{"id":"https://openalex.org/W1975212040","doi":"https://doi.org/10.1109/acssc.2013.6810293","title":"Bayesian spike inference from calcium imaging data","display_name":"Bayesian spike inference from calcium imaging data","publication_year":2013,"publication_date":"2013-11-01","ids":{"openalex":"https://openalex.org/W1975212040","doi":"https://doi.org/10.1109/acssc.2013.6810293","mag":"1975212040"},"language":"en","primary_location":{"id":"doi:10.1109/acssc.2013.6810293","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acssc.2013.6810293","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 Asilomar Conference on Signals, Systems and Computers","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5054955073","display_name":"Eftychios A. Pnevmatikakis","orcid":"https://orcid.org/0000-0003-1509-6394"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Eftychios A. Pnevmatikakis","raw_affiliation_strings":["Department of Statistics, Columbia University, New York, NY","Department of Statistics, Center for Theoretical Neuroscience, Grossman Center for the Statistics of Mind, Columbia University, New York, NY"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, Columbia University, New York, NY","institution_ids":["https://openalex.org/I78577930"]},{"raw_affiliation_string":"Department of Statistics, Center for Theoretical Neuroscience, Grossman Center for the Statistics of Mind, Columbia University, New York, NY","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080814522","display_name":"Josh Merel","orcid":null},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Josh Merel","raw_affiliation_strings":["Department of Statistics, Columbia University, New York, NY","Department of Statistics, Center for Theoretical Neuroscience, Grossman Center for the Statistics of Mind, Columbia University, New York, NY"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, Columbia University, New York, NY","institution_ids":["https://openalex.org/I78577930"]},{"raw_affiliation_string":"Department of Statistics, Center for Theoretical Neuroscience, Grossman Center for the Statistics of Mind, Columbia University, New York, NY","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013659514","display_name":"Ari Pakman","orcid":"https://orcid.org/0000-0001-8047-2240"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ari Pakman","raw_affiliation_strings":["Department of Statistics, Columbia University, New York, NY","Department of Statistics, Center for Theoretical Neuroscience, Grossman Center for the Statistics of Mind, Columbia University, New York, NY"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, Columbia University, New York, NY","institution_ids":["https://openalex.org/I78577930"]},{"raw_affiliation_string":"Department of Statistics, Center for Theoretical Neuroscience, Grossman Center for the Statistics of Mind, Columbia University, New York, NY","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023278055","display_name":"Liam Paninski","orcid":"https://orcid.org/0000-0002-0276-7032"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Liam Paninski","raw_affiliation_strings":["Department of Statistics, Columbia University, New York, NY","Department of Statistics, Center for Theoretical Neuroscience, Grossman Center for the Statistics of Mind, Columbia University, New York, NY"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, Columbia University, New York, NY","institution_ids":["https://openalex.org/I78577930"]},{"raw_affiliation_string":"Department of Statistics, Center for Theoretical Neuroscience, Grossman Center for the Statistics of Mind, Columbia University, New York, NY","institution_ids":["https://openalex.org/I78577930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5054955073"],"corresponding_institution_ids":["https://openalex.org/I78577930"],"apc_list":null,"apc_paid":null,"fwci":1.2436,"has_fulltext":false,"cited_by_count":72,"citation_normalized_percentile":{"value":0.77684683,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"349","last_page":"353"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10581","display_name":"Neural dynamics and brain function","score":0.9994999766349792,"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":0.9994999766349792,"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/T13187","display_name":"Diffusion and Search Dynamics","score":0.9925000071525574,"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/T12056","display_name":"Markov Chains and Monte Carlo Methods","score":0.9843999743461609,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/spike","display_name":"Spike (software development)","score":0.8640888929367065},{"id":"https://openalex.org/keywords/spike-train","display_name":"Spike train","score":0.5904642343521118},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5834701657295227},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5667284727096558},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.5652889013290405},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5439385175704956},{"id":"https://openalex.org/keywords/gibbs-sampling","display_name":"Gibbs sampling","score":0.538092315196991},{"id":"https://openalex.org/keywords/posterior-probability","display_name":"Posterior probability","score":0.5073673129081726},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4555164873600006},{"id":"https://openalex.org/keywords/point-estimation","display_name":"Point estimation","score":0.42643821239471436},{"id":"https://openalex.org/keywords/bin","display_name":"Bin","score":0.4148951470851898},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4101807475090027},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3823454976081848},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2625741958618164},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.23999705910682678}],"concepts":[{"id":"https://openalex.org/C2781390188","wikidata":"https://www.wikidata.org/wiki/Q25203449","display_name":"Spike (software development)","level":2,"score":0.8640888929367065},{"id":"https://openalex.org/C2909946758","wikidata":"https://www.wikidata.org/wiki/Q194277","display_name":"Spike train","level":3,"score":0.5904642343521118},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5834701657295227},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5667284727096558},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.5652889013290405},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5439385175704956},{"id":"https://openalex.org/C158424031","wikidata":"https://www.wikidata.org/wiki/Q1191905","display_name":"Gibbs sampling","level":3,"score":0.538092315196991},{"id":"https://openalex.org/C57830394","wikidata":"https://www.wikidata.org/wiki/Q278079","display_name":"Posterior probability","level":3,"score":0.5073673129081726},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4555164873600006},{"id":"https://openalex.org/C41426520","wikidata":"https://www.wikidata.org/wiki/Q1192065","display_name":"Point estimation","level":2,"score":0.42643821239471436},{"id":"https://openalex.org/C156273044","wikidata":"https://www.wikidata.org/wiki/Q4913766","display_name":"Bin","level":2,"score":0.4148951470851898},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4101807475090027},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3823454976081848},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2625741958618164},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.23999705910682678},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/acssc.2013.6810293","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acssc.2013.6810293","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 Asilomar Conference on Signals, Systems and Computers","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.47999998927116394,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320333591","display_name":"Multidisciplinary University Research Initiative","ror":null},{"id":"https://openalex.org/F4320338281","display_name":"Army Research Office","ror":"https://ror.org/05epdh915"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W875731594","https://openalex.org/W1501586228","https://openalex.org/W1519516901","https://openalex.org/W1663973292","https://openalex.org/W2001222755","https://openalex.org/W2014381155","https://openalex.org/W2033765726","https://openalex.org/W2057881395","https://openalex.org/W2067474937","https://openalex.org/W2089315051","https://openalex.org/W2108094133","https://openalex.org/W2132067227","https://openalex.org/W2136342418","https://openalex.org/W2137576513","https://openalex.org/W2154047075","https://openalex.org/W2166493798","https://openalex.org/W2963730944","https://openalex.org/W4212863985","https://openalex.org/W6679698722","https://openalex.org/W6680409316"],"related_works":["https://openalex.org/W2383615955","https://openalex.org/W2329992713","https://openalex.org/W2062974934","https://openalex.org/W2187212244","https://openalex.org/W2775582103","https://openalex.org/W1558157446","https://openalex.org/W2173049006","https://openalex.org/W4281636778","https://openalex.org/W2950605049","https://openalex.org/W2014837149"],"abstract_inverted_index":{"We":[0,42,87],"present":[1,43],"efficient":[2],"Bayesian":[3],"methods":[4,18,83,113],"for":[5,84,123],"extracting":[6],"neuronal":[7],"spiking":[8],"information":[9],"from":[10,22],"calcium":[11,39],"imaging":[12,40],"data.":[13,41],"The":[14],"goal":[15],"of":[16,26,51,72,103,125],"our":[17],"is":[19],"to":[20,117],"sample":[21,68],"the":[23,49,70,104,129],"posterior":[24,107],"distribution":[25,108],"spike":[27,34,53,106,131],"trains":[28],"and":[29,74,98,121,133],"model":[30,96,134],"parameters":[31,97],"(baseline":[32],"concentration,":[33],"amplitude":[35],"etc)":[36],"given":[37],"noisy":[38],"discrete":[44],"time":[45,56,65],"algorithms":[46,66],"where":[47],"that":[48,67,91],"existence":[50],"a":[52],"at":[54,77],"each":[55],"bin":[57],"using":[58,81],"Gibbs":[59],"methods,":[60],"as":[61,63,115],"well":[62],"continuous":[64,110],"over":[69,94],"number":[71],"spikes":[73],"their":[75],"locations":[76],"an":[78],"arbitrary":[79],"resolution":[80],"Metropolis-Hastings":[82],"point":[85,119],"processes.":[86],"provide":[88,100],"Rao-Blackwellized":[89],"extensions":[90],"(i)":[92],"marginalize":[93],"several":[95],"(ii)":[99],"smooth":[101],"estimates":[102,120],"marginal":[105],"in":[109,127],"time.":[111],"Our":[112],"serve":[114],"complements":[116],"standard":[118],"allow":[122],"quantification":[124],"uncertainty":[126],"estimating":[128],"underlying":[130],"train":[132],"parameters.":[135]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":9},{"year":2019,"cited_by_count":13},{"year":2018,"cited_by_count":8},{"year":2017,"cited_by_count":7},{"year":2016,"cited_by_count":6},{"year":2014,"cited_by_count":2}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}