{"id":"https://openalex.org/W4386953658","doi":"https://doi.org/10.1371/journal.pcbi.1011406","title":"Simulation-based inference for efficient identification of generative models in computational connectomics","display_name":"Simulation-based inference for efficient identification of generative models in computational connectomics","publication_year":2023,"publication_date":"2023-09-22","ids":{"openalex":"https://openalex.org/W4386953658","doi":"https://doi.org/10.1371/journal.pcbi.1011406","pmid":"https://pubmed.ncbi.nlm.nih.gov/37738260"},"language":"en","primary_location":{"id":"doi:10.1371/journal.pcbi.1011406","is_oa":true,"landing_page_url":"https://doi.org/10.1371/journal.pcbi.1011406","pdf_url":null,"source":{"id":"https://openalex.org/S86033158","display_name":"PLoS Computational Biology","issn_l":"1553-734X","issn":["1553-734X","1553-7358"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310315706","host_organization_name":"Public Library of Science","host_organization_lineage":["https://openalex.org/P4310315706"],"host_organization_lineage_names":["Public Library of Science"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"PLOS Computational Biology","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1371/journal.pcbi.1011406","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5055129584","display_name":"Jan Boelts","orcid":"https://orcid.org/0000-0003-4979-7092"},"institutions":[{"id":"https://openalex.org/I8087733","display_name":"University of T\u00fcbingen","ror":"https://ror.org/03a1kwz48","country_code":"DE","type":"education","lineage":["https://openalex.org/I8087733"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Jan Boelts","raw_affiliation_strings":["Machine Learning in Science, University of T\u00fcbingen, T\u00fcbingen, Germany","T\u00fcbingen AI Center, University of T\u00fcbingen, T\u00fcbingen, Germany"],"raw_orcid":"https://orcid.org/0000-0003-4979-7092","affiliations":[{"raw_affiliation_string":"Machine Learning in Science, University of T\u00fcbingen, T\u00fcbingen, Germany","institution_ids":["https://openalex.org/I8087733"]},{"raw_affiliation_string":"T\u00fcbingen AI Center, University of T\u00fcbingen, T\u00fcbingen, Germany","institution_ids":["https://openalex.org/I8087733"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038134800","display_name":"Philipp Harth","orcid":"https://orcid.org/0000-0001-8831-3893"},"institutions":[{"id":"https://openalex.org/I195893171","display_name":"Zuse Institute Berlin","ror":"https://ror.org/02eva5865","country_code":"DE","type":"facility","lineage":["https://openalex.org/I195893171"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Philipp Harth","raw_affiliation_strings":["Department of Visual and Data-centric Computing, Zuse Institute Berlin, Berlin, Germany"],"raw_orcid":"https://orcid.org/0000-0001-8831-3893","affiliations":[{"raw_affiliation_string":"Department of Visual and Data-centric Computing, Zuse Institute Berlin, Berlin, Germany","institution_ids":["https://openalex.org/I195893171"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026158316","display_name":"Richard Gao","orcid":"https://orcid.org/0000-0001-5916-6433"},"institutions":[{"id":"https://openalex.org/I8087733","display_name":"University of T\u00fcbingen","ror":"https://ror.org/03a1kwz48","country_code":"DE","type":"education","lineage":["https://openalex.org/I8087733"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Richard Gao","raw_affiliation_strings":["Machine Learning in Science, University of T\u00fcbingen, T\u00fcbingen, Germany","T\u00fcbingen AI Center, University of T\u00fcbingen, T\u00fcbingen, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Machine Learning in Science, University of T\u00fcbingen, T\u00fcbingen, Germany","institution_ids":["https://openalex.org/I8087733"]},{"raw_affiliation_string":"T\u00fcbingen AI Center, University of T\u00fcbingen, T\u00fcbingen, Germany","institution_ids":["https://openalex.org/I8087733"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037017210","display_name":"Daniel Udvary","orcid":"https://orcid.org/0000-0002-8697-3975"},"institutions":[{"id":"https://openalex.org/I2800451603","display_name":"Center of Advanced European Studies and Research","ror":"https://ror.org/05350h943","country_code":"DE","type":"facility","lineage":["https://openalex.org/I2800451603"]},{"id":"https://openalex.org/I4210127408","display_name":"Max Planck Institute for Brain Research","ror":"https://ror.org/02h1nk258","country_code":"DE","type":"facility","lineage":["https://openalex.org/I149899117","https://openalex.org/I4210127408"]},{"id":"https://openalex.org/I4387152376","display_name":"Max Planck Institute for Neurobiology of Behavior \u2013 caesar","ror":"https://ror.org/02yjyfs84","country_code":"DE","type":"facility","lineage":["https://openalex.org/I149899117","https://openalex.org/I4387152376"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Daniel Udvary","raw_affiliation_strings":["In Silico Brain Sciences, Max Planck Institute for Neurobiology of Behavior - caesar, Bonn, Germany","In Silico Brain Sciences, Max Planck Institute for Neurobiology of Behavior \u2013 caesar, Bonn, Germany"],"raw_orcid":"https://orcid.org/0000-0002-8697-3975","affiliations":[{"raw_affiliation_string":"In Silico Brain Sciences, Max Planck Institute for Neurobiology of Behavior - caesar, Bonn, Germany","institution_ids":["https://openalex.org/I4210127408","https://openalex.org/I2800451603"]},{"raw_affiliation_string":"In Silico Brain Sciences, Max Planck Institute for Neurobiology of Behavior \u2013 caesar, Bonn, Germany","institution_ids":["https://openalex.org/I4387152376"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069435084","display_name":"Felipe Y\u00e1\u00f1ez","orcid":"https://orcid.org/0000-0002-9598-0616"},"institutions":[{"id":"https://openalex.org/I2800451603","display_name":"Center of Advanced European Studies and Research","ror":"https://ror.org/05350h943","country_code":"DE","type":"facility","lineage":["https://openalex.org/I2800451603"]},{"id":"https://openalex.org/I4210127408","display_name":"Max Planck Institute for Brain Research","ror":"https://ror.org/02h1nk258","country_code":"DE","type":"facility","lineage":["https://openalex.org/I149899117","https://openalex.org/I4210127408"]},{"id":"https://openalex.org/I4387152376","display_name":"Max Planck Institute for Neurobiology of Behavior \u2013 caesar","ror":"https://ror.org/02yjyfs84","country_code":"DE","type":"facility","lineage":["https://openalex.org/I149899117","https://openalex.org/I4387152376"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Felipe Y\u00e1\u00f1ez","raw_affiliation_strings":["In Silico Brain Sciences, Max Planck Institute for Neurobiology of Behavior - caesar, Bonn, Germany","In Silico Brain Sciences, Max Planck Institute for Neurobiology of Behavior \u2013 caesar, Bonn, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"In Silico Brain Sciences, Max Planck Institute for Neurobiology of Behavior - caesar, Bonn, Germany","institution_ids":["https://openalex.org/I4210127408","https://openalex.org/I2800451603"]},{"raw_affiliation_string":"In Silico Brain Sciences, Max Planck Institute for Neurobiology of Behavior \u2013 caesar, Bonn, Germany","institution_ids":["https://openalex.org/I4387152376"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012693590","display_name":"Daniel Baum","orcid":"https://orcid.org/0000-0003-1550-7245"},"institutions":[{"id":"https://openalex.org/I195893171","display_name":"Zuse Institute Berlin","ror":"https://ror.org/02eva5865","country_code":"DE","type":"facility","lineage":["https://openalex.org/I195893171"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Daniel Baum","raw_affiliation_strings":["Department of Visual and Data-centric Computing, Zuse Institute Berlin, Berlin, Germany"],"raw_orcid":"https://orcid.org/0000-0003-1550-7245","affiliations":[{"raw_affiliation_string":"Department of Visual and Data-centric Computing, Zuse Institute Berlin, Berlin, Germany","institution_ids":["https://openalex.org/I195893171"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091630951","display_name":"Hans\u2010Christian Hege","orcid":"https://orcid.org/0000-0002-6574-0988"},"institutions":[{"id":"https://openalex.org/I195893171","display_name":"Zuse Institute Berlin","ror":"https://ror.org/02eva5865","country_code":"DE","type":"facility","lineage":["https://openalex.org/I195893171"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Hans-Christian Hege","raw_affiliation_strings":["Department of Visual and Data-centric Computing, Zuse Institute Berlin, Berlin, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Visual and Data-centric Computing, Zuse Institute Berlin, Berlin, Germany","institution_ids":["https://openalex.org/I195893171"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075878858","display_name":"Marcel Oberlaender","orcid":"https://orcid.org/0000-0001-9011-0630"},"institutions":[{"id":"https://openalex.org/I2800451603","display_name":"Center of Advanced European Studies and Research","ror":"https://ror.org/05350h943","country_code":"DE","type":"facility","lineage":["https://openalex.org/I2800451603"]},{"id":"https://openalex.org/I4210127408","display_name":"Max Planck Institute for Brain Research","ror":"https://ror.org/02h1nk258","country_code":"DE","type":"facility","lineage":["https://openalex.org/I149899117","https://openalex.org/I4210127408"]},{"id":"https://openalex.org/I4387152376","display_name":"Max Planck Institute for Neurobiology of Behavior \u2013 caesar","ror":"https://ror.org/02yjyfs84","country_code":"DE","type":"facility","lineage":["https://openalex.org/I149899117","https://openalex.org/I4387152376"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Marcel Oberlaender","raw_affiliation_strings":["Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, Free University Amsterdam, Amsterdam, Netherlands","In Silico Brain Sciences, Max Planck Institute for Neurobiology of Behavior - caesar, Bonn, Germany","In Silico Brain Sciences, Max Planck Institute for Neurobiology of Behavior \u2013 caesar, Bonn, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, Free University Amsterdam, Amsterdam, Netherlands","institution_ids":[]},{"raw_affiliation_string":"In Silico Brain Sciences, Max Planck Institute for Neurobiology of Behavior - caesar, Bonn, Germany","institution_ids":["https://openalex.org/I4210127408","https://openalex.org/I2800451603"]},{"raw_affiliation_string":"In Silico Brain Sciences, Max Planck Institute for Neurobiology of Behavior \u2013 caesar, Bonn, Germany","institution_ids":["https://openalex.org/I4387152376"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080225154","display_name":"Jakob H. Macke","orcid":"https://orcid.org/0000-0001-5154-8912"},"institutions":[{"id":"https://openalex.org/I4210135521","display_name":"Max Planck Institute for Intelligent Systems","ror":"https://ror.org/04fq9j139","country_code":"DE","type":"facility","lineage":["https://openalex.org/I149899117","https://openalex.org/I4210135521"]},{"id":"https://openalex.org/I8087733","display_name":"University of T\u00fcbingen","ror":"https://ror.org/03a1kwz48","country_code":"DE","type":"education","lineage":["https://openalex.org/I8087733"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Jakob H. Macke","raw_affiliation_strings":["Empirical Inference, Max Planck Institute for Intelligent Systems, T\u00fcbingen, Germany","Machine Learning in Science, University of T\u00fcbingen, T\u00fcbingen, Germany","T\u00fcbingen AI Center, University of T\u00fcbingen, T\u00fcbingen, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Empirical Inference, Max Planck Institute for Intelligent Systems, T\u00fcbingen, Germany","institution_ids":["https://openalex.org/I4210135521"]},{"raw_affiliation_string":"Machine Learning in Science, University of T\u00fcbingen, T\u00fcbingen, Germany","institution_ids":["https://openalex.org/I8087733"]},{"raw_affiliation_string":"T\u00fcbingen AI Center, University of T\u00fcbingen, T\u00fcbingen, Germany","institution_ids":["https://openalex.org/I8087733"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5012693590","https://openalex.org/A5026158316","https://openalex.org/A5037017210","https://openalex.org/A5038134800","https://openalex.org/A5055129584","https://openalex.org/A5069435084","https://openalex.org/A5075878858","https://openalex.org/A5080225154","https://openalex.org/A5091630951"],"corresponding_institution_ids":["https://openalex.org/I195893171","https://openalex.org/I2800451603","https://openalex.org/I4210127408","https://openalex.org/I4210135521","https://openalex.org/I4387152376","https://openalex.org/I8087733"],"apc_list":{"value":2655,"currency":"USD","value_usd":2655},"apc_paid":{"value":2655,"currency":"USD","value_usd":2655},"fwci":1.5364,"has_fulltext":true,"cited_by_count":9,"citation_normalized_percentile":{"value":0.82351235,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"19","issue":"9","first_page":"e1011406","last_page":"e1011406"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10581","display_name":"Neural dynamics and brain function","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10581","display_name":"Neural dynamics and brain function","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10044","display_name":"Protein Structure and Dynamics","score":0.9934999942779541,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10241","display_name":"Functional Brain Connectivity Studies","score":0.9916999936103821,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/connectomics","display_name":"Connectomics","score":0.8439909219741821},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7584408521652222},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6920835971832275},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.5500468611717224},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.5365187525749207},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4927974045276642},{"id":"https://openalex.org/keywords/bayes-theorem","display_name":"Bayes' theorem","score":0.47524356842041016},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.46982693672180176},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.45901456475257874},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.449318528175354},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.44449248909950256},{"id":"https://openalex.org/keywords/approximate-bayesian-computation","display_name":"Approximate Bayesian computation","score":0.44128525257110596},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.41548240184783936},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.29114893078804016},{"id":"https://openalex.org/keywords/connectome","display_name":"Connectome","score":0.26436060667037964}],"concepts":[{"id":"https://openalex.org/C2779097318","wikidata":"https://www.wikidata.org/wiki/Q2993446","display_name":"Connectomics","level":4,"score":0.8439909219741821},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7584408521652222},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6920835971832275},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.5500468611717224},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.5365187525749207},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4927974045276642},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.47524356842041016},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46982693672180176},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.45901456475257874},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.449318528175354},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.44449248909950256},{"id":"https://openalex.org/C2779377595","wikidata":"https://www.wikidata.org/wiki/Q21045424","display_name":"Approximate Bayesian computation","level":3,"score":0.44128525257110596},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.41548240184783936},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.29114893078804016},{"id":"https://openalex.org/C45715564","wikidata":"https://www.wikidata.org/wiki/Q1292103","display_name":"Connectome","level":3,"score":0.26436060667037964},{"id":"https://openalex.org/C3018011982","wikidata":"https://www.wikidata.org/wiki/Q7316120","display_name":"Functional connectivity","level":2,"score":0.0},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000818","descriptor_name":"Animals","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000818","descriptor_name":"Animals","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000818","descriptor_name":"Animals","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001499","descriptor_name":"Bayes Theorem","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001499","descriptor_name":"Bayes Theorem","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001499","descriptor_name":"Bayes Theorem","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003198","descriptor_name":"Computer Simulation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003198","descriptor_name":"Computer Simulation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003198","descriptor_name":"Computer Simulation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D009474","descriptor_name":"Neurons","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":false},{"descriptor_ui":"D009474","descriptor_name":"Neurons","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":false},{"descriptor_ui":"D009474","descriptor_name":"Neurons","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":false},{"descriptor_ui":"D051381","descriptor_name":"Rats","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D051381","descriptor_name":"Rats","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D051381","descriptor_name":"Rats","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D063132","descriptor_name":"Connectome","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D063132","descriptor_name":"Connectome","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D063132","descriptor_name":"Connectome","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true}],"locations_count":7,"locations":[{"id":"doi:10.1371/journal.pcbi.1011406","is_oa":true,"landing_page_url":"https://doi.org/10.1371/journal.pcbi.1011406","pdf_url":null,"source":{"id":"https://openalex.org/S86033158","display_name":"PLoS Computational Biology","issn_l":"1553-734X","issn":["1553-734X","1553-7358"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310315706","host_organization_name":"Public Library of Science","host_organization_lineage":["https://openalex.org/P4310315706"],"host_organization_lineage_names":["Public Library of Science"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"PLOS Computational Biology","raw_type":"journal-article"},{"id":"pmid:37738260","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37738260","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"PLoS computational biology","raw_type":null},{"id":"pmh:oai:research.vu.nl:openaire/2f76f991-8b80-4d51-84cf-b90b1f9ef37b","is_oa":true,"landing_page_url":"https://research.vu.nl/en/publications/2f76f991-8b80-4d51-84cf-b90b1f9ef37b","pdf_url":null,"source":{"id":"https://openalex.org/S4306401107","display_name":"VU Research Portal","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I865915315","host_organization_name":"Vrije Universiteit Amsterdam","host_organization_lineage":["https://openalex.org/I865915315"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Boelts, J, Harth, P, Gao, R, Udvary, D, Y\u00e1\u00f1ez, F, Baum, D, Hege, H C, Oberlaender, M & Macke, J H 2023, 'Simulation-based inference for efficient identification of generative models in computational connectomics', PLoS Computational Biology, vol. 19, no. 9, e1011406, pp. 1-28. https://doi.org/10.1371/journal.pcbi.1011406","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:pubmedcentral.nih.gov:10550169","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/10550169","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC10550169/pdf/pcbi.1011406.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"PLoS Comput Biol","raw_type":"Text"},{"id":"pmh:oai:RePEc:plo:pcbi00:1011406","is_oa":false,"landing_page_url":"https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1011406","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},{"id":"pmh:oai:doaj.org/article:9ebf71dcc8994f13a10da94b297b793c","is_oa":true,"landing_page_url":"https://doaj.org/article/9ebf71dcc8994f13a10da94b297b793c","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"PLoS Computational Biology, Vol 19, Iss 9, p e1011406 (2023)","raw_type":"article"},{"id":"pmh:oai:research.vu.nl:openaire_cris_publications/2f76f991-8b80-4d51-84cf-b90b1f9ef37b","is_oa":true,"landing_page_url":"https://hdl.handle.net/1871.1/2f76f991-8b80-4d51-84cf-b90b1f9ef37b","pdf_url":null,"source":{"id":"https://openalex.org/S4306401107","display_name":"VU Research Portal","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I865915315","host_organization_name":"Vrije Universiteit Amsterdam","host_organization_lineage":["https://openalex.org/I865915315"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Boelts, J, Harth, P, Gao, R, Udvary, D, Y\u00e1\u00f1ez, F, Baum, D, Hege, H C, Oberlaender, M & Macke, J H 2023, 'Simulation-based inference for efficient identification of generative models in computational connectomics', PLoS Computational Biology, vol. 19, no. 9, e1011406, pp. 1-28. https://doi.org/10.1371/journal.pcbi.1011406","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":{"id":"doi:10.1371/journal.pcbi.1011406","is_oa":true,"landing_page_url":"https://doi.org/10.1371/journal.pcbi.1011406","pdf_url":null,"source":{"id":"https://openalex.org/S86033158","display_name":"PLoS Computational Biology","issn_l":"1553-734X","issn":["1553-734X","1553-7358"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310315706","host_organization_name":"Public Library of Science","host_organization_lineage":["https://openalex.org/P4310315706"],"host_organization_lineage_names":["Public Library of Science"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"PLOS Computational Biology","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1572799848","display_name":null,"funder_award_id":"633428","funder_id":"https://openalex.org/F4320338337","funder_display_name":"H2020 Marie Sk\u0142odowska-Curie Actions"},{"id":"https://openalex.org/G4150511369","display_name":null,"funder_award_id":"FKZ 01GQ1002","funder_id":"https://openalex.org/F4320321114","funder_display_name":"Bundesministerium f\u00fcr Bildung und Forschung"},{"id":"https://openalex.org/G4514252537","display_name":"Reverse engineering sensory perception and decision making: bridging physiology, anatomy and behavior","funder_award_id":"633428","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G4568914905","display_name":null,"funder_award_id":"01IS18052","funder_id":"https://openalex.org/F4320321114","funder_display_name":"Bundesministerium f\u00fcr Bildung und Forschung"},{"id":"https://openalex.org/G4672631619","display_name":null,"funder_award_id":"SFB 1089","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"},{"id":"https://openalex.org/G5175512232","display_name":null,"funder_award_id":"01GQ1002","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G5415233182","display_name":null,"funder_award_id":"01IS18039A","funder_id":"https://openalex.org/F4320321114","funder_display_name":"Bundesministerium f\u00fcr Bildung und Forschung"},{"id":"https://openalex.org/G5534580418","display_name":null,"funder_award_id":"FKZ 01IS18039A","funder_id":"https://openalex.org/F4320321114","funder_display_name":"Bundesministerium f\u00fcr Bildung und Forschung"},{"id":"https://openalex.org/G5577881020","display_name":null,"funder_award_id":"project SiMaLeSAM, FKZ 01IS21055A and T\u00fcbingen AI Center, FKZ 01IS18039A","funder_id":"https://openalex.org/F4320321114","funder_display_name":"Bundesministerium f\u00fcr Bildung und Forschung"},{"id":"https://openalex.org/G6685893338","display_name":"Automated Model Inference from Neural Dynamics for a Mechanistic Understanding of Cognition","funder_award_id":"101030918","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G7237385214","display_name":null,"funder_award_id":"SPP 2041","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"},{"id":"https://openalex.org/G7842005466","display_name":null,"funder_award_id":"Horizon 2020","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G7907426250","display_name":null,"funder_award_id":"390727645","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"},{"id":"https://openalex.org/G8063013204","display_name":null,"funder_award_id":"01GQ1002","funder_id":"https://openalex.org/F4320321114","funder_display_name":"Bundesministerium f\u00fcr Bildung und Forschung"},{"id":"https://openalex.org/G8263575055","display_name":null,"funder_award_id":"SPP 2041 PN 34721065; Germany\u2019s Excellence Strategy MLCoE-EXC number 2064/1 PN 390727645","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"},{"id":"https://openalex.org/G8329838592","display_name":null,"funder_award_id":"PN 390727645","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"},{"id":"https://openalex.org/G8909454090","display_name":"Automated Model Inference from Neural Dynamics for a Mechanistic Understanding of Cognition","funder_award_id":"101030918","funder_id":"https://openalex.org/F4320338337","funder_display_name":"H2020 Marie Sk\u0142odowska-Curie Actions"},{"id":"https://openalex.org/G8915364236","display_name":null,"funder_award_id":"2064/1","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"}],"funders":[{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"},{"id":"https://openalex.org/F4320320879","display_name":"Deutsche Forschungsgemeinschaft","ror":"https://ror.org/018mejw64"},{"id":"https://openalex.org/F4320321114","display_name":"Bundesministerium f\u00fcr Bildung und Forschung","ror":"https://ror.org/04pz7b180"},{"id":"https://openalex.org/F4320338337","display_name":"H2020 Marie Sk\u0142odowska-Curie Actions","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":95,"referenced_works":["https://openalex.org/W1513082520","https://openalex.org/W1518747218","https://openalex.org/W1566179300","https://openalex.org/W1579853615","https://openalex.org/W1583837637","https://openalex.org/W1962710288","https://openalex.org/W1987521590","https://openalex.org/W2006700032","https://openalex.org/W2026981426","https://openalex.org/W2032841135","https://openalex.org/W2041918412","https://openalex.org/W2055139905","https://openalex.org/W2061490418","https://openalex.org/W2067392831","https://openalex.org/W2071187610","https://openalex.org/W2101950425","https://openalex.org/W2106948112","https://openalex.org/W2113197787","https://openalex.org/W2114538750","https://openalex.org/W2117144089","https://openalex.org/W2118050239","https://openalex.org/W2132620577","https://openalex.org/W2139053813","https://openalex.org/W2140195253","https://openalex.org/W2146693559","https://openalex.org/W2151729750","https://openalex.org/W2152246075","https://openalex.org/W2182367256","https://openalex.org/W2559655401","https://openalex.org/W2562589097","https://openalex.org/W2612690371","https://openalex.org/W2738150700","https://openalex.org/W2741541701","https://openalex.org/W2766819726","https://openalex.org/W2781708744","https://openalex.org/W2797452937","https://openalex.org/W2801490189","https://openalex.org/W2802399484","https://openalex.org/W2807503652","https://openalex.org/W2895152177","https://openalex.org/W2963284032","https://openalex.org/W2963306315","https://openalex.org/W2963742597","https://openalex.org/W2970331231","https://openalex.org/W2976347345","https://openalex.org/W2982268628","https://openalex.org/W2992035660","https://openalex.org/W3009954736","https://openalex.org/W3018228603","https://openalex.org/W3027507201","https://openalex.org/W3031514878","https://openalex.org/W3081344392","https://openalex.org/W3087344693","https://openalex.org/W3094576540","https://openalex.org/W3096195703","https://openalex.org/W3100636956","https://openalex.org/W3129727011","https://openalex.org/W3150807214","https://openalex.org/W3157094080","https://openalex.org/W3163824856","https://openalex.org/W3170914969","https://openalex.org/W3176256066","https://openalex.org/W3185216564","https://openalex.org/W3186956811","https://openalex.org/W3189506822","https://openalex.org/W3202234921","https://openalex.org/W3213412084","https://openalex.org/W4212774754","https://openalex.org/W4213435196","https://openalex.org/W4213455879","https://openalex.org/W4225897185","https://openalex.org/W4225922149","https://openalex.org/W4226024614","https://openalex.org/W4245626742","https://openalex.org/W4250394585","https://openalex.org/W4281700741","https://openalex.org/W4281779047","https://openalex.org/W4281791353","https://openalex.org/W4281842027","https://openalex.org/W4283328497","https://openalex.org/W4285044781","https://openalex.org/W4287778440","https://openalex.org/W4288050765","https://openalex.org/W4288350962","https://openalex.org/W4293343253","https://openalex.org/W4297632441","https://openalex.org/W4303454044","https://openalex.org/W4307188633","https://openalex.org/W4308748732","https://openalex.org/W4310895557","https://openalex.org/W4321498060","https://openalex.org/W4378474129","https://openalex.org/W4394649545","https://openalex.org/W6601363074","https://openalex.org/W6769913903"],"related_works":["https://openalex.org/W2807503652","https://openalex.org/W2212379672","https://openalex.org/W2424680827","https://openalex.org/W2079675757","https://openalex.org/W2912524409","https://openalex.org/W4376988852","https://openalex.org/W4296551294","https://openalex.org/W4296960511","https://openalex.org/W3101955189","https://openalex.org/W4366999383"],"abstract_inverted_index":{"Recent":[0],"advances":[1],"in":[2,52,180,190,192,201,280],"connectomics":[3,182],"research":[4],"enable":[5],"the":[6,14,34,59,115,131,137,167,185,196,216,223],"acquisition":[7],"of":[8,11,17,25,122,187,195,210,276],"increasing":[9],"amounts":[10],"data":[12,26,62,82,142],"about":[13,33],"connectivity":[15,203,294],"patterns":[16],"neurons.":[18],"How":[19],"can":[20,83,251],"we":[21,94],"use":[22,97],"this":[23,104],"wealth":[24],"to":[27,43,57,96,102,113,129,155,177,222,232,254,261,272,288],"efficiently":[28],"derive":[29],"and":[30,56,76,125,149,241,285],"test":[31],"hypotheses":[32],"principles":[35],"underlying":[36],"these":[37],"patterns?":[38],"A":[39],"common":[40],"approach":[41,269],"is":[42,270],"simulate":[44],"neuronal":[45],"networks":[46],"using":[47],"a":[48,53,109,123,157,207,273,283],"hypothesized":[49],"wiring":[50,68,111,146,188,211,255,266],"rule":[51,112,124,147,212,263],"generative":[54,277],"model":[55,194,290],"compare":[58],"resulting":[60],"synthetic":[61],"with":[63,136,292],"empirical":[64,81,116,293],"data.":[65,138,295],"However,":[66],"most":[67],"rules":[69,189,256],"have":[70],"at":[71,257],"least":[72],"some":[73],"free":[74],"parameters,":[75],"identifying":[77],"parameters":[78,132,148,164,186,213,229,291],"that":[79,133,169,214],"reproduce":[80,215],"be":[84,252],"challenging":[85],"as":[86],"it":[87],"often":[88],"requires":[89],"manual":[90],"parameter":[91,239],"tuning.":[92],"Here,":[93],"propose":[95],"simulation-based":[98],"Bayesian":[99,127],"inference":[100,128],"(SBI)":[101],"address":[103],"challenge.":[105],"Rather":[106],"than":[107],"optimizing":[108],"fixed":[110],"fit":[114],"data,":[117],"SBI":[118,179,205,250],"considers":[119],"many":[120],"parametrizations":[121],"performs":[126],"identify":[130],"are":[134],"compatible":[135],"It":[139],"uses":[140],"simulated":[141],"from":[143],"multiple":[144],"candidate":[145],"relies":[150],"on":[151,166],"machine":[152],"learning":[153],"methods":[154],"estimate":[156],"probability":[158],"distribution":[159,162,225],"(the":[160],"'posterior":[161],"over":[163,226],"conditioned":[165],"data')":[168],"characterizes":[170],"all":[171,227],"data-compatible":[172,228],"parameters.":[173],"We":[174,218,246],"demonstrate":[175],"how":[176,220,249],"apply":[178],"computational":[181],"by":[183],"inferring":[184],"an":[191],"silico":[193],"rat":[197],"barrel":[198],"cortex,":[199],"given":[200],"vivo":[202],"measurements.":[204,217],"identifies":[206],"wide":[208,274],"range":[209,275],"show":[219,248],"access":[221],"posterior":[224],"allows":[230],"us":[231],"analyze":[233],"their":[234],"relationship,":[235],"revealing":[236],"biologically":[237],"plausible":[238],"interactions":[240],"enabling":[242],"experimentally":[243],"testable":[244],"predictions.":[245],"further":[247],"applied":[253],"different":[258],"spatial":[259],"scales":[260],"quantitatively":[262],"out":[264],"invalid":[265],"hypotheses.":[267],"Our":[268],"applicable":[271],"models":[278],"used":[279],"connectomics,":[281],"providing":[282],"quantitative":[284],"efficient":[286],"way":[287],"constrain":[289]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":1}],"updated_date":"2026-05-05T08:41:31.759640","created_date":"2025-10-10T00:00:00"}