{"id":"https://openalex.org/W2006257129","doi":"https://doi.org/10.1155/2015/493769","title":"Estimating Latent Attentional States Based on Simultaneous Binary and Continuous Behavioral Measures","display_name":"Estimating Latent Attentional States Based on Simultaneous Binary and Continuous Behavioral Measures","publication_year":2015,"publication_date":"2015-01-01","ids":{"openalex":"https://openalex.org/W2006257129","doi":"https://doi.org/10.1155/2015/493769","mag":"2006257129","pmid":"https://pubmed.ncbi.nlm.nih.gov/25883639"},"language":"en","primary_location":{"id":"doi:10.1155/2015/493769","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2015/493769","pdf_url":"https://downloads.hindawi.com/journals/cin/2015/493769.pdf","source":{"id":"https://openalex.org/S72372694","display_name":"Computational Intelligence and Neuroscience","issn_l":"1687-5265","issn":["1687-5265","1687-5273"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Intelligence and Neuroscience","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://downloads.hindawi.com/journals/cin/2015/493769.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100457703","display_name":"Zhe Chen","orcid":"https://orcid.org/0000-0002-6483-6056"},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Zhe Chen","raw_affiliation_strings":["Departments of Psychiatry, Neuroscience and Physiology, School of Medicine, New York University, New York, NY 10016, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Departments of Psychiatry, Neuroscience and Physiology, School of Medicine, New York University, New York, NY 10016, USA","institution_ids":["https://openalex.org/I57206974"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5100457703"],"corresponding_institution_ids":["https://openalex.org/I57206974"],"apc_list":{"value":2100,"currency":"USD","value_usd":2100},"apc_paid":{"value":2100,"currency":"USD","value_usd":2100},"fwci":0.333,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.60328373,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":"2015","issue":null,"first_page":"1","last_page":"11"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10581","display_name":"Neural dynamics and brain function","score":0.9991000294685364,"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":0.9991000294685364,"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/T10448","display_name":"Memory and Neural Mechanisms","score":0.9918000102043152,"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/T10042","display_name":"Neural and Behavioral Psychology Studies","score":0.9567000269889832,"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/computer-science","display_name":"Computer science","score":0.6854428052902222},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6609483957290649},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.626367449760437},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4845103621482849},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4817831218242645},{"id":"https://openalex.org/keywords/multinomial-distribution","display_name":"Multinomial distribution","score":0.47051113843917847},{"id":"https://openalex.org/keywords/binary-data","display_name":"Binary data","score":0.46828243136405945},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.45975494384765625},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.45671242475509644},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3355857729911804},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.16305682063102722},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13418105244636536}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6854428052902222},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6609483957290649},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.626367449760437},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4845103621482849},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4817831218242645},{"id":"https://openalex.org/C192065140","wikidata":"https://www.wikidata.org/wiki/Q1147928","display_name":"Multinomial distribution","level":2,"score":0.47051113843917847},{"id":"https://openalex.org/C2779190172","wikidata":"https://www.wikidata.org/wiki/Q4913888","display_name":"Binary data","level":3,"score":0.46828243136405945},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.45975494384765625},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.45671242475509644},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3355857729911804},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.16305682063102722},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13418105244636536},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D001288","descriptor_name":"Attention","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":false},{"descriptor_ui":"D001288","descriptor_name":"Attention","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":false},{"descriptor_ui":"D001288","descriptor_name":"Attention","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":false},{"descriptor_ui":"D001519","descriptor_name":"Behavior","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":false},{"descriptor_ui":"D001519","descriptor_name":"Behavior","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":false},{"descriptor_ui":"D001519","descriptor_name":"Behavior","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":false},{"descriptor_ui":"D003198","descriptor_name":"Computer Simulation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D003198","descriptor_name":"Computer Simulation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D003198","descriptor_name":"Computer Simulation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","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":"D015233","descriptor_name":"Models, Statistical","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D015233","descriptor_name":"Models, Statistical","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D015233","descriptor_name":"Models, Statistical","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":4,"locations":[{"id":"doi:10.1155/2015/493769","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2015/493769","pdf_url":"https://downloads.hindawi.com/journals/cin/2015/493769.pdf","source":{"id":"https://openalex.org/S72372694","display_name":"Computational Intelligence and Neuroscience","issn_l":"1687-5265","issn":["1687-5265","1687-5273"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Intelligence and Neuroscience","raw_type":"journal-article"},{"id":"pmid:25883639","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/25883639","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":"Computational intelligence and neuroscience","raw_type":null},{"id":"pmh:oai:doaj.org/article:591ff705870742e89863214fc9f69326","is_oa":true,"landing_page_url":"https://doaj.org/article/591ff705870742e89863214fc9f69326","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Computational Intelligence and Neuroscience, Vol 2015 (2015)","raw_type":"article"},{"id":"pmh:oai:pubmedcentral.nih.gov:4391722","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/4391722","pdf_url":null,"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":"Comput Intell Neurosci","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1155/2015/493769","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2015/493769","pdf_url":"https://downloads.hindawi.com/journals/cin/2015/493769.pdf","source":{"id":"https://openalex.org/S72372694","display_name":"Computational Intelligence and Neuroscience","issn_l":"1687-5265","issn":["1687-5265","1687-5273"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Intelligence and Neuroscience","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2043726368","display_name":null,"funder_award_id":"IIS-1307645","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G2587954501","display_name":"CRCNS: Computational Approaches to Uncover Neural Representation of Population Codes in Rodent Hippocampal-Cortical Circuits","funder_award_id":"1307645","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320319918","display_name":"York University","ror":"https://ror.org/05fq50484"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2006257129.pdf","grobid_xml":"https://content.openalex.org/works/W2006257129.grobid-xml"},"referenced_works_count":41,"referenced_works":["https://openalex.org/W139917725","https://openalex.org/W1842942389","https://openalex.org/W1882651929","https://openalex.org/W1966316609","https://openalex.org/W1976551160","https://openalex.org/W1979441832","https://openalex.org/W1989844119","https://openalex.org/W1992803127","https://openalex.org/W1999135570","https://openalex.org/W1999567494","https://openalex.org/W2011889641","https://openalex.org/W2018795431","https://openalex.org/W2019011597","https://openalex.org/W2021766318","https://openalex.org/W2045425629","https://openalex.org/W2058247065","https://openalex.org/W2066532331","https://openalex.org/W2075931307","https://openalex.org/W2076618452","https://openalex.org/W2102584403","https://openalex.org/W2104446072","https://openalex.org/W2104791085","https://openalex.org/W2109843705","https://openalex.org/W2111911706","https://openalex.org/W2119357806","https://openalex.org/W2119805934","https://openalex.org/W2119945372","https://openalex.org/W2124271233","https://openalex.org/W2125838338","https://openalex.org/W2132991226","https://openalex.org/W2135537007","https://openalex.org/W2139902660","https://openalex.org/W2159593968","https://openalex.org/W2164183806","https://openalex.org/W2164970774","https://openalex.org/W2168062689","https://openalex.org/W2261519444","https://openalex.org/W2334126544","https://openalex.org/W2342960162","https://openalex.org/W2487997806","https://openalex.org/W4240912299"],"related_works":["https://openalex.org/W2053269318","https://openalex.org/W2364370872","https://openalex.org/W2955220190","https://openalex.org/W2097963413","https://openalex.org/W2025614924","https://openalex.org/W2294335174","https://openalex.org/W3145575561","https://openalex.org/W2305090462","https://openalex.org/W2477685749","https://openalex.org/W2049576621"],"abstract_inverted_index":{"Cognition":[0],"is":[1,8,121,132],"a":[2,30,67,107],"complex":[3],"and":[4,33,44,83,97],"dynamic":[5],"process.":[6],"It":[7],"an":[9],"essential":[10],"goal":[11,131],"to":[12,133],"estimate":[13],"latent":[14],"attentional":[15,39],"states":[16],"based":[17],"on":[18],"behavioral":[19,25,46,125,144],"measures":[20],"in":[21],"many":[22,124],"sequences":[23,141],"of":[24,70,94],"tasks.":[26],"Here,":[27],"we":[28,89,112],"propose":[29],"probabilistic":[31],"modeling":[32,60],"inference":[34],"framework":[35],"for":[36,123],"estimating":[37],"the":[38,52,61,71,92,98,102,114,129,135],"state":[40,62,140],"using":[41,80],"simultaneous":[42],"binary":[43],"continuous":[45],"measures.":[47,145],"The":[48],"proposed":[49],"model":[50,56,74,95],"extends":[51],"standard":[53],"hidden":[54,72],"Markov":[55],"(HMM)":[57],"by":[58],"explicitly":[59],"duration":[63],"distribution,":[64],"which":[65],"yields":[66],"special":[68],"example":[69],"semi-Markov":[73],"(HSMM).":[75],"We":[76],"validate":[77,113],"our":[78],"methods":[79],"computer":[81,87],"simulations":[82],"experimental":[84,103],"data.":[85],"In":[86],"simulations,":[88],"systematically":[90],"investigate":[91],"impacts":[93],"mismatch":[96],"latency":[99],"distribution.":[100],"For":[101],"data":[104],"collected":[105],"from":[106,142],"rodent":[108],"visual":[109],"detection":[110],"task,":[111],"results":[115],"with":[116],"predictive":[117],"log-likelihood.":[118],"Our":[119],"work":[120],"useful":[122],"neuroscience":[126],"experiments,":[127],"where":[128],"common":[130],"infer":[134],"discrete":[136],"(binary":[137],"or":[138],"multinomial)":[139],"multiple":[143]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2026-06-22T08:00:12.763002","created_date":"2025-10-10T00:00:00"}