{"id":"https://openalex.org/W2051563870","doi":"https://doi.org/10.1162/neco.2010.08-08-838","title":"Extracting State Transition Dynamics from Multiple Spike Trains Using Hidden Markov Models with Correlated Poisson Distribution","display_name":"Extracting State Transition Dynamics from Multiple Spike Trains Using Hidden Markov Models with Correlated Poisson Distribution","publication_year":2010,"publication_date":"2010-03-25","ids":{"openalex":"https://openalex.org/W2051563870","doi":"https://doi.org/10.1162/neco.2010.08-08-838","mag":"2051563870","pmid":"https://pubmed.ncbi.nlm.nih.gov/20337539"},"language":"en","primary_location":{"id":"doi:10.1162/neco.2010.08-08-838","is_oa":false,"landing_page_url":"https://doi.org/10.1162/neco.2010.08-08-838","pdf_url":null,"source":{"id":"https://openalex.org/S207023548","display_name":"Neural Computation","issn_l":"0899-7667","issn":["0899-7667","1530-888X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315718","host_organization_name":"The MIT Press","host_organization_lineage":["https://openalex.org/P4310315718"],"host_organization_lineage_names":["The MIT Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Computation","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5033816900","display_name":"Kentaro Katahira","orcid":"https://orcid.org/0000-0002-2018-3938"},"institutions":[{"id":"https://openalex.org/I2800939219","display_name":"RIKEN Center for Brain Science","ror":"https://ror.org/04j1n1c04","country_code":"JP","type":"facility","lineage":["https://openalex.org/I2800939219","https://openalex.org/I4210110652"]},{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kentaro Katahira","raw_affiliation_strings":["Graduate School of Frontier Sciences, University of Tokyo, 277-8561 Chiba, Japan, and RIKEN Brain Science Institute, 35-0198 Saitama, Japan","Graduate School of Frontier Sciences, University of Tokyo, 277-8561#N# Chiba, Japan, and RIKEN Brain Science Institute, 35-0198 Saitama, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Frontier Sciences, University of Tokyo, 277-8561 Chiba, Japan, and RIKEN Brain Science Institute, 35-0198 Saitama, Japan","institution_ids":["https://openalex.org/I2800939219","https://openalex.org/I74801974"]},{"raw_affiliation_string":"Graduate School of Frontier Sciences, University of Tokyo, 277-8561#N# Chiba, Japan, and RIKEN Brain Science Institute, 35-0198 Saitama, Japan","institution_ids":["https://openalex.org/I2800939219","https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038575019","display_name":"Jun Nishikawa","orcid":"https://orcid.org/0000-0002-3914-8526"},"institutions":[{"id":"https://openalex.org/I2800939219","display_name":"RIKEN Center for Brain Science","ror":"https://ror.org/04j1n1c04","country_code":"JP","type":"facility","lineage":["https://openalex.org/I2800939219","https://openalex.org/I4210110652"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Jun Nishikawa","raw_affiliation_strings":["RIKEN Brain Science Institute, 35-0198 Saitama, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"RIKEN Brain Science Institute, 35-0198 Saitama, Japan","institution_ids":["https://openalex.org/I2800939219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015691007","display_name":"Kazuo Okanoya","orcid":"https://orcid.org/0000-0002-7439-9566"},"institutions":[{"id":"https://openalex.org/I2800939219","display_name":"RIKEN Center for Brain Science","ror":"https://ror.org/04j1n1c04","country_code":"JP","type":"facility","lineage":["https://openalex.org/I2800939219","https://openalex.org/I4210110652"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kazuo Okanoya","raw_affiliation_strings":["RIKEN Brain Science Institute, 35-0198 Saitama, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"RIKEN Brain Science Institute, 35-0198 Saitama, Japan","institution_ids":["https://openalex.org/I2800939219"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103124754","display_name":"Masato Okada","orcid":"https://orcid.org/0000-0002-9040-8784"},"institutions":[{"id":"https://openalex.org/I2800939219","display_name":"RIKEN Center for Brain Science","ror":"https://ror.org/04j1n1c04","country_code":"JP","type":"facility","lineage":["https://openalex.org/I2800939219","https://openalex.org/I4210110652"]},{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masato Okada","raw_affiliation_strings":["Graduate School of Frontier Sciences, University of Tokyo, 277-8561 Chiba, Japan, and RIKEN Brain Science Institute, 35-0198 Saitama, Japan","Graduate School of Frontier Sciences, University of Tokyo, 277-8561#N# Chiba, Japan, and RIKEN Brain Science Institute, 35-0198 Saitama, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Frontier Sciences, University of Tokyo, 277-8561 Chiba, Japan, and RIKEN Brain Science Institute, 35-0198 Saitama, Japan","institution_ids":["https://openalex.org/I2800939219","https://openalex.org/I74801974"]},{"raw_affiliation_string":"Graduate School of Frontier Sciences, University of Tokyo, 277-8561#N# Chiba, Japan, and RIKEN Brain Science Institute, 35-0198 Saitama, Japan","institution_ids":["https://openalex.org/I2800939219","https://openalex.org/I74801974"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6547,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.70831992,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":96},"biblio":{"volume":"22","issue":"9","first_page":"2369","last_page":"2389"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10581","display_name":"Neural dynamics and brain function","score":0.9994000196456909,"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":0.9994000196456909,"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/T10320","display_name":"Neural Networks and Applications","score":0.9944999814033508,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9768000245094299,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.7931497693061829},{"id":"https://openalex.org/keywords/poisson-distribution","display_name":"Poisson distribution","score":0.7479636073112488},{"id":"https://openalex.org/keywords/markov-model","display_name":"Markov model","score":0.49824953079223633},{"id":"https://openalex.org/keywords/bayes-theorem","display_name":"Bayes' theorem","score":0.49534931778907776},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.48606422543525696},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.45256924629211426},{"id":"https://openalex.org/keywords/spike-train","display_name":"Spike train","score":0.4466026723384857},{"id":"https://openalex.org/keywords/multivariate-normal-distribution","display_name":"Multivariate normal distribution","score":0.4415634274482727},{"id":"https://openalex.org/keywords/negative-binomial-distribution","display_name":"Negative binomial distribution","score":0.4293863773345947},{"id":"https://openalex.org/keywords/spike","display_name":"Spike (software development)","score":0.42204561829566956},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.42199790477752686},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.42137858271598816},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.4124453365802765},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4062117636203766},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3900296986103058},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.3586307168006897},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.22333571314811707},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.21185916662216187},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.19528409838676453}],"concepts":[{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.7931497693061829},{"id":"https://openalex.org/C100906024","wikidata":"https://www.wikidata.org/wiki/Q205692","display_name":"Poisson distribution","level":2,"score":0.7479636073112488},{"id":"https://openalex.org/C163836022","wikidata":"https://www.wikidata.org/wiki/Q6771326","display_name":"Markov model","level":3,"score":0.49824953079223633},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.49534931778907776},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.48606422543525696},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.45256924629211426},{"id":"https://openalex.org/C2909946758","wikidata":"https://www.wikidata.org/wiki/Q194277","display_name":"Spike train","level":3,"score":0.4466026723384857},{"id":"https://openalex.org/C177384507","wikidata":"https://www.wikidata.org/wiki/Q1149000","display_name":"Multivariate normal distribution","level":3,"score":0.4415634274482727},{"id":"https://openalex.org/C199335787","wikidata":"https://www.wikidata.org/wiki/Q743364","display_name":"Negative binomial distribution","level":3,"score":0.4293863773345947},{"id":"https://openalex.org/C2781390188","wikidata":"https://www.wikidata.org/wiki/Q25203449","display_name":"Spike (software development)","level":2,"score":0.42204561829566956},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.42199790477752686},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.42137858271598816},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4124453365802765},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4062117636203766},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3900296986103058},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.3586307168006897},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.22333571314811707},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.21185916662216187},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.19528409838676453},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","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},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008390","descriptor_name":"Markov Chains","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D008390","descriptor_name":"Markov Chains","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D008390","descriptor_name":"Markov Chains","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D008959","descriptor_name":"Models, Neurological","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008959","descriptor_name":"Models, Neurological","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008959","descriptor_name":"Models, Neurological","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D009474","descriptor_name":"Neurons","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D009474","descriptor_name":"Neurons","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D009474","descriptor_name":"Neurons","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016012","descriptor_name":"Poisson Distribution","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016012","descriptor_name":"Poisson Distribution","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016012","descriptor_name":"Poisson Distribution","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":2,"locations":[{"id":"doi:10.1162/neco.2010.08-08-838","is_oa":false,"landing_page_url":"https://doi.org/10.1162/neco.2010.08-08-838","pdf_url":null,"source":{"id":"https://openalex.org/S207023548","display_name":"Neural Computation","issn_l":"0899-7667","issn":["0899-7667","1530-888X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315718","host_organization_name":"The MIT Press","host_organization_lineage":["https://openalex.org/P4310315718"],"host_organization_lineage_names":["The MIT Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Computation","raw_type":"journal-article"},{"id":"pmid:20337539","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/20337539","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":"Neural computation","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1501542638","https://openalex.org/W1618600317","https://openalex.org/W1985841281","https://openalex.org/W1991266025","https://openalex.org/W2011703226","https://openalex.org/W2022448907","https://openalex.org/W2023373280","https://openalex.org/W2027666633","https://openalex.org/W2035969394","https://openalex.org/W2038721060","https://openalex.org/W2043969094","https://openalex.org/W2071498445","https://openalex.org/W2084793648","https://openalex.org/W2109843705","https://openalex.org/W2110242299","https://openalex.org/W2111066871","https://openalex.org/W2111761474","https://openalex.org/W2113547349","https://openalex.org/W2115979064","https://openalex.org/W2120843707","https://openalex.org/W2125502516","https://openalex.org/W2145977470","https://openalex.org/W2147238273","https://openalex.org/W2163194183","https://openalex.org/W2167270514","https://openalex.org/W2168919237","https://openalex.org/W2595697910","https://openalex.org/W2597289420","https://openalex.org/W2911546748","https://openalex.org/W4243109555"],"related_works":["https://openalex.org/W2383615955","https://openalex.org/W2056756835","https://openalex.org/W2187212244","https://openalex.org/W2062974934","https://openalex.org/W2775582103","https://openalex.org/W2329992713","https://openalex.org/W1558157446","https://openalex.org/W2173049006","https://openalex.org/W2014837149","https://openalex.org/W2114811586"],"abstract_inverted_index":{"Neural":[0],"activity":[1],"is":[2,44],"nonstationary":[3],"and":[4,96,131],"varies":[5],"across":[6],"time.":[7],"Hidden":[8],"Markov":[9],"models":[10],"(HMMs)":[11],"have":[12],"been":[13,33],"used":[14,34],"to":[15],"track":[16],"the":[17,36,42,48,54,70,83,90,101,113,123],"state":[18],"transition":[19],"among":[20],"quasi-stationary":[21],"discrete":[22],"neural":[23],"states.":[24],"Within":[25],"this":[26],"context,":[27],"an":[28,106],"independent":[29],"Poisson":[30,64,119],"model":[31,43],"has":[32],"for":[35,69,82,109],"output":[37,71],"distribution":[38,65,72],"of":[39,46,73,93,116,125],"HMMs;":[40],"hence,":[41],"incapable":[45],"tracking":[47],"change":[49],"in":[50],"correlation":[51,67,97],"without":[52],"modulating":[53],"firing":[55],"rate.":[56],"To":[57],"achieve":[58],"this,":[59],"we":[60],"applied":[61],"a":[62,77,117,137],"multivariate":[63,118],"with":[66],"terms":[68],"HMMs.":[74],"We":[75,104,121],"formulated":[76],"variational":[78],"Bayes":[79],"(VB)":[80],"inference":[81],"model.":[84],"The":[85],"VB":[86],"could":[87],"automatically":[88],"determine":[89],"appropriate":[91],"number":[92],"hidden":[94],"states":[95],"types":[98],"while":[99],"avoiding":[100],"overlearning":[102],"problem.":[103],"developed":[105],"efficient":[107],"algorithm":[108],"computing":[110],"posteriors":[111],"using":[112],"recursive":[114],"relationship":[115],"distribution.":[120],"demonstrated":[122],"performance":[124],"our":[126],"method":[127],"on":[128],"synthetic":[129],"data":[130],"real":[132],"spike":[133],"trains":[134],"recorded":[135],"from":[136],"songbird.":[138]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2012,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}