{"id":"https://openalex.org/W4392903553","doi":"https://doi.org/10.1109/icassp48485.2024.10446801","title":"Estimating Directed Spectral Information Flow between Multi-Resolution Time Series","display_name":"Estimating Directed Spectral Information Flow between Multi-Resolution Time Series","publication_year":2024,"publication_date":"2024-03-18","ids":{"openalex":"https://openalex.org/W4392903553","doi":"https://doi.org/10.1109/icassp48485.2024.10446801","pmid":"https://pubmed.ncbi.nlm.nih.gov/40321673"},"language":"en","primary_location":{"id":"doi:10.1109/icassp48485.2024.10446801","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icassp48485.2024.10446801","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC12048868/pdf/nihms-2075522.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5094178939","display_name":"Qiqi Xian","orcid":null},"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":false,"raw_author_name":"Qiqi Xian","raw_affiliation_strings":["Neuroscience Institute, NYU Grossman School of Medicine,Dept. Psychiatry,New York,NY,USA","Dept. Psychiatry, Neuroscience Institute, NYU Grossman School of Medicine, New York, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Neuroscience Institute, NYU Grossman School of Medicine,Dept. Psychiatry,New York,NY,USA","institution_ids":["https://openalex.org/I57206974"]},{"raw_affiliation_string":"Dept. Psychiatry, Neuroscience Institute, NYU Grossman School of Medicine, New York, NY, USA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100457703","display_name":"Zhe Chen","orcid":"https://orcid.org/0000-0002-6483-6056"},"institutions":[{"id":"https://openalex.org/I83041322","display_name":"Brooklyn College","ror":"https://ror.org/019k4jq75","country_code":"US","type":"education","lineage":["https://openalex.org/I83041322"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhe Sage Chen","raw_affiliation_strings":["NYU Tandon School of Engineering,Dept. Biomedical Engineering,Brooklyn,NY,USA","Dept. Biomedical Engineering, NYU Tandon School of Engineering, Brooklyn, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NYU Tandon School of Engineering,Dept. Biomedical Engineering,Brooklyn,NY,USA","institution_ids":["https://openalex.org/I83041322"]},{"raw_affiliation_string":"Dept. Biomedical Engineering, NYU Tandon School of Engineering, Brooklyn, NY, USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.02513934,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"2024","issue":null,"first_page":"2156","last_page":"2159"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9836000204086304,"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"}},"topics":[{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9836000204086304,"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/T11270","display_name":"Complex Systems and Time Series Analysis","score":0.9818000197410583,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9757000207901001,"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/bivariate-analysis","display_name":"Bivariate analysis","score":0.9057589173316956},{"id":"https://openalex.org/keywords/granger-causality","display_name":"Granger causality","score":0.7406628131866455},{"id":"https://openalex.org/keywords/causality","display_name":"Causality (physics)","score":0.7020752429962158},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6773675084114075},{"id":"https://openalex.org/keywords/information-flow","display_name":"Information flow","score":0.607024073600769},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.6057006120681763},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.578528642654419},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5725787878036499},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.5134957432746887},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.49562108516693115},{"id":"https://openalex.org/keywords/resolution","display_name":"Resolution (logic)","score":0.467502236366272},{"id":"https://openalex.org/keywords/flow","display_name":"Flow (mathematics)","score":0.4544827938079834},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.41849035024642944},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.32866454124450684},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.30212920904159546},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2605689465999603},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21336451172828674},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08922526240348816}],"concepts":[{"id":"https://openalex.org/C64341305","wikidata":"https://www.wikidata.org/wiki/Q4919225","display_name":"Bivariate analysis","level":2,"score":0.9057589173316956},{"id":"https://openalex.org/C129824826","wikidata":"https://www.wikidata.org/wiki/Q2630107","display_name":"Granger causality","level":2,"score":0.7406628131866455},{"id":"https://openalex.org/C64357122","wikidata":"https://www.wikidata.org/wiki/Q1149766","display_name":"Causality (physics)","level":2,"score":0.7020752429962158},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6773675084114075},{"id":"https://openalex.org/C2779136372","wikidata":"https://www.wikidata.org/wiki/Q10283002","display_name":"Information flow","level":2,"score":0.607024073600769},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.6057006120681763},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.578528642654419},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5725787878036499},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.5134957432746887},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.49562108516693115},{"id":"https://openalex.org/C138268822","wikidata":"https://www.wikidata.org/wiki/Q1051925","display_name":"Resolution (logic)","level":2,"score":0.467502236366272},{"id":"https://openalex.org/C38349280","wikidata":"https://www.wikidata.org/wiki/Q1434290","display_name":"Flow (mathematics)","level":2,"score":0.4544827938079834},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.41849035024642944},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.32866454124450684},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30212920904159546},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2605689465999603},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21336451172828674},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08922526240348816},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/icassp48485.2024.10446801","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icassp48485.2024.10446801","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},{"id":"pmid:40321673","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/40321673","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":"Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing. ICASSP (Conference)","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:12048868","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/12048868","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC12048868/pdf/nihms-2075522.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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proc IEEE Int Conf Acoust Speech Signal Process","raw_type":"Text"}],"best_oa_location":{"id":"pmh:oai:pubmedcentral.nih.gov:12048868","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/12048868","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC12048868/pdf/nihms-2075522.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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proc IEEE Int Conf Acoust Speech Signal Process","raw_type":"Text"},"sustainable_development_goals":[{"score":0.6100000143051147,"id":"https://metadata.un.org/sdg/13","display_name":"Climate action"}],"awards":[{"id":"https://openalex.org/G1687040466","display_name":null,"funder_award_id":"R01 MH139352","funder_id":"https://openalex.org/F4320337346","funder_display_name":"National Institute of Mental Health"},{"id":"https://openalex.org/G3179287280","display_name":null,"funder_award_id":"MH118928","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G3543402550","display_name":null,"funder_award_id":"DA056394","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G605039452","display_name":null,"funder_award_id":"RF1 DA056394","funder_id":"https://openalex.org/F4320337347","funder_display_name":"National Institute on Drug Abuse"},{"id":"https://openalex.org/G8698347643","display_name":null,"funder_award_id":"R01 MH118928","funder_id":"https://openalex.org/F4320337346","funder_display_name":"National Institute of Mental Health"}],"funders":[{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"},{"id":"https://openalex.org/F4320337346","display_name":"National Institute of Mental Health","ror":"https://ror.org/04xeg9z08"},{"id":"https://openalex.org/F4320337347","display_name":"National Institute on Drug Abuse","ror":"https://ror.org/00fq5cm18"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4392903553.pdf","grobid_xml":"https://content.openalex.org/works/W4392903553.grobid-xml"},"referenced_works_count":11,"referenced_works":["https://openalex.org/W1636081627","https://openalex.org/W1971428016","https://openalex.org/W2097064800","https://openalex.org/W2116031726","https://openalex.org/W2136562407","https://openalex.org/W2744112845","https://openalex.org/W2892944220","https://openalex.org/W2963739582","https://openalex.org/W3000709978","https://openalex.org/W3011792982","https://openalex.org/W3123283837"],"related_works":["https://openalex.org/W2035792466","https://openalex.org/W2761997784","https://openalex.org/W2977645287","https://openalex.org/W4251418261","https://openalex.org/W4244184932","https://openalex.org/W2613542790","https://openalex.org/W1489061421","https://openalex.org/W1530435600","https://openalex.org/W1972675643","https://openalex.org/W2056895937"],"abstract_inverted_index":{"Identifying":[0],"directed":[1,60],"information":[2,61],"flow":[3,62],"or":[4],"Granger":[5,31],"causality":[6,32],"between":[7,33],"multivariate":[8],"time":[9],"series":[10],"is":[11],"important":[12],"for":[13,79],"a":[14,43],"wide":[15],"range":[16],"of":[17],"applications":[18],"in":[19],"science":[20],"and":[21,51,55,76],"engineering.":[22],"However,":[23],"traditional":[24],"data-driven":[25],"approaches":[26],"are":[27],"insufficient":[28],"to":[29,47],"assess":[30],"multimodal":[34],"data":[35],"with":[36,70],"distinct":[37],"temporal":[38],"resolution.":[39],"Here":[40],"we":[41],"propose":[42],"new":[44],"analysis":[45],"approach":[46,69],"address":[48],"this":[49],"challenge":[50],"present":[52],"quantitative":[53],"characterizations":[54],"statistical":[56],"assessment":[57],"on":[58,74],"frequency-dependent":[59],"(\"generalized":[63],"spectral":[64],"causality\").":[65],"We":[66],"validate":[67],"our":[68],"intensive":[71],"computer":[72],"simulations":[73],"bivariate":[75],"trivariate":[77],"systems":[78],"various":[80],"conditions.":[81]},"counts_by_year":[],"updated_date":"2026-06-24T13:16:06.693445","created_date":"2025-10-10T00:00:00"}