0000-0003-3650-940X","id":"4A899BFC-F248-11E8-B48F-1D18A9856A87","last_name":"Alistarh","first_name":"Dan-Adrian","full_name":"Alistarh, Dan-Adrian"}],"department":[{"_id":"GradSch"},{"_id":"DaAl"},{"_id":"ChLa"}],"page":"147","publication_status":"published","ddc":["000"],"abstract":[{"lang":"eng","text":"Deep learning has become an integral part of a large number of important applications, and many of the recent breakthroughs have been enabled by the ability to train very large models, capable to capture complex patterns and relationships from the data. At the same time, the massive sizes of modern deep learning models have made their deployment to smaller devices more challenging; this is particularly important, as in many applications the users rely on accurate deep learning predictions, but they only have access to devices with limited memory and compute power. One solution to this problem is to prune neural networks, by setting as many of their parameters as possible to zero, to obtain accurate sparse models with lower memory footprint. Despite the great research progress in obtaining sparse models that preserve accuracy, while satisfying memory and computational constraints, there are still many challenges associated with efficiently training sparse models, as well as understanding their generalization properties.\r\n\r\nThe focus of this thesis is to investigate how the training process of sparse models can be made more efficient, and to understand the differences between sparse and dense models in terms of how well they can generalize to changes in the data distribution. We first study a method for co-training sparse and dense models, at a lower cost compared to regular training. With our method we can obtain very accurate sparse networks, and dense models that can recover the baseline accuracy. Furthermore, we are able to more easily analyze the differences, at prediction level, between the sparse-dense model pairs. Next, we investigate the generalization properties of sparse neural networks in more detail, by studying how well different sparse models trained on a larger task can adapt to smaller, more specialized tasks, in a transfer learning scenario. Our analysis across multiple pruning methods and sparsity levels reveals that sparse models provide features that can transfer similarly to or better than the dense baseline. However, the choice of the pruning method plays an important role, and can influence the results when the features are fixed (linear finetuning), or when they are allowed to adapt to the new task (full finetuning). Using sparse models with fixed masks for finetuning on new tasks has an important practical advantage, as it enables training neural networks on smaller devices. However, one drawback of current pruning methods is that the entire training cycle has to be repeated to obtain the initial sparse model, for every sparsity target; in consequence, the entire training process is costly and also multiple models need to be stored. In the last part of the thesis we propose a method that can train accurate dense models that are compressible in a single step, to multiple sparsity levels, without additional finetuning. Our method results in sparse models that can be competitive with existing pruning methods, and which can also successfully generalize to new tasks."}],"file_date_updated":"2023-05-24T16:12:59Z","_id":"13074","acknowledged_ssus":[{"_id":"ScienComp"}],"doi":"10.15479/at:ista:13074","year":"2023","citation":{"mla":"Peste, Elena-Alexandra. <i>Efficiency and Generalization of Sparse Neural Networks</i>. Institute of Science and Technology Austria, 2023, doi:<a href=\"https://doi.org/10.15479/at:ista:13074\">10.15479/at:ista:13074</a>.","chicago":"Peste, Elena-Alexandra. “Efficiency and Generalization of Sparse Neural Networks.” Institute of Science and Technology Austria, 2023. <a href=\"https://doi.org/10.15479/at:ista:13074\">https://doi.org/10.15479/at:ista:13074</a>.","ista":"Peste E-A. 2023. Efficiency and generalization of sparse neural networks. Institute of Science and Technology Austria.","short":"E.-A. Peste, Efficiency and Generalization of Sparse Neural Networks, Institute of Science and Technology Austria, 2023.","ama":"Peste E-A. Efficiency and generalization of sparse neural networks. 2023. doi:<a href=\"https://doi.org/10.15479/at:ista:13074\">10.15479/at:ista:13074</a>","ieee":"E.-A. Peste, “Efficiency and generalization of sparse neural networks,” Institute of Science and Technology Austria, 2023.","apa":"Peste, E.-A. (2023). <i>Efficiency and generalization of sparse neural networks</i>. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/at:ista:13074\">https://doi.org/10.15479/at:ista:13074</a>"},"date_created":"2023-05-23T17:07:53Z","ec_funded":1,"degree_awarded":"PhD","related_material":{"record":[{"status":"public","id":"11458","relation":"part_of_dissertation"},{"relation":"part_of_dissertation","id":"13053","status":"public"},{"status":"public","id":"12299","relation":"part_of_dissertation"}]}},{"date_published":"2023-08-04T00:00:00Z","publisher":"Institute of Science and Technology Austria","department":[{"_id":"JoDa"},{"_id":"SaSi"},{"_id":"GaNo"},{"_id":"PeJo"},{"_id":"Bio"},{"_id":"RySh"}],"project":[{"_id":"265CB4D0-B435-11E9-9278-68D0E5697425","grant_number":"I03600","call_identifier":"FWF","name":"Optical control of synaptic function via adhesion molecules"},{"grant_number":"W1232-B24","_id":"26AA4EF2-B435-11E9-9278-68D0E5697425","call_identifier":"FWF","name":"Molecular Drug Targets"},{"_id":"25C5A090-B435-11E9-9278-68D0E5697425","grant_number":"Z00312","name":"The Wittgenstein Prize","call_identifier":"FWF"},{"_id":"23889792-32DE-11EA-91FC-C7463DDC885E","name":"High content imaging to decode human immune cell interactions in health and allergic disease"},{"name":"Probing the Reversibility of Autism Spectrum Disorders by Employing in vivo and in vitro Models","call_identifier":"H2020","grant_number":"715508","_id":"25444568-B435-11E9-9278-68D0E5697425"},{"call_identifier":"H2020","name":"Biophysics and circuit function of a giant cortical glumatergic synapse","grant_number":"692692","_id":"25B7EB9E-B435-11E9-9278-68D0E5697425"},{"call_identifier":"H2020","name":"International IST Doctoral Program","grant_number":"665385","_id":"2564DBCA-B435-11E9-9278-68D0E5697425"},{"grant_number":"101026635","_id":"fc2be41b-9c52-11eb-aca3-faa90aa144e9","name":"Synaptic computations of the hippocampal CA3 circuitry","call_identifier":"H2020"}],"tmp":{"image":"/images/cc_by_nc_sa.png","legal_code_url":"https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode","name":"Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)","short":"CC BY-NC-SA (4.0)"},"ddc":["610"],"abstract":[{"lang":"eng","text":"Mapping the complex and dense arrangement of cells and their connectivity in brain tissue demands nanoscale spatial resolution imaging. Super-resolution optical microscopy excels at visualizing specific molecules and individual cells but fails to provide tissue context. Here, we developed Comprehensive Analysis of Tissues across Scales (CATS), a technology to densely map brain tissue architecture from millimeter regional to nanometer synaptic scales in diverse chemically fixed brain preparations, including rodent and human. CATS uses fixation-compatible extracellular labeling and optical imaging, including stimulated emission depletion or expansion microscopy, to comprehensively delineate cellular structures. It enables three-dimensional reconstruction of single synapses and mapping of synaptic connectivity by identification and analysis of putative synaptic cleft regions. Applying CATS to the mouse hippocampal mossy fiber circuitry, we reconstructed and quantified the synaptic input and output structure of identified neurons. We furthermore demonstrate applicability to clinically derived human tissue samples, including formalin-fixed paraffin-embedded routine diagnostic specimens, for visualizing the cellular architecture of brain tissue in health and disease."}],"contributor":[{"first_name":"Julia M","last_name":"Michalska","id":"443DB6DE-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Julia","last_name":"Lyudchik","id":"46E28B80-F248-11E8-B48F-1D18A9856A87"},{"orcid":"0000-0002-2340-7431","id":"39BDC62C-F248-11E8-B48F-1D18A9856A87","last_name":"Velicky","first_name":"Philipp"},{"first_name":"Hana","id":"ee3cb6ca-ec98-11ea-ae11-ff703e2254ed","last_name":"Stefanickova"},{"first_name":"Jake","id":"63836096-4690-11EA-BD4E-32803DDC885E","last_name":"Watson","orcid":"0000-0002-8698-3823"},{"first_name":"Alban","last_name":"Cenameri","id":"9ac8f577-2357-11eb-997a-e566c5550886"},{"first_name":"Christoph M","last_name":"Sommer","id":"4DF26D8C-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-1216-9105"},{"first_name":"Nicole","id":"4CD6AAC6-F248-11E8-B48F-1D18A9856A87","last_name":"Amberg","orcid":"0000-0002-3183-8207"},{"first_name":"Alessandro","id":"41CB84B2-F248-11E8-B48F-1D18A9856A87","last_name":"Venturino","orcid":"0000-0003-2356-9403"},{"first_name":"Karl","last_name":"Roessler"},{"first_name":"Thomas","last_name":"Czech"},{"first_name":"Romana","last_name":"Höftberger"},{"first_name":"Sandra","last_name":"Siegert","id":"36ACD32E-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-8635-0877"},{"last_name":"Novarino","id":"3E57A680-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-7673-7178","first_name":"Gaia"},{"first_name":"Peter M","orcid":"0000-0001-5001-4804","last_name":"Jonas","id":"353C1B58-F248-11E8-B48F-1D18A9856A87"}],"doi":"10.15479/AT:ISTA:13126","_id":"13126","file_date_updated":"2023-08-04T13:19:47Z","acknowledged_ssus":[{"_id":"ScienComp"},{"_id":"Bio"},{"_id":"PreCl"},{"_id":"LifeSc"},{"_id":"M-Shop"},{"_id":"E-Lib"}],"related_material":{"record":[{"id":"14257","relation":"used_in_publication","status":"public"}],"link":[{"relation":"research_data","url":"https://pub.ista.ac.at/group_danzl/data/CATS/","description":"Original data for Fig. 5d, Fig. 5d (N2V) and Fig. 5f-i, provided via an external link due to the large size (>10GB) of the datasets. "}]},"ec_funded":1,"year":"2023","acknowledgement":"We thank Jakob Vorlaufer, Nathalie Agudelo-Dueñas, Wiebke Jahr, Andreas Wartak for microscope maintenance and troubleshooting, Caroline Kreuzinger, Anna Freeman, and Irene Erber for technical assistance and Matthias Tomschik for support with obtaining human samples. We gratefully acknowledge Eder Miguel for setting up webKnossos and Marek Šuplata for computational support and hardware control. We are grateful to Ryuichi Shigemoto and Bernd Bickel for generous support, and Michael Sixt and Scott Boyd (Stanford University) for discussions and critical reading of the manuscript. PSD95-HaloTag mice were kindly provided by Seth Grant (University of Edinburgh). We acknowledge expert support by IST Austria’s scientific computing, imaging and optics, preclinical, and lab support facilities, and by the Library and Miba machine shop.\r\nWe gratefully acknowledge funding by the following sources: \r\nAustrian Science Fund (FWF) grant I3600-B27 (JGD)\r\nAustrian Science Fund (FWF) grant DK W1232 (JGD, JMM)\r\nAustrian Science Fund (FWF) grant Z 312-B27, Wittgenstein award (PJ)\r\nAustrian Science Funds (FWF) projects I4685-B, I6565-B (SYNABS) and DOC 33-B27 (RH)\r\nGesellschaft für Forschungsförderung NÖ (NFB) grant LSC18-022 (JGD)\r\nEuropean Union’s Horizon 2020 research and innovation programme, European Research Council (ERC) grant 715508 – REVERSEAUTISM (GN)\r\nEuropean Union’s Horizon 2020 research and innovation programme, European Research Council (ERC) grant 692692 – GIANTSYN (PJ)\r\nMarie Skłodowska-Curie Actions Fellowship GA no. 665385 under the EU Horizon 2020 program (JMM, JL)\r\nMarie Skłodowska-Curie Actions Individual Fellowship 101026635 under the EU Horizon 2020 program (JFW)","citation":{"apa":"Danzl, J. G. (2023). Research data for the publication “Imaging brain tissue architecture across millimeter to nanometer scales.” Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/AT:ISTA:13126\">https://doi.org/10.15479/AT:ISTA:13126</a>","short":"J.G. Danzl, (2023).","ieee":"J. G. Danzl, “Research data for the publication ‘Imaging brain tissue architecture across millimeter to nanometer scales.’” Institute of Science and Technology Austria, 2023.","ama":"Danzl JG. Research data for the publication “Imaging brain tissue architecture across millimeter to nanometer scales.” 2023. doi:<a href=\"https://doi.org/10.15479/AT:ISTA:13126\">10.15479/AT:ISTA:13126</a>","ista":"Danzl JG. 2023. Research data for the publication ‘Imaging brain tissue architecture across millimeter to nanometer scales’, Institute of Science and Technology Austria, <a href=\"https://doi.org/10.15479/AT:ISTA:13126\">10.15479/AT:ISTA:13126</a>.","mla":"Danzl, Johann G. <i>Research Data for the Publication “Imaging Brain Tissue Architecture across Millimeter to Nanometer Scales.”</i> Institute of Science and Technology Austria, 2023, doi:<a href=\"https://doi.org/10.15479/AT:ISTA:13126\">10.15479/AT:ISTA:13126</a>.","chicago":"Danzl, Johann G. “Research Data for the Publication ‘Imaging Brain Tissue Architecture across Millimeter to Nanometer Scales.’” Institute of Science and Technology Austria, 2023. <a 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A., Lechner, M., &#38; Zikelic, D. (2023). A learner-verifier framework for neural network controllers and certificates of stochastic systems. In <i>Tools and Algorithms for the Construction and Analysis of Systems </i> (Vol. 13993, pp. 3–25). Paris, France: Springer Nature. <a href=\"https://doi.org/10.1007/978-3-031-30823-9_1\">https://doi.org/10.1007/978-3-031-30823-9_1</a>","ista":"Chatterjee K, Henzinger TA, Lechner M, Zikelic D. 2023. A learner-verifier framework for neural network controllers and certificates of stochastic systems. Tools and Algorithms for the Construction and Analysis of Systems . TACAS: Tools and Algorithms for the Construction and Analysis of Systems, LNCS, vol. 13993, 3–25.","mla":"Chatterjee, Krishnendu, et al. “A Learner-Verifier Framework for Neural Network Controllers and Certificates of Stochastic Systems.” <i>Tools and Algorithms for the Construction and Analysis of Systems </i>, vol. 13993, Springer Nature, 2023, pp. 3–25, doi:<a href=\"https://doi.org/10.1007/978-3-031-30823-9_1\">10.1007/978-3-031-30823-9_1</a>.","chicago":"Chatterjee, Krishnendu, Thomas A Henzinger, Mathias Lechner, and Dorde Zikelic. “A Learner-Verifier Framework for Neural Network Controllers and Certificates of Stochastic Systems.” In <i>Tools and Algorithms for the Construction and Analysis of Systems </i>, 13993:3–25. Springer Nature, 2023. <a href=\"https://doi.org/10.1007/978-3-031-30823-9_1\">https://doi.org/10.1007/978-3-031-30823-9_1</a>.","ama":"Chatterjee K, Henzinger TA, Lechner M, Zikelic D. A learner-verifier framework for neural network controllers and certificates of stochastic systems. In: <i>Tools and Algorithms for the Construction and Analysis of Systems </i>. Vol 13993. Springer Nature; 2023:3-25. doi:<a href=\"https://doi.org/10.1007/978-3-031-30823-9_1\">10.1007/978-3-031-30823-9_1</a>","ieee":"K. Chatterjee, T. A. Henzinger, M. Lechner, and D. Zikelic, “A learner-verifier framework for neural network controllers and certificates of stochastic systems,” in <i>Tools and Algorithms for the Construction and Analysis of Systems </i>, Paris, France, 2023, vol. 13993, pp. 3–25.","short":"K. Chatterjee, T.A. Henzinger, M. Lechner, D. Zikelic, in:, Tools and Algorithms for the Construction and Analysis of Systems , Springer Nature, 2023, pp. 3–25."},"doi":"10.1007/978-3-031-30823-9_1","_id":"13142","file_date_updated":"2023-06-19T08:29:30Z","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"},"ddc":["000"],"abstract":[{"text":"Reinforcement learning has received much attention for learning controllers of deterministic systems. We consider a learner-verifier framework for stochastic control systems and survey recent methods that formally guarantee a conjunction of reachability and safety properties. Given a property and a lower bound on the probability of the property being satisfied, our framework jointly learns a control policy and a formal certificate to ensure the satisfaction of the property with a desired probability threshold. Both the control policy and the formal certificate are continuous functions from states to reals, which are learned as parameterized neural networks. While in the deterministic case, the certificates are invariant and barrier functions for safety, or Lyapunov and ranking functions for liveness, in the stochastic case the certificates are supermartingales. For certificate verification, we use interval arithmetic abstract interpretation to bound the expected values of neural network functions.","lang":"eng"}],"publication_status":"published","date_published":"2023-04-22T00:00:00Z","publisher":"Springer Nature","quality_controlled":"1","volume":13993,"department":[{"_id":"KrCh"},{"_id":"ToHe"}],"page":"3-25","project":[{"_id":"0599E47C-7A3F-11EA-A408-12923DDC885E","grant_number":"863818","name":"Formal Methods for Stochastic Models: Algorithms and Applications","call_identifier":"H2020"},{"name":"International IST Doctoral Program","call_identifier":"H2020","_id":"2564DBCA-B435-11E9-9278-68D0E5697425","grant_number":"665385"}],"scopus_import":"1","has_accepted_license":"1","intvolume":"     13993","article_processing_charge":"No","date_updated":"2025-07-14T09:09:52Z","oa":1,"title":"A learner-verifier framework for neural network controllers and certificates of stochastic systems","publication":"Tools and Algorithms for the Construction and Analysis of Systems ","language":[{"iso":"eng"}],"publication_identifier":{"isbn":["9783031308222"],"eissn":["1611-3349"],"issn":["0302-9743"]},"month":"04","conference":{"end_date":"2023-04-27","location":"Paris, France","start_date":"2023-04-22","name":"TACAS: Tools and Algorithms for the Construction and Analysis of Systems"},"file":[{"relation":"main_file","file_size":528455,"access_level":"open_access","content_type":"application/pdf","creator":"dernst","date_created":"2023-06-19T08:29:30Z","date_updated":"2023-06-19T08:29:30Z","success":1,"file_name":"2023_LNCS_Chatterjee.pdf","checksum":"3d8a8bb24d211bc83360dfc2fd744307","file_id":"13150"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","oa_version":"Published Version","day":"22","author":[{"last_name":"Chatterjee","id":"2E5DCA20-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-4561-241X","full_name":"Chatterjee, Krishnendu","first_name":"Krishnendu"},{"id":"40876CD8-F248-11E8-B48F-1D18A9856A87","last_name":"Henzinger","orcid":"0000-0002-2985-7724","full_name":"Henzinger, Thomas A","first_name":"Thomas A"},{"id":"3DC22916-F248-11E8-B48F-1D18A9856A87","last_name":"Lechner","first_name":"Mathias","full_name":"Lechner, Mathias"},{"full_name":"Zikelic, Dorde","first_name":"Dorde","id":"294AA7A6-F248-11E8-B48F-1D18A9856A87","last_name":"Zikelic","orcid":"0000-0002-4681-1699"}],"status":"public","type":"conference","alternative_title":["LNCS"]},{"external_id":{"pmid":["37429995"],"isi":["001025621500001"]},"abstract":[{"lang":"eng","text":"Three-dimensional (3D) reconstruction of living brain tissue down to an individual synapse level would create opportunities for decoding the dynamics and structure–function relationships of the brain’s complex and dense information processing network; however, this has been hindered by insufficient 3D resolution, inadequate signal-to-noise ratio and prohibitive light burden in optical imaging, whereas electron microscopy is inherently static. Here we solved these challenges by developing an integrated optical/machine-learning technology, LIONESS (live information-optimized nanoscopy enabling saturated segmentation). This leverages optical modifications to stimulated emission depletion microscopy in comprehensively, extracellularly labeled tissue and previous information on sample structure via machine learning to simultaneously achieve isotropic super-resolution, high signal-to-noise ratio and compatibility with living tissue. This allows dense deep-learning-based instance segmentation and 3D reconstruction at a synapse level, incorporating molecular, activity and morphodynamic information. LIONESS opens up avenues for studying the dynamic functional (nano-)architecture of living brain tissue."}],"publication_status":"published","department":[{"_id":"PeJo"},{"_id":"GaNo"},{"_id":"BeBi"},{"_id":"JoDa"},{"_id":"Bio"}],"page":"1256-1265","volume":20,"quality_controlled":"1","publisher":"Springer Nature","date_published":"2023-08-01T00:00:00Z","project":[{"grant_number":"I03600","_id":"265CB4D0-B435-11E9-9278-68D0E5697425","name":"Optical control of synaptic function via adhesion molecules","call_identifier":"FWF"},{"name":"Molecular Drug Targets","call_identifier":"FWF","grant_number":"W1232-B24","_id":"2548AE96-B435-11E9-9278-68D0E5697425"},{"call_identifier":"FWF","name":"The Wittgenstein Prize","grant_number":"Z00312","_id":"25C5A090-B435-11E9-9278-68D0E5697425"},{"_id":"23889792-32DE-11EA-91FC-C7463DDC885E","name":"High content imaging to decode human immune cell interactions in health and allergic disease"},{"name":"International IST Doctoral Program","call_identifier":"H2020","_id":"2564DBCA-B435-11E9-9278-68D0E5697425","grant_number":"665385"},{"name":"MATERIALIZABLE: Intelligent fabrication-oriented Computational Design and Modeling","call_identifier":"H2020","grant_number":"715767","_id":"24F9549A-B435-11E9-9278-68D0E5697425"},{"call_identifier":"H2020","name":"Probing the Reversibility of Autism Spectrum Disorders by Employing in vivo and in vitro Models","_id":"25444568-B435-11E9-9278-68D0E5697425","grant_number":"715508"},{"call_identifier":"H2020","name":"Biophysics and circuit function of a giant cortical glumatergic synapse","grant_number":"692692","_id":"25B7EB9E-B435-11E9-9278-68D0E5697425"},{"call_identifier":"H2020","name":"Synaptic computations of the hippocampal CA3 circuitry","_id":"fc2be41b-9c52-11eb-aca3-faa90aa144e9","grant_number":"101026635"},{"name":"High-speed 3D-nanoscopy to study the role of adhesion during 3D cell migration","_id":"2668BFA0-B435-11E9-9278-68D0E5697425","grant_number":"LT00057"}],"ec_funded":1,"related_material":{"record":[{"status":"public","id":"12817","relation":"research_data"},{"status":"public","id":"14770","relation":"shorter_version"}],"link":[{"relation":"software","url":"https://github.com/danzllab/LIONESS"}]},"citation":{"short":"P. Velicky, E. Miguel Villalba, J.M. Michalska, J. Lyudchik, D. Wei, Z. Lin, J. Watson, J. Troidl, J. Beyer, Y. Ben Simon, C.M. Sommer, W. Jahr, A. Cenameri, J. Broichhagen, S.G.N. Grant, P.M. Jonas, G. Novarino, H. Pfister, B. Bickel, J.G. Danzl, Nature Methods 20 (2023) 1256–1265.","ieee":"P. Velicky <i>et al.</i>, “Dense 4D nanoscale reconstruction of living brain tissue,” <i>Nature Methods</i>, vol. 20. Springer Nature, pp. 1256–1265, 2023.","ama":"Velicky P, Miguel Villalba E, Michalska JM, et al. Dense 4D nanoscale reconstruction of living brain tissue. <i>Nature Methods</i>. 2023;20:1256-1265. doi:<a href=\"https://doi.org/10.1038/s41592-023-01936-6\">10.1038/s41592-023-01936-6</a>","ista":"Velicky P, Miguel Villalba E, Michalska JM, Lyudchik J, Wei D, Lin Z, Watson J, Troidl J, Beyer J, Ben Simon Y, Sommer CM, Jahr W, Cenameri A, Broichhagen J, Grant SGN, Jonas PM, Novarino G, Pfister H, Bickel B, Danzl JG. 2023. Dense 4D nanoscale reconstruction of living brain tissue. Nature Methods. 20, 1256–1265.","chicago":"Velicky, Philipp, Eder Miguel Villalba, Julia M Michalska, Julia Lyudchik, Donglai Wei, Zudi Lin, Jake Watson, et al. “Dense 4D Nanoscale Reconstruction of Living Brain Tissue.” <i>Nature Methods</i>. Springer Nature, 2023. <a href=\"https://doi.org/10.1038/s41592-023-01936-6\">https://doi.org/10.1038/s41592-023-01936-6</a>.","mla":"Velicky, Philipp, et al. “Dense 4D Nanoscale Reconstruction of Living Brain Tissue.” <i>Nature Methods</i>, vol. 20, Springer Nature, 2023, pp. 1256–65, doi:<a href=\"https://doi.org/10.1038/s41592-023-01936-6\">10.1038/s41592-023-01936-6</a>.","apa":"Velicky, P., Miguel Villalba, E., Michalska, J. M., Lyudchik, J., Wei, D., Lin, Z., … Danzl, J. G. (2023). Dense 4D nanoscale reconstruction of living brain tissue. <i>Nature Methods</i>. Springer Nature. <a href=\"https://doi.org/10.1038/s41592-023-01936-6\">https://doi.org/10.1038/s41592-023-01936-6</a>"},"date_created":"2023-07-23T22:01:13Z","acknowledgement":"We thank J. Vorlaufer, N. Agudelo and A. Wartak for microscope maintenance and troubleshooting, C. Kreuzinger and A. Freeman for technical assistance, M. Šuplata for hardware control support and M. Cunha dos Santos for initial exploration of software. We\r\nthank P. Henderson for advice on deep-learning training and M. Sixt, S. Boyd and T. Weiss for discussions and critical reading of the manuscript. L. Lavis (Janelia Research Campus) generously provided the JF585-HaloTag ligand. We acknowledge expert support by IST\r\nAustria’s scientific computing, imaging and optics, preclinical, library and laboratory support facilities and by the Miba machine shop. We gratefully acknowledge funding by the following sources: Austrian Science Fund (F.W.F.) grant no. I3600-B27 (J.G.D.), grant no. DK W1232\r\n(J.G.D. and J.M.M.) and grant no. Z 312-B27, Wittgenstein award (P.J.); the Gesellschaft für Forschungsförderung NÖ grant no. LSC18-022 (J.G.D.); an ISTA Interdisciplinary project grant (J.G.D. and B.B.); the European Union’s Horizon 2020 research and innovation programme,\r\nMarie-Skłodowska Curie grant 665385 (J.M.M. and J.L.); the European Union’s Horizon 2020 research and innovation programme, European Research Council grant no. 715767, MATERIALIZABLE (B.B.); grant no. 715508, REVERSEAUTISM (G.N.); grant no. 695568, SYNNOVATE (S.G.N.G.); and grant no. 692692, GIANTSYN (P.J.); the Simons\r\nFoundation Autism Research Initiative grant no. 529085 (S.G.N.G.); the Wellcome Trust Technology Development grant no. 202932 (S.G.N.G.); the Marie Skłodowska-Curie Actions Individual Fellowship no. 101026635 under the EU Horizon 2020 program (J.F.W.);\r\nthe Human Frontier Science Program postdoctoral fellowship LT000557/2018 (W.J.); and the National Science Foundation grant no. IIS-1835231 (H.P.) and NCS-FO-2124179 (H.P.).","year":"2023","doi":"10.1038/s41592-023-01936-6","acknowledged_ssus":[{"_id":"ScienComp"},{"_id":"Bio"},{"_id":"PreCl"},{"_id":"E-Lib"},{"_id":"LifeSc"},{"_id":"M-Shop"}],"_id":"13267","article_type":"original","oa_version":"Published Version","day":"01","main_file_link":[{"url":"https://doi.org/10.1038/s41592-023-01936-6","open_access":"1"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publication_identifier":{"eissn":["1548-7105"],"issn":["1548-7091"]},"month":"08","author":[{"orcid":"0000-0002-2340-7431","last_name":"Velicky","id":"39BDC62C-F248-11E8-B48F-1D18A9856A87","first_name":"Philipp","full_name":"Velicky, Philipp"},{"orcid":"0000-0001-5665-0430","id":"3FB91342-F248-11E8-B48F-1D18A9856A87","last_name":"Miguel Villalba","full_name":"Miguel Villalba, Eder","first_name":"Eder"},{"orcid":"0000-0003-3862-1235","id":"443DB6DE-F248-11E8-B48F-1D18A9856A87","last_name":"Michalska","full_name":"Michalska, Julia M","first_name":"Julia M"},{"first_name":"Julia","full_name":"Lyudchik, Julia","last_name":"Lyudchik","id":"46E28B80-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Donglai","full_name":"Wei, Donglai","last_name":"Wei"},{"full_name":"Lin, Zudi","first_name":"Zudi","last_name":"Lin"},{"orcid":"0000-0002-8698-3823","last_name":"Watson","id":"63836096-4690-11EA-BD4E-32803DDC885E","first_name":"Jake","full_name":"Watson, Jake"},{"first_name":"Jakob","full_name":"Troidl, Jakob","last_name":"Troidl"},{"last_name":"Beyer","first_name":"Johanna","full_name":"Beyer, Johanna"},{"first_name":"Yoav","full_name":"Ben Simon, Yoav","id":"43DF3136-F248-11E8-B48F-1D18A9856A87","last_name":"Ben Simon"},{"full_name":"Sommer, Christoph M","first_name":"Christoph M","last_name":"Sommer","id":"4DF26D8C-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-1216-9105"},{"full_name":"Jahr, Wiebke","first_name":"Wiebke","last_name":"Jahr","id":"425C1CE8-F248-11E8-B48F-1D18A9856A87"},{"last_name":"Cenameri","id":"9ac8f577-2357-11eb-997a-e566c5550886","first_name":"Alban","full_name":"Cenameri, Alban"},{"full_name":"Broichhagen, Johannes","first_name":"Johannes","last_name":"Broichhagen"},{"first_name":"Seth G.N.","full_name":"Grant, Seth G.N.","last_name":"Grant"},{"orcid":"0000-0001-5001-4804","id":"353C1B58-F248-11E8-B48F-1D18A9856A87","last_name":"Jonas","full_name":"Jonas, Peter M","first_name":"Peter M"},{"first_name":"Gaia","full_name":"Novarino, Gaia","orcid":"0000-0002-7673-7178","id":"3E57A680-F248-11E8-B48F-1D18A9856A87","last_name":"Novarino"},{"last_name":"Pfister","full_name":"Pfister, Hanspeter","first_name":"Hanspeter"},{"orcid":"0000-0001-6511-9385","id":"49876194-F248-11E8-B48F-1D18A9856A87","last_name":"Bickel","full_name":"Bickel, Bernd","first_name":"Bernd"},{"last_name":"Danzl","id":"42EFD3B6-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-8559-3973","first_name":"Johann G","full_name":"Danzl, Johann G"}],"pmid":1,"status":"public","type":"journal_article","scopus_import":"1","intvolume":"        20","isi":1,"title":"Dense 4D nanoscale reconstruction of living brain tissue","oa":1,"date_updated":"2024-01-10T08:37:48Z","article_processing_charge":"Yes","publication":"Nature Methods","language":[{"iso":"eng"}]},{"language":[{"iso":"eng"}],"publication":"Proceedings of the 37th AAAI Conference on Artificial Intelligence","title":"Learning control policies for stochastic systems with reach-avoid guarantees","article_processing_charge":"No","issue":"10","date_updated":"2025-07-14T09:10:02Z","intvolume":"        37","status":"public","type":"conference","arxiv":1,"author":[{"orcid":"0000-0002-4681-1699","id":"294AA7A6-F248-11E8-B48F-1D18A9856A87","last_name":"Zikelic","first_name":"Dorde","full_name":"Zikelic, Dorde"},{"id":"3DC22916-F248-11E8-B48F-1D18A9856A87","last_name":"Lechner","first_name":"Mathias","full_name":"Lechner, Mathias"},{"full_name":"Henzinger, Thomas A","first_name":"Thomas A","last_name":"Henzinger","id":"40876CD8-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-2985-7724"},{"id":"2E5DCA20-F248-11E8-B48F-1D18A9856A87","last_name":"Chatterjee","orcid":"0000-0002-4561-241X","first_name":"Krishnendu","full_name":"Chatterjee, Krishnendu"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","day":"26","oa_version":"Preprint","publication_identifier":{"issn":["2159-5399"],"eissn":["2374-3468"]},"month":"06","conference":{"location":"Washington, DC, United States","end_date":"2023-02-14","name":"AAAI: Conference on Artificial Intelligence","start_date":"2023-02-07"},"_id":"14830","doi":"10.1609/aaai.v37i10.26407","keyword":["General Medicine"],"date_created":"2024-01-18T07:44:31Z","citation":{"apa":"Zikelic, D., Lechner, M., Henzinger, T. A., &#38; Chatterjee, K. (2023). Learning control policies for stochastic systems with reach-avoid guarantees. In <i>Proceedings of the 37th AAAI Conference on Artificial Intelligence</i> (Vol. 37, pp. 11926–11935). Washington, DC, United States: Association for the Advancement of Artificial Intelligence. <a href=\"https://doi.org/10.1609/aaai.v37i10.26407\">https://doi.org/10.1609/aaai.v37i10.26407</a>","ama":"Zikelic D, Lechner M, Henzinger TA, Chatterjee K. Learning control policies for stochastic systems with reach-avoid guarantees. In: <i>Proceedings of the 37th AAAI Conference on Artificial Intelligence</i>. Vol 37. Association for the Advancement of Artificial Intelligence; 2023:11926-11935. doi:<a href=\"https://doi.org/10.1609/aaai.v37i10.26407\">10.1609/aaai.v37i10.26407</a>","ieee":"D. Zikelic, M. Lechner, T. A. Henzinger, and K. Chatterjee, “Learning control policies for stochastic systems with reach-avoid guarantees,” in <i>Proceedings of the 37th AAAI Conference on Artificial Intelligence</i>, Washington, DC, United States, 2023, vol. 37, no. 10, pp. 11926–11935.","short":"D. Zikelic, M. Lechner, T.A. Henzinger, K. Chatterjee, in:, Proceedings of the 37th AAAI Conference on Artificial Intelligence, Association for the Advancement of Artificial Intelligence, 2023, pp. 11926–11935.","mla":"Zikelic, Dorde, et al. “Learning Control Policies for Stochastic Systems with Reach-Avoid Guarantees.” <i>Proceedings of the 37th AAAI Conference on Artificial Intelligence</i>, vol. 37, no. 10, Association for the Advancement of Artificial Intelligence, 2023, pp. 11926–35, doi:<a href=\"https://doi.org/10.1609/aaai.v37i10.26407\">10.1609/aaai.v37i10.26407</a>.","ista":"Zikelic D, Lechner M, Henzinger TA, Chatterjee K. 2023. Learning control policies for stochastic systems with reach-avoid guarantees. Proceedings of the 37th AAAI Conference on Artificial Intelligence. AAAI: Conference on Artificial Intelligence vol. 37, 11926–11935.","chicago":"Zikelic, Dorde, Mathias Lechner, Thomas A Henzinger, and Krishnendu Chatterjee. “Learning Control Policies for Stochastic Systems with Reach-Avoid Guarantees.” In <i>Proceedings of the 37th AAAI Conference on Artificial Intelligence</i>, 37:11926–35. Association for the Advancement of Artificial Intelligence, 2023. <a href=\"https://doi.org/10.1609/aaai.v37i10.26407\">https://doi.org/10.1609/aaai.v37i10.26407</a>."},"year":"2023","acknowledgement":"This work was supported in part by the ERC-2020-AdG 101020093, ERC CoG 863818 (FoRM-SMArt) and the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 665385.","related_material":{"record":[{"relation":"earlier_version","id":"14600","status":"public"}]},"ec_funded":1,"project":[{"call_identifier":"H2020","name":"Vigilant Algorithmic Monitoring of Software","grant_number":"101020093","_id":"62781420-2b32-11ec-9570-8d9b63373d4d"},{"call_identifier":"H2020","name":"Formal Methods for Stochastic Models: Algorithms and Applications","_id":"0599E47C-7A3F-11EA-A408-12923DDC885E","grant_number":"863818"},{"_id":"2564DBCA-B435-11E9-9278-68D0E5697425","grant_number":"665385","call_identifier":"H2020","name":"International IST Doctoral Program"}],"volume":37,"quality_controlled":"1","department":[{"_id":"ToHe"},{"_id":"KrCh"}],"page":"11926-11935","date_published":"2023-06-26T00:00:00Z","publisher":"Association for the Advancement of Artificial Intelligence","publication_status":"published","abstract":[{"text":"We study the problem of learning controllers for discrete-time non-linear stochastic dynamical systems with formal reach-avoid guarantees. This work presents the first method for providing formal reach-avoid guarantees, which combine and generalize stability and safety guarantees, with a tolerable probability threshold p in [0,1] over the infinite time horizon. Our method leverages advances in machine learning literature and it represents formal certificates as neural networks. In particular, we learn a certificate in the form of a reach-avoid supermartingale (RASM), a novel notion that we introduce in this work. Our RASMs provide reachability and avoidance guarantees by imposing constraints on what can be viewed as a stochastic extension of level sets of Lyapunov functions for deterministic systems. Our approach solves several important problems -- it can be used to learn a control policy from scratch, to verify a reach-avoid specification for a fixed control policy, or to fine-tune a pre-trained policy if it does not satisfy the reach-avoid specification. We validate our approach on 3 stochastic non-linear reinforcement learning tasks.","lang":"eng"}],"external_id":{"arxiv":["2210.05308"]}},{"file":[{"access_level":"closed","relation":"source_file","file_size":10891454,"content_type":"application/zip","creator":"gpuixeus","date_created":"2023-08-16T18:15:17Z","date_updated":"2023-08-17T06:55:24Z","file_name":"Thesis_latex_forpdfa.zip","checksum":"4e44e169f2724ee8c9324cd60bcc2b71","file_id":"14075"},{"checksum":"e10b04cd8f3fecc0d9ef6e6868b6e1e8","file_id":"14079","file_name":"PhDThesis_PuixeuG.pdf","success":1,"date_updated":"2023-08-18T10:47:55Z","date_created":"2023-08-18T10:47:55Z","creator":"gpuixeus","relation":"main_file","content_type":"application/pdf","access_level":"open_access","file_size":19856686}],"user_id":"8b945eb4-e2f2-11eb-945a-df72226e66a9","oa_version":"Published Version","day":"15","month":"08","publication_identifier":{"isbn":["978-3-99078-035-0"],"issn":["2663-337X"]},"author":[{"full_name":"Puixeu Sala, Gemma","first_name":"Gemma","orcid":"0000-0001-8330-1754","last_name":"Puixeu Sala","id":"33AB266C-F248-11E8-B48F-1D18A9856A87"}],"type":"dissertation","status":"public","alternative_title":["ISTA Thesis"],"has_accepted_license":"1","title":"The molecular basis of sexual dimorphism: Experimental and theoretical characterization of phenotypic, transcriptomic and genetic patterns of sex-specific adaptation","article_processing_charge":"No","date_updated":"2023-12-13T12:15:36Z","oa":1,"language":[{"iso":"eng"}],"abstract":[{"lang":"eng","text":"Females and males across species are subject to divergent selective pressures arising\r\nfrom di↵erent reproductive interests and ecological niches. This often translates into a\r\nintricate array of sex-specific natural and sexual selection on traits that have a shared\r\ngenetic basis between both sexes, causing a genetic sexual conflict. The resolution of\r\nthis conflict mostly relies on the evolution of sex-specific expression of the shared genes,\r\nleading to phenotypic sexual dimorphism. Such sex-specific gene expression is thought\r\nto evolve via modifications of the genetic networks ultimately linked to sex-determining\r\ntranscription factors. Although much empirical and theoretical evidence supports this\r\nstandard picture of the molecular basis of sexual conflict resolution, there still are a\r\nfew open questions regarding the complex array of selective forces driving phenotypic\r\ndi↵erentiation between the sexes, as well as the molecular mechanisms underlying sexspecific adaptation. I address some of these open questions in my PhD thesis.\r\nFirst, how do patterns of phenotypic sexual dimorphism vary within populations,\r\nas a response to the temporal and spatial changes in sex-specific selective forces? To\r\ntackle this question, I analyze the patterns of sex-specific phenotypic variation along\r\nthree life stages and across populations spanning the whole geographical range of Rumex\r\nhastatulus, a wind-pollinated angiosperm, in the first Chapter of the thesis.\r\nSecond, how do gene expression patterns lead to phenotypic dimorphism, and what\r\nare the molecular mechanisms underlying the observed transcriptomic variation? I\r\naddress this question by examining the sex- and tissue-specific expression variation in\r\nnewly-generated datasets of sex-specific expression in heads and gonads of Drosophila\r\nmelanogaster. I additionally used two complementary approaches for the study of the\r\ngenetic basis of sex di↵erences in gene expression in the second and third Chapters of\r\nthe thesis.\r\nThird, how does intersex correlation, thought to be one of the main aspects constraining the ability for the two sexes to decouple, interact with the evolution of sexual\r\ndimorphism? I develop models of sex-specific stabilizing selection, mutation and drift\r\nto formalize common intuition regarding the patterns of covariation between intersex\r\ncorrelation and sexual dimorphism in the fourth Chapter of the thesis.\r\nAlltogether, the work described in this PhD thesis provides useful insights into the\r\nlinks between genetic, transcriptomic and phenotypic layers of sex-specific variation,\r\nand contributes to our general understanding of the dynamics of sexual dimorphism\r\nevolution."}],"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"},"ddc":["576"],"publication_status":"published","department":[{"_id":"GradSch"},{"_id":"NiBa"},{"_id":"BeVi"}],"page":"230","supervisor":[{"first_name":"Beatriz","full_name":"Vicoso, Beatriz","orcid":"0000-0002-4579-8306","id":"49E1C5C6-F248-11E8-B48F-1D18A9856A87","last_name":"Vicoso"},{"first_name":"Nicholas H","full_name":"Barton, Nicholas H","orcid":"0000-0002-8548-5240","last_name":"Barton","id":"4880FE40-F248-11E8-B48F-1D18A9856A87"}],"date_published":"2023-08-15T00:00:00Z","publisher":"Institute of Science and Technology Austria","project":[{"_id":"2564DBCA-B435-11E9-9278-68D0E5697425","grant_number":"665385","call_identifier":"H2020","name":"International IST Doctoral Program"},{"_id":"9B9DFC9E-BA93-11EA-9121-9846C619BF3A","grant_number":"25817","name":"Sexual conflict: resolution, constraints and biomedical implications"}],"degree_awarded":"PhD","related_material":{"record":[{"id":"9803","relation":"research_data","status":"public"},{"id":"12933","relation":"research_data","status":"public"},{"id":"6831","relation":"part_of_dissertation","status":"public"},{"status":"public","id":"14077","relation":"part_of_dissertation"}]},"ec_funded":1,"date_created":"2023-08-15T10:20:40Z","citation":{"ista":"Puixeu Sala G. 2023. The molecular basis of sexual dimorphism: Experimental and theoretical characterization of phenotypic, transcriptomic and genetic patterns of sex-specific adaptation. Institute of Science and Technology Austria.","chicago":"Puixeu Sala, Gemma. “The Molecular Basis of Sexual Dimorphism: Experimental and Theoretical Characterization of Phenotypic, Transcriptomic and Genetic Patterns of Sex-Specific Adaptation.” Institute of Science and Technology Austria, 2023. <a href=\"https://doi.org/10.15479/at:ista:14058\">https://doi.org/10.15479/at:ista:14058</a>.","mla":"Puixeu Sala, Gemma. <i>The Molecular Basis of Sexual Dimorphism: Experimental and Theoretical Characterization of Phenotypic, Transcriptomic and Genetic Patterns of Sex-Specific Adaptation</i>. Institute of Science and Technology Austria, 2023, doi:<a href=\"https://doi.org/10.15479/at:ista:14058\">10.15479/at:ista:14058</a>.","ieee":"G. Puixeu Sala, “The molecular basis of sexual dimorphism: Experimental and theoretical characterization of phenotypic, transcriptomic and genetic patterns of sex-specific adaptation,” Institute of Science and Technology Austria, 2023.","ama":"Puixeu Sala G. The molecular basis of sexual dimorphism: Experimental and theoretical characterization of phenotypic, transcriptomic and genetic patterns of sex-specific adaptation. 2023. doi:<a href=\"https://doi.org/10.15479/at:ista:14058\">10.15479/at:ista:14058</a>","short":"G. Puixeu Sala, The Molecular Basis of Sexual Dimorphism: Experimental and Theoretical Characterization of Phenotypic, Transcriptomic and Genetic Patterns of Sex-Specific Adaptation, Institute of Science and Technology Austria, 2023.","apa":"Puixeu Sala, G. (2023). <i>The molecular basis of sexual dimorphism: Experimental and theoretical characterization of phenotypic, transcriptomic and genetic patterns of sex-specific adaptation</i>. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/at:ista:14058\">https://doi.org/10.15479/at:ista:14058</a>"},"year":"2023","doi":"10.15479/at:ista:14058","_id":"14058","file_date_updated":"2023-08-18T10:47:55Z"},{"abstract":[{"lang":"eng","text":"The regulatory architecture of gene expression is known to differ substantially between sexes in Drosophila, but most studies performed\r\nso far used whole-body data and only single crosses, which may have limited their scope to detect patterns that are robust across tissues\r\nand biological replicates. Here, we use allele-specific gene expression of parental and reciprocal hybrid crosses between 6 Drosophila\r\nmelanogaster inbred lines to quantify cis- and trans-regulatory variation in heads and gonads of both sexes separately across 3 replicate\r\ncrosses. Our results suggest that female and male heads, as well as ovaries, have a similar regulatory architecture. On the other hand,\r\ntestes display more and substantially different cis-regulatory effects, suggesting that sex differences in the regulatory architecture that\r\nhave been previously observed may largely derive from testis-specific effects. We also examine the difference in cis-regulatory variation\r\nof genes across different levels of sex bias in gonads and heads. Consistent with the idea that intersex correlations constrain expression\r\nand can lead to sexual antagonism, we find more cis variation in unbiased and moderately biased genes in heads. In ovaries, reduced cis\r\nvariation is observed for male-biased genes, suggesting that cis variants acting on these genes in males do not lead to changes in ovary\r\nexpression. Finally, we examine the dominance patterns of gene expression and find that sex- and tissue-specific patterns of inheritance\r\nas well as trans-regulatory variation are highly variable across biological crosses, although these were performed in highly controlled\r\nexperimental conditions. This highlights the importance of using various genetic backgrounds to infer generalizable patterns."}],"external_id":{"isi":["001002997200001"]},"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"},"ddc":["570"],"publication_status":"published","quality_controlled":"1","volume":13,"department":[{"_id":"BeVi"},{"_id":"NiBa"},{"_id":"GradSch"}],"date_published":"2023-08-01T00:00:00Z","publisher":"Oxford University Press","project":[{"grant_number":"665385","_id":"2564DBCA-B435-11E9-9278-68D0E5697425","name":"International IST Doctoral Program","call_identifier":"H2020"},{"name":"Sexual conflict: resolution, constraints and biomedical implications","grant_number":"25817","_id":"9B9DFC9E-BA93-11EA-9121-9846C619BF3A"}],"related_material":{"record":[{"id":"12933","relation":"research_data","status":"public"},{"status":"public","id":"14058","relation":"dissertation_contains"}]},"ec_funded":1,"keyword":["Genetics (clinical)","Genetics","Molecular Biology"],"date_created":"2023-08-18T06:52:14Z","citation":{"apa":"Puixeu Sala, G., Macon, A., &#38; Vicoso, B. (2023). Sex-specific estimation of cis and trans regulation of gene expression in heads and gonads of Drosophila melanogaster. <i>G3: Genes, Genomes, Genetics</i>. Oxford University Press. <a href=\"https://doi.org/10.1093/g3journal/jkad121\">https://doi.org/10.1093/g3journal/jkad121</a>","ama":"Puixeu Sala G, Macon A, Vicoso B. Sex-specific estimation of cis and trans regulation of gene expression in heads and gonads of Drosophila melanogaster. <i>G3: Genes, Genomes, Genetics</i>. 2023;13(8). doi:<a href=\"https://doi.org/10.1093/g3journal/jkad121\">10.1093/g3journal/jkad121</a>","ieee":"G. Puixeu Sala, A. Macon, and B. Vicoso, “Sex-specific estimation of cis and trans regulation of gene expression in heads and gonads of Drosophila melanogaster,” <i>G3: Genes, Genomes, Genetics</i>, vol. 13, no. 8. Oxford University Press, 2023.","short":"G. Puixeu Sala, A. Macon, B. Vicoso, G3: Genes, Genomes, Genetics 13 (2023).","mla":"Puixeu Sala, Gemma, et al. “Sex-Specific Estimation of Cis and Trans Regulation of Gene Expression in Heads and Gonads of Drosophila Melanogaster.” <i>G3: Genes, Genomes, Genetics</i>, vol. 13, no. 8, Oxford University Press, 2023, doi:<a href=\"https://doi.org/10.1093/g3journal/jkad121\">10.1093/g3journal/jkad121</a>.","chicago":"Puixeu Sala, Gemma, Ariana Macon, and Beatriz Vicoso. “Sex-Specific Estimation of Cis and Trans Regulation of Gene Expression in Heads and Gonads of Drosophila Melanogaster.” <i>G3: Genes, Genomes, Genetics</i>. Oxford University Press, 2023. <a href=\"https://doi.org/10.1093/g3journal/jkad121\">https://doi.org/10.1093/g3journal/jkad121</a>.","ista":"Puixeu Sala G, Macon A, Vicoso B. 2023. Sex-specific estimation of cis and trans regulation of gene expression in heads and gonads of Drosophila melanogaster. G3: Genes, Genomes, Genetics. 13(8)."},"year":"2023","acknowledgement":"We thank members of the Vicoso Group for comments on the manuscript, the Scientific Computing Unit at ISTA for technical support, and 2 anonymous reviewers for useful feedback. GP is the recipient of a DOC Fellowship of the Austrian Academy of Sciences at the Institute of Science and Technology Austria (DOC 25817) and received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie Grant (agreement no. 665385).","doi":"10.1093/g3journal/jkad121","acknowledged_ssus":[{"_id":"ScienComp"}],"article_type":"original","_id":"14077","file_date_updated":"2023-11-07T09:00:19Z","file":[{"creator":"dernst","access_level":"open_access","content_type":"application/pdf","file_size":845642,"relation":"main_file","file_id":"14498","checksum":"c62e29fc7c5efbf8356f4c60cab4a2d1","file_name":"2023_G3_Puixeu.pdf","success":1,"date_updated":"2023-11-07T09:00:19Z","date_created":"2023-11-07T09:00:19Z"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","oa_version":"Published Version","day":"01","publication_identifier":{"issn":["2160-1836"]},"month":"08","author":[{"first_name":"Gemma","full_name":"Puixeu Sala, Gemma","orcid":"0000-0001-8330-1754","id":"33AB266C-F248-11E8-B48F-1D18A9856A87","last_name":"Puixeu Sala"},{"full_name":"Macon, Ariana","first_name":"Ariana","id":"2A0848E2-F248-11E8-B48F-1D18A9856A87","last_name":"Macon"},{"full_name":"Vicoso, Beatriz","first_name":"Beatriz","orcid":"0000-0002-4579-8306","last_name":"Vicoso","id":"49E1C5C6-F248-11E8-B48F-1D18A9856A87"}],"status":"public","type":"journal_article","scopus_import":"1","intvolume":"        13","has_accepted_license":"1","isi":1,"title":"Sex-specific estimation of cis and trans regulation of gene expression in heads and gonads of Drosophila melanogaster","article_processing_charge":"Yes","issue":"8","date_updated":"2023-12-13T12:15:37Z","oa":1,"publication":"G3: Genes, Genomes, Genetics","language":[{"iso":"eng"}]},{"doi":"10.1609/aaai.v37i12.26747","_id":"14242","ec_funded":1,"acknowledgement":"This work was supported in part by the ERC-2020-AdG 101020093, ERC CoG 863818 (FoRM-SMArt) and the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 665385. Research was sponsored by the United\r\nStates Air Force Research Laboratory and the United States Air Force Artificial Intelligence Accelerator and was accomplished under Cooperative Agreement Number FA8750-19-2-\r\n1000. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied,\r\nof the United States Air Force or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright\r\nnotation herein. The research was also funded in part by the AI2050 program at Schmidt Futures (Grant G-22-63172) and Capgemini SE.","year":"2023","citation":{"apa":"Lechner, M., Zikelic, D., Chatterjee, K., Henzinger, T. A., &#38; Rus, D. (2023). Quantization-aware interval bound propagation for training certifiably robust quantized neural networks. In <i>Proceedings of the 37th AAAI Conference on Artificial Intelligence</i> (Vol. 37, pp. 14964–14973). Washington, DC, United States: Association for the Advancement of Artificial Intelligence. <a href=\"https://doi.org/10.1609/aaai.v37i12.26747\">https://doi.org/10.1609/aaai.v37i12.26747</a>","mla":"Lechner, Mathias, et al. “Quantization-Aware Interval Bound Propagation for Training Certifiably Robust Quantized Neural Networks.” <i>Proceedings of the 37th AAAI Conference on Artificial Intelligence</i>, vol. 37, no. 12, Association for the Advancement of Artificial Intelligence, 2023, pp. 14964–73, doi:<a href=\"https://doi.org/10.1609/aaai.v37i12.26747\">10.1609/aaai.v37i12.26747</a>.","chicago":"Lechner, Mathias, Dorde Zikelic, Krishnendu Chatterjee, Thomas A Henzinger, and Daniela Rus. “Quantization-Aware Interval Bound Propagation for Training Certifiably Robust Quantized Neural Networks.” In <i>Proceedings of the 37th AAAI Conference on Artificial Intelligence</i>, 37:14964–73. Association for the Advancement of Artificial Intelligence, 2023. <a href=\"https://doi.org/10.1609/aaai.v37i12.26747\">https://doi.org/10.1609/aaai.v37i12.26747</a>.","ista":"Lechner M, Zikelic D, Chatterjee K, Henzinger TA, Rus D. 2023. Quantization-aware interval bound propagation for training certifiably robust quantized neural networks. Proceedings of the 37th AAAI Conference on Artificial Intelligence. AAAI: Conference on Artificial Intelligence vol. 37, 14964–14973.","short":"M. Lechner, D. Zikelic, K. Chatterjee, T.A. Henzinger, D. Rus, in:, Proceedings of the 37th AAAI Conference on Artificial Intelligence, Association for the Advancement of Artificial Intelligence, 2023, pp. 14964–14973.","ama":"Lechner M, Zikelic D, Chatterjee K, Henzinger TA, Rus D. Quantization-aware interval bound propagation for training certifiably robust quantized neural networks. In: <i>Proceedings of the 37th AAAI Conference on Artificial Intelligence</i>. Vol 37. Association for the Advancement of Artificial Intelligence; 2023:14964-14973. doi:<a href=\"https://doi.org/10.1609/aaai.v37i12.26747\">10.1609/aaai.v37i12.26747</a>","ieee":"M. Lechner, D. Zikelic, K. Chatterjee, T. A. Henzinger, and D. Rus, “Quantization-aware interval bound propagation for training certifiably robust quantized neural networks,” in <i>Proceedings of the 37th AAAI Conference on Artificial Intelligence</i>, Washington, DC, United States, 2023, vol. 37, no. 12, pp. 14964–14973."},"date_created":"2023-08-27T22:01:17Z","publisher":"Association for the Advancement of Artificial Intelligence","date_published":"2023-06-26T00:00:00Z","page":"14964-14973","department":[{"_id":"ToHe"},{"_id":"KrCh"}],"volume":37,"quality_controlled":"1","project":[{"grant_number":"101020093","_id":"62781420-2b32-11ec-9570-8d9b63373d4d","call_identifier":"H2020","name":"Vigilant Algorithmic Monitoring of Software"},{"call_identifier":"H2020","name":"Formal Methods for Stochastic Models: Algorithms and Applications","_id":"0599E47C-7A3F-11EA-A408-12923DDC885E","grant_number":"863818"},{"grant_number":"665385","_id":"2564DBCA-B435-11E9-9278-68D0E5697425","name":"International IST Doctoral Program","call_identifier":"H2020"}],"external_id":{"arxiv":["2211.16187"]},"abstract":[{"text":"We study the problem of training and certifying adversarially robust quantized neural networks (QNNs). Quantization is a technique for making neural networks more efficient by running them using low-bit integer arithmetic and is therefore commonly adopted in industry. Recent work has shown that floating-point neural networks that have been verified to be robust can become vulnerable to adversarial attacks after quantization, and certification of the quantized representation is necessary to guarantee robustness. In this work, we present quantization-aware interval bound propagation (QA-IBP), a novel method for training robust QNNs. Inspired by advances in robust learning of non-quantized networks, our training algorithm computes the gradient of an abstract representation of the actual network. Unlike existing approaches, our method can handle the discrete semantics of QNNs. Based on QA-IBP, we also develop a complete verification procedure for verifying the adversarial robustness of QNNs, which is guaranteed to terminate and produce a correct answer. Compared to existing approaches, the key advantage of our verification procedure is that it runs entirely on GPU or other accelerator devices. We demonstrate experimentally that our approach significantly outperforms existing methods and establish the new state-of-the-art for training and certifying the robustness of QNNs.","lang":"eng"}],"publication_status":"published","publication":"Proceedings of the 37th AAAI Conference on Artificial Intelligence","language":[{"iso":"eng"}],"intvolume":"        37","scopus_import":"1","date_updated":"2025-07-14T09:09:56Z","oa":1,"article_processing_charge":"No","issue":"12","title":"Quantization-aware interval bound propagation for training certifiably robust quantized neural networks","status":"public","type":"conference","conference":{"end_date":"2023-02-14","location":"Washington, DC, United States","start_date":"2023-02-07","name":"AAAI: Conference on Artificial Intelligence"},"month":"06","publication_identifier":{"isbn":["9781577358800"]},"day":"26","oa_version":"Preprint","main_file_link":[{"open_access":"1","url":"https://doi.org/10.48550/arXiv.2211.16187"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","author":[{"first_name":"Mathias","full_name":"Lechner, Mathias","last_name":"Lechner","id":"3DC22916-F248-11E8-B48F-1D18A9856A87"},{"orcid":"0000-0002-4681-1699","id":"294AA7A6-F248-11E8-B48F-1D18A9856A87","last_name":"Zikelic","first_name":"Dorde","full_name":"Zikelic, Dorde"},{"first_name":"Krishnendu","full_name":"Chatterjee, Krishnendu","last_name":"Chatterjee","id":"2E5DCA20-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-4561-241X"},{"full_name":"Henzinger, Thomas A","first_name":"Thomas A","id":"40876CD8-F248-11E8-B48F-1D18A9856A87","last_name":"Henzinger","orcid":"0000-0002-2985-7724"},{"full_name":"Rus, Daniela","first_name":"Daniela","last_name":"Rus"}],"arxiv":1},{"oa":1,"date_updated":"2025-07-14T09:09:56Z","issue":"5","article_processing_charge":"No","title":"Bidding graph games with partially-observable budgets","scopus_import":"1","intvolume":"        37","language":[{"iso":"eng"}],"publication":"Proceedings of the 37th AAAI Conference on Artificial Intelligence","author":[{"full_name":"Avni, Guy","first_name":"Guy","orcid":"0000-0001-5588-8287","id":"463C8BC2-F248-11E8-B48F-1D18A9856A87","last_name":"Avni"},{"first_name":"Ismael R","full_name":"Jecker, Ismael R","id":"85D7C63E-7D5D-11E9-9C0F-98C4E5697425","last_name":"Jecker"},{"id":"294AA7A6-F248-11E8-B48F-1D18A9856A87","last_name":"Zikelic","orcid":"0000-0002-4681-1699","first_name":"Dorde","full_name":"Zikelic, Dorde"}],"arxiv":1,"conference":{"start_date":"2023-02-07","name":"AAAI: Conference on Artificial Intelligence","end_date":"2023-02-14","location":"Washington, DC, United States"},"month":"06","publication_identifier":{"isbn":["9781577358800"]},"oa_version":"Published Version","main_file_link":[{"url":"https://doi.org/10.1609/aaai.v37i5.25679","open_access":"1"}],"day":"27","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","type":"conference","status":"public","acknowledgement":"This research was supported in part by ISF grant no.1679/21, by the ERC CoG 863818 (ForM-SMArt), and the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 665385.","year":"2023","date_created":"2023-08-27T22:01:18Z","citation":{"apa":"Avni, G., Jecker, I. R., &#38; Zikelic, D. (2023). Bidding graph games with partially-observable budgets. In <i>Proceedings of the 37th AAAI Conference on Artificial Intelligence</i> (Vol. 37, pp. 5464–5471). Washington, DC, United States. <a href=\"https://doi.org/10.1609/aaai.v37i5.25679\">https://doi.org/10.1609/aaai.v37i5.25679</a>","mla":"Avni, Guy, et al. “Bidding Graph Games with Partially-Observable Budgets.” <i>Proceedings of the 37th AAAI Conference on Artificial Intelligence</i>, vol. 37, no. 5, 2023, pp. 5464–71, doi:<a href=\"https://doi.org/10.1609/aaai.v37i5.25679\">10.1609/aaai.v37i5.25679</a>.","ista":"Avni G, Jecker IR, Zikelic D. 2023. Bidding graph games with partially-observable budgets. Proceedings of the 37th AAAI Conference on Artificial Intelligence. AAAI: Conference on Artificial Intelligence vol. 37, 5464–5471.","chicago":"Avni, Guy, Ismael R Jecker, and Dorde Zikelic. “Bidding Graph Games with Partially-Observable Budgets.” In <i>Proceedings of the 37th AAAI Conference on Artificial Intelligence</i>, 37:5464–71, 2023. <a href=\"https://doi.org/10.1609/aaai.v37i5.25679\">https://doi.org/10.1609/aaai.v37i5.25679</a>.","ama":"Avni G, Jecker IR, Zikelic D. Bidding graph games with partially-observable budgets. In: <i>Proceedings of the 37th AAAI Conference on Artificial Intelligence</i>. Vol 37. ; 2023:5464-5471. doi:<a href=\"https://doi.org/10.1609/aaai.v37i5.25679\">10.1609/aaai.v37i5.25679</a>","ieee":"G. Avni, I. R. Jecker, and D. Zikelic, “Bidding graph games with partially-observable budgets,” in <i>Proceedings of the 37th AAAI Conference on Artificial Intelligence</i>, Washington, DC, United States, 2023, vol. 37, no. 5, pp. 5464–5471.","short":"G. Avni, I.R. Jecker, D. Zikelic, in:, Proceedings of the 37th AAAI Conference on Artificial Intelligence, 2023, pp. 5464–5471."},"ec_funded":1,"_id":"14243","doi":"10.1609/aaai.v37i5.25679","publication_status":"published","external_id":{"arxiv":["2211.13626"]},"abstract":[{"text":"Two-player zero-sum \"graph games\" are central in logic, verification, and multi-agent systems. The game proceeds by placing a token on a vertex of a graph, and allowing the players to move it to produce an infinite path, which determines the winner or payoff of the game. Traditionally, the players alternate turns in moving the token. In \"bidding games\", however, the players have budgets and in each turn, an auction (bidding) determines which player moves the token. So far, bidding games have only been studied as full-information games. In this work we initiate the study of partial-information bidding games: we study bidding games in which a player's initial budget is drawn from a known probability distribution. We show that while for some bidding mechanisms and objectives, it is straightforward to adapt the results from the full-information setting to the partial-information setting, for others, the analysis is significantly more challenging, requires new techniques, and gives rise to interesting results. Specifically, we study games with \"mean-payoff\" objectives in combination with \"poorman\" bidding. We construct optimal strategies for a partially-informed player who plays against a fully-informed adversary. We show that, somewhat surprisingly, the \"value\" under pure strategies does not necessarily exist in such games.","lang":"eng"}],"project":[{"grant_number":"863818","_id":"0599E47C-7A3F-11EA-A408-12923DDC885E","name":"Formal Methods for Stochastic Models: Algorithms and Applications","call_identifier":"H2020"},{"grant_number":"665385","_id":"2564DBCA-B435-11E9-9278-68D0E5697425","name":"International IST Doctoral Program","call_identifier":"H2020"}],"date_published":"2023-06-27T00:00:00Z","department":[{"_id":"ToHe"},{"_id":"KrCh"}],"page":"5464-5471","volume":37,"quality_controlled":"1"},{"date_updated":"2024-02-21T12:18:18Z","oa":1,"article_processing_charge":"Yes (in subscription journal)","title":"Imaging brain tissue architecture across millimeter to nanometer scales","isi":1,"scopus_import":"1","language":[{"iso":"eng"}],"publication":"Nature Biotechnology","author":[{"first_name":"Julia M","full_name":"Michalska, Julia M","id":"443DB6DE-F248-11E8-B48F-1D18A9856A87","last_name":"Michalska","orcid":"0000-0003-3862-1235"},{"first_name":"Julia","full_name":"Lyudchik, Julia","id":"46E28B80-F248-11E8-B48F-1D18A9856A87","last_name":"Lyudchik"},{"full_name":"Velicky, Philipp","first_name":"Philipp","orcid":"0000-0002-2340-7431","id":"39BDC62C-F248-11E8-B48F-1D18A9856A87","last_name":"Velicky"},{"id":"ee3cb6ca-ec98-11ea-ae11-ff703e2254ed","last_name":"Korinkova","full_name":"Korinkova, Hana","first_name":"Hana"},{"orcid":"0000-0002-8698-3823","last_name":"Watson","id":"63836096-4690-11EA-BD4E-32803DDC885E","full_name":"Watson, Jake","first_name":"Jake"},{"id":"9ac8f577-2357-11eb-997a-e566c5550886","last_name":"Cenameri","full_name":"Cenameri, Alban","first_name":"Alban"},{"id":"4DF26D8C-F248-11E8-B48F-1D18A9856A87","last_name":"Sommer","orcid":"0000-0003-1216-9105","first_name":"Christoph M","full_name":"Sommer, Christoph M"},{"orcid":"0000-0002-3183-8207","id":"4CD6AAC6-F248-11E8-B48F-1D18A9856A87","last_name":"Amberg","full_name":"Amberg, Nicole","first_name":"Nicole"},{"first_name":"Alessandro","full_name":"Venturino, Alessandro","orcid":"0000-0003-2356-9403","id":"41CB84B2-F248-11E8-B48F-1D18A9856A87","last_name":"Venturino"},{"last_name":"Roessler","first_name":"Karl","full_name":"Roessler, Karl"},{"full_name":"Czech, Thomas","first_name":"Thomas","last_name":"Czech"},{"last_name":"Höftberger","full_name":"Höftberger, Romana","first_name":"Romana"},{"id":"36ACD32E-F248-11E8-B48F-1D18A9856A87","last_name":"Siegert","orcid":"0000-0001-8635-0877","first_name":"Sandra","full_name":"Siegert, Sandra"},{"id":"3E57A680-F248-11E8-B48F-1D18A9856A87","last_name":"Novarino","orcid":"0000-0002-7673-7178","full_name":"Novarino, Gaia","first_name":"Gaia"},{"first_name":"Peter M","full_name":"Jonas, Peter M","last_name":"Jonas","id":"353C1B58-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-5001-4804"},{"first_name":"Johann G","full_name":"Danzl, Johann G","id":"42EFD3B6-F248-11E8-B48F-1D18A9856A87","last_name":"Danzl","orcid":"0000-0001-8559-3973"}],"publication_identifier":{"issn":["1087-0156"],"eissn":["1546-1696"]},"month":"08","day":"31","main_file_link":[{"open_access":"1","url":"https://doi.org/10.1038/s41587-023-01911-8"}],"oa_version":"Published Version","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","status":"public","type":"journal_article","acknowledgement":"We thank J. Vorlaufer, N. Agudelo-Dueñas, W. Jahr and A. Wartak for microscope maintenance and troubleshooting; C. Kreuzinger, A. Freeman and I. Erber for technical assistance; and M. Tomschik for support with obtaining human samples. We gratefully acknowledge E. Miguel for setting up webKnossos and M. Šuplata for computational support and hardware control. We are grateful to R. Shigemoto and B. Bickel for generous support and M. Sixt and S. Boyd (Stanford University) for discussions and critical reading of the paper. PSD95-HaloTag mice were kindly provided by S. Grant (University of Edinburgh). We acknowledge expert support by Institute of Science and Technology Austria’s scientific computing, imaging and optics, preclinical and lab support facilities and by the Miba machine shop and library. We gratefully acknowledge funding by the following sources: Austrian Science Fund (FWF) grant I3600-B27 (J.G.D.); Austrian Science Fund (FWF) grant DK W1232 (J.G.D. and J.M.M.); Austrian Science Fund (FWF) grant Z 312-B27, Wittgenstein award (P.J.); Austrian Science Fund (FWF) projects I4685-B, I6565-B (SYNABS) and DOC 33-B27 (R.H.); Gesellschaft für Forschungsförderung NÖ (NFB) grant LSC18-022 (J.G.D.); European Union’s Horizon 2020 research and innovation programme, European Research Council (ERC) grant 715508 – REVERSEAUTISM (G.N.); European Union’s Horizon 2020 research and innovation programme, European Research Council (ERC) grant 692692 – GIANTSYN (P.J.); Marie Skłodowska-Curie Actions Fellowship GA no. 665385 under the EU Horizon 2020 program (J.M.M. and J.L.); and Marie Skłodowska-Curie Actions Individual Fellowship no. 101026635 under the EU Horizon 2020 program (J.F.W.).","year":"2023","date_created":"2023-09-03T22:01:15Z","citation":{"chicago":"Michalska, Julia M, Julia Lyudchik, Philipp Velicky, Hana Korinkova, Jake Watson, Alban Cenameri, Christoph M Sommer, et al. “Imaging Brain Tissue Architecture across Millimeter to Nanometer Scales.” <i>Nature Biotechnology</i>. Springer Nature, 2023. <a href=\"https://doi.org/10.1038/s41587-023-01911-8\">https://doi.org/10.1038/s41587-023-01911-8</a>.","mla":"Michalska, Julia M., et al. “Imaging Brain Tissue Architecture across Millimeter to Nanometer Scales.” <i>Nature Biotechnology</i>, Springer Nature, 2023, doi:<a href=\"https://doi.org/10.1038/s41587-023-01911-8\">10.1038/s41587-023-01911-8</a>.","ista":"Michalska JM, Lyudchik J, Velicky P, Korinkova H, Watson J, Cenameri A, Sommer CM, Amberg N, Venturino A, Roessler K, Czech T, Höftberger R, Siegert S, Novarino G, Jonas PM, Danzl JG. 2023. Imaging brain tissue architecture across millimeter to nanometer scales. Nature Biotechnology.","short":"J.M. Michalska, J. Lyudchik, P. Velicky, H. Korinkova, J. Watson, A. Cenameri, C.M. Sommer, N. Amberg, A. Venturino, K. Roessler, T. Czech, R. Höftberger, S. Siegert, G. Novarino, P.M. Jonas, J.G. Danzl, Nature Biotechnology (2023).","ieee":"J. M. Michalska <i>et al.</i>, “Imaging brain tissue architecture across millimeter to nanometer scales,” <i>Nature Biotechnology</i>. Springer Nature, 2023.","ama":"Michalska JM, Lyudchik J, Velicky P, et al. Imaging brain tissue architecture across millimeter to nanometer scales. <i>Nature Biotechnology</i>. 2023. doi:<a href=\"https://doi.org/10.1038/s41587-023-01911-8\">10.1038/s41587-023-01911-8</a>","apa":"Michalska, J. M., Lyudchik, J., Velicky, P., Korinkova, H., Watson, J., Cenameri, A., … Danzl, J. G. (2023). Imaging brain tissue architecture across millimeter to nanometer scales. <i>Nature Biotechnology</i>. Springer Nature. <a href=\"https://doi.org/10.1038/s41587-023-01911-8\">https://doi.org/10.1038/s41587-023-01911-8</a>"},"ec_funded":1,"related_material":{"record":[{"id":"13126","relation":"research_data","status":"public"}],"link":[{"url":"https://github.com/danzllab/CATS","relation":"software"}]},"article_type":"original","_id":"14257","acknowledged_ssus":[{"_id":"ScienComp"},{"_id":"Bio"},{"_id":"PreCl"},{"_id":"LifeSc"},{"_id":"M-Shop"},{"_id":"E-Lib"}],"doi":"10.1038/s41587-023-01911-8","publication_status":"epub_ahead","external_id":{"isi":["001065254200001"]},"abstract":[{"text":"Mapping the complex and dense arrangement of cells and their connectivity in brain tissue demands nanoscale spatial resolution imaging. Super-resolution optical microscopy excels at visualizing specific molecules and individual cells but fails to provide tissue context. Here we developed Comprehensive Analysis of Tissues across Scales (CATS), a technology to densely map brain tissue architecture from millimeter regional to nanometer synaptic scales in diverse chemically fixed brain preparations, including rodent and human. CATS uses fixation-compatible extracellular labeling and optical imaging, including stimulated emission depletion or expansion microscopy, to comprehensively delineate cellular structures. It enables three-dimensional reconstruction of single synapses and mapping of synaptic connectivity by identification and analysis of putative synaptic cleft regions. Applying CATS to the mouse hippocampal mossy fiber circuitry, we reconstructed and quantified the synaptic input and output structure of identified neurons. We furthermore demonstrate applicability to clinically derived human tissue samples, including formalin-fixed paraffin-embedded routine diagnostic specimens, for visualizing the cellular architecture of brain tissue in health and disease.","lang":"eng"}],"project":[{"_id":"265CB4D0-B435-11E9-9278-68D0E5697425","grant_number":"I03600","name":"Optical control of synaptic function via adhesion molecules","call_identifier":"FWF"},{"grant_number":"W1232-B24","_id":"2548AE96-B435-11E9-9278-68D0E5697425","name":"Molecular Drug Targets","call_identifier":"FWF"},{"_id":"25C5A090-B435-11E9-9278-68D0E5697425","grant_number":"Z00312","name":"The Wittgenstein Prize","call_identifier":"FWF"},{"name":"High content imaging to decode human immune cell interactions in health and allergic disease","_id":"23889792-32DE-11EA-91FC-C7463DDC885E"},{"grant_number":"715508","_id":"25444568-B435-11E9-9278-68D0E5697425","name":"Probing the Reversibility of Autism Spectrum Disorders by Employing in vivo and in vitro Models","call_identifier":"H2020"},{"grant_number":"692692","_id":"25B7EB9E-B435-11E9-9278-68D0E5697425","name":"Biophysics and circuit function of a giant cortical glumatergic synapse","call_identifier":"H2020"},{"name":"International IST Doctoral Program","call_identifier":"H2020","grant_number":"665385","_id":"2564DBCA-B435-11E9-9278-68D0E5697425"},{"_id":"fc2be41b-9c52-11eb-aca3-faa90aa144e9","grant_number":"101026635","name":"Synaptic computations of the hippocampal CA3 circuitry","call_identifier":"H2020"}],"publisher":"Springer Nature","date_published":"2023-08-31T00:00:00Z","department":[{"_id":"SaSi"},{"_id":"GaNo"},{"_id":"PeJo"},{"_id":"JoDa"},{"_id":"Bio"},{"_id":"RySh"}],"quality_controlled":"1"},{"publication_status":"published","abstract":[{"text":"Markov decision processes can be viewed as transformers of probability distributions. While this view is useful from a practical standpoint to reason about trajectories of distributions, basic reachability and safety problems are known to be computationally intractable (i.e., Skolem-hard) to solve in such models. Further, we show that even for simple examples of MDPs, strategies for safety objectives over distributions can require infinite memory and randomization.\r\nIn light of this, we present a novel overapproximation approach to synthesize strategies in an MDP, such that a safety objective over the distributions is met. More precisely, we develop a new framework for template-based synthesis of certificates as affine distributional and inductive invariants for safety objectives in MDPs. We provide two algorithms within this framework. One can only synthesize memoryless strategies, but has relative completeness guarantees, while the other can synthesize general strategies. The runtime complexity of both algorithms is in PSPACE. We implement these algorithms and show that they can solve several non-trivial examples.","lang":"eng"}],"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"},"ddc":["000"],"project":[{"_id":"2564DBCA-B435-11E9-9278-68D0E5697425","grant_number":"665385","call_identifier":"H2020","name":"International IST Doctoral Program"},{"name":"Formal Methods for Stochastic Models: Algorithms and Applications","call_identifier":"H2020","_id":"0599E47C-7A3F-11EA-A408-12923DDC885E","grant_number":"863818"}],"volume":13966,"quality_controlled":"1","page":"86-112","department":[{"_id":"KrCh"}],"date_published":"2023-07-17T00:00:00Z","publisher":"Springer Nature","citation":{"apa":"Akshay, S., Chatterjee, K., Meggendorfer, T., &#38; Zikelic, D. (2023). MDPs as distribution transformers: Affine invariant synthesis for safety objectives. In <i>International Conference on Computer Aided Verification</i> (Vol. 13966, pp. 86–112). Paris, France: Springer Nature. <a href=\"https://doi.org/10.1007/978-3-031-37709-9_5\">https://doi.org/10.1007/978-3-031-37709-9_5</a>","ama":"Akshay S, Chatterjee K, Meggendorfer T, Zikelic D. MDPs as distribution transformers: Affine invariant synthesis for safety objectives. In: <i>International Conference on Computer Aided Verification</i>. Vol 13966. Springer Nature; 2023:86-112. doi:<a href=\"https://doi.org/10.1007/978-3-031-37709-9_5\">10.1007/978-3-031-37709-9_5</a>","ieee":"S. Akshay, K. Chatterjee, T. Meggendorfer, and D. Zikelic, “MDPs as distribution transformers: Affine invariant synthesis for safety objectives,” in <i>International Conference on Computer Aided Verification</i>, Paris, France, 2023, vol. 13966, pp. 86–112.","short":"S. Akshay, K. Chatterjee, T. Meggendorfer, D. Zikelic, in:, International Conference on Computer Aided Verification, Springer Nature, 2023, pp. 86–112.","ista":"Akshay S, Chatterjee K, Meggendorfer T, Zikelic D. 2023. MDPs as distribution transformers: Affine invariant synthesis for safety objectives. International Conference on Computer Aided Verification. CAV: Computer Aided Verification, LNCS, vol. 13966, 86–112.","chicago":"Akshay, S., Krishnendu Chatterjee, Tobias Meggendorfer, and Dorde Zikelic. “MDPs as Distribution Transformers: Affine Invariant Synthesis for Safety Objectives.” In <i>International Conference on Computer Aided Verification</i>, 13966:86–112. Springer Nature, 2023. <a href=\"https://doi.org/10.1007/978-3-031-37709-9_5\">https://doi.org/10.1007/978-3-031-37709-9_5</a>.","mla":"Akshay, S., et al. “MDPs as Distribution Transformers: Affine Invariant Synthesis for Safety Objectives.” <i>International Conference on Computer Aided Verification</i>, vol. 13966, Springer Nature, 2023, pp. 86–112, doi:<a href=\"https://doi.org/10.1007/978-3-031-37709-9_5\">10.1007/978-3-031-37709-9_5</a>."},"date_created":"2023-09-10T22:01:12Z","year":"2023","acknowledgement":"This work was supported in part by the ERC CoG 863818 (FoRM-SMArt) and the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 665385 as well as DST/CEFIPRA/INRIA project EQuaVE and SERB Matrices grant MTR/2018/00074.","ec_funded":1,"_id":"14317","file_date_updated":"2023-09-20T08:46:43Z","doi":"10.1007/978-3-031-37709-9_5","author":[{"full_name":"Akshay, S.","first_name":"S.","last_name":"Akshay"},{"first_name":"Krishnendu","full_name":"Chatterjee, Krishnendu","id":"2E5DCA20-F248-11E8-B48F-1D18A9856A87","last_name":"Chatterjee","orcid":"0000-0002-4561-241X"},{"orcid":"0000-0002-1712-2165","id":"b21b0c15-30a2-11eb-80dc-f13ca25802e1","last_name":"Meggendorfer","first_name":"Tobias","full_name":"Meggendorfer, Tobias"},{"first_name":"Dorde","full_name":"Zikelic, Dorde","last_name":"Zikelic","id":"294AA7A6-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-4681-1699"}],"file":[{"success":1,"checksum":"f143c8eedf609f20f2aad2eeb496d53f","file_name":"2023_LNCS_Akshay.pdf","file_id":"14349","date_created":"2023-09-20T08:46:43Z","date_updated":"2023-09-20T08:46:43Z","creator":"dernst","content_type":"application/pdf","access_level":"open_access","file_size":531745,"relation":"main_file"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","day":"17","oa_version":"Published Version","month":"07","publication_identifier":{"eissn":["1611-3349"],"isbn":["9783031377082"],"issn":["0302-9743"]},"conference":{"end_date":"2023-07-22","location":"Paris, France","start_date":"2023-07-17","name":"CAV: Computer Aided Verification"},"type":"conference","status":"public","alternative_title":["LNCS"],"title":"MDPs as distribution transformers: Affine invariant synthesis for safety objectives","article_processing_charge":"Yes (in subscription journal)","date_updated":"2025-07-14T09:09:56Z","oa":1,"intvolume":"     13966","has_accepted_license":"1","scopus_import":"1","language":[{"iso":"eng"}],"publication":"International Conference on Computer Aided Verification"}]