{"id":"https://openalex.org/W1967866517","doi":"https://doi.org/10.1109/ciss.2015.7086908","title":"Closed form jitter methods for neuronal spike train analysis","display_name":"Closed form jitter methods for neuronal spike train analysis","publication_year":2015,"publication_date":"2015-03-01","ids":{"openalex":"https://openalex.org/W1967866517","doi":"https://doi.org/10.1109/ciss.2015.7086908","mag":"1967866517"},"language":"en","primary_location":{"id":"doi:10.1109/ciss.2015.7086908","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ciss.2015.7086908","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 49th Annual Conference on Information Sciences and Systems (CISS)","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/A5066298913","display_name":"Daniel Jeck","orcid":null},"institutions":[{"id":"https://openalex.org/I1314596251","display_name":"Allen Institute for Brain Science","ror":"https://ror.org/00dcv1019","country_code":"US","type":"facility","lineage":["https://openalex.org/I1314596251","https://openalex.org/I4210140341"]},{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Daniel Jeck","raw_affiliation_strings":["Department of Biomedical Engineering, ZanvyI Krieger Mind/Brain Institute","Zanvyl Krieger Mind/Brain Institute, Johns Hopkins University, Baltimore, Maryland 21218, USA"],"affiliations":[{"raw_affiliation_string":"Department of Biomedical Engineering, ZanvyI Krieger Mind/Brain Institute","institution_ids":["https://openalex.org/I1314596251"]},{"raw_affiliation_string":"Zanvyl Krieger Mind/Brain Institute, Johns Hopkins University, Baltimore, Maryland 21218, USA","institution_ids":["https://openalex.org/I145311948"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016761623","display_name":"Ernst Niebur","orcid":"https://orcid.org/0000-0002-2815-9262"},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ernst Niebur","raw_affiliation_strings":["Solomon Snyder Department of Neuroscience, Johns Hopkins University, Baltimore, Maryland","Zanvyl Krieger Mind/Brain Institute, Johns Hopkins University, Baltimore, Maryland 21218, USA"],"affiliations":[{"raw_affiliation_string":"Solomon Snyder Department of Neuroscience, Johns Hopkins University, Baltimore, Maryland","institution_ids":["https://openalex.org/I145311948"]},{"raw_affiliation_string":"Zanvyl Krieger Mind/Brain Institute, Johns Hopkins University, Baltimore, Maryland 21218, USA","institution_ids":["https://openalex.org/I145311948"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5066298913"],"corresponding_institution_ids":["https://openalex.org/I1314596251","https://openalex.org/I145311948"],"apc_list":null,"apc_paid":null,"fwci":0.1613,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.51466783,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"80","issue":null,"first_page":"1","last_page":"3"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10581","display_name":"Neural dynamics and brain function","score":1.0,"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":1.0,"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/T11513","display_name":"stochastic dynamics and bifurcation","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11601","display_name":"Neuroscience and Neural Engineering","score":0.9962000250816345,"subfield":{"id":"https://openalex.org/subfields/2804","display_name":"Cellular and Molecular 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/spike","display_name":"Spike (software development)","score":0.8910744190216064},{"id":"https://openalex.org/keywords/jitter","display_name":"Jitter","score":0.8480277061462402},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6643191576004028},{"id":"https://openalex.org/keywords/train","display_name":"Train","score":0.6129417419433594},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.5501294732093811},{"id":"https://openalex.org/keywords/spike-train","display_name":"Spike train","score":0.5387035608291626},{"id":"https://openalex.org/keywords/interval","display_name":"Interval (graph theory)","score":0.5065885782241821},{"id":"https://openalex.org/keywords/resampling","display_name":"Resampling","score":0.5019645690917969},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5006282329559326},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.4958101212978363},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2645520269870758},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1956484019756317}],"concepts":[{"id":"https://openalex.org/C2781390188","wikidata":"https://www.wikidata.org/wiki/Q25203449","display_name":"Spike (software development)","level":2,"score":0.8910744190216064},{"id":"https://openalex.org/C134652429","wikidata":"https://www.wikidata.org/wiki/Q1052698","display_name":"Jitter","level":2,"score":0.8480277061462402},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6643191576004028},{"id":"https://openalex.org/C190839683","wikidata":"https://www.wikidata.org/wiki/Q2448197","display_name":"Train","level":2,"score":0.6129417419433594},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.5501294732093811},{"id":"https://openalex.org/C2909946758","wikidata":"https://www.wikidata.org/wiki/Q194277","display_name":"Spike train","level":3,"score":0.5387035608291626},{"id":"https://openalex.org/C2778067643","wikidata":"https://www.wikidata.org/wiki/Q166507","display_name":"Interval (graph theory)","level":2,"score":0.5065885782241821},{"id":"https://openalex.org/C150921843","wikidata":"https://www.wikidata.org/wiki/Q1170431","display_name":"Resampling","level":2,"score":0.5019645690917969},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5006282329559326},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4958101212978363},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2645520269870758},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1956484019756317},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"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/ciss.2015.7086908","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ciss.2015.7086908","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 49th Annual Conference on Information Sciences and Systems (CISS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"},{"id":"https://openalex.org/F4320337345","display_name":"Office of Naval Research","ror":"https://ror.org/00rk2pe57"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W266383608","https://openalex.org/W1501028655","https://openalex.org/W1567626583","https://openalex.org/W1586810339","https://openalex.org/W1967866517","https://openalex.org/W1973752972","https://openalex.org/W2042312351","https://openalex.org/W2063972845","https://openalex.org/W2073512103","https://openalex.org/W2097180131","https://openalex.org/W2105756523","https://openalex.org/W2112332687","https://openalex.org/W2117564327","https://openalex.org/W2118458514","https://openalex.org/W2138704896","https://openalex.org/W2148200426","https://openalex.org/W2398741376","https://openalex.org/W4214571354"],"related_works":["https://openalex.org/W2383615955","https://openalex.org/W2056756835","https://openalex.org/W2187212244","https://openalex.org/W2775582103","https://openalex.org/W2329992713","https://openalex.org/W2062974934","https://openalex.org/W1558157446","https://openalex.org/W2098097562","https://openalex.org/W2173049006","https://openalex.org/W2014837149"],"abstract_inverted_index":{"Interval":[0],"jitter":[1,91],"and":[2,93,129],"spike":[3,20,72,132,142],"resampling":[4],"methods":[5,23,55],"are":[6,48,56],"used":[7,52],"to":[8,38,61],"analyze":[9],"the":[10,25,63,66,86,96,108],"time":[11,46],"scale":[12,47],"at":[13,43],"which":[14],"temporal":[15],"correlations":[16,42],"occur":[17],"in":[18,74,110],"neuronal":[19],"trains.":[21,133],"These":[22],"allow":[24],"computation":[26],"of":[27,65,68,98,121,131,140],"jitter-corrected":[28],"cross":[29],"correlograms":[30],"as":[31,33],"well":[32],"statistically":[34],"robust":[35],"hypothesis":[36],"testing":[37],"decide":[39],"whether":[40],"observed":[41],"a":[44,70],"given":[45],"significant.":[49],"Since":[50],"currently":[51],"Monte":[53],"Carlo":[54],"computationally":[57],"costly,":[58],"we":[59],"propose":[60],"compute":[62],"distribution":[64,81],"probability":[67],"observing":[69],"jittered":[71],"train":[73],"closed":[75],"form.":[76],"We":[77],"show":[78],"that":[79],"this":[80],"is":[82],"obtained":[83],"by":[84],"computing":[85,107],"analytical":[87],"solution":[88],"for":[89,137],"each":[90],"interval":[92],"then":[94],"convolving":[95],"distributions":[97],"all":[99,102],"intervals.":[100],"For":[101],"mean":[103,126],"firing":[104,127],"rates":[105,128],"tested,":[106],"convolutions":[109],"Fourier":[111],"space":[112],"rather":[113],"than":[114],"directly":[115],"improves":[116],"performance":[117],"considerably":[118],"without":[119],"loss":[120],"accuracy.":[122,146],"Performance":[123],"increased":[124],"with":[125,144],"length":[130],"The":[134],"method":[135],"allows":[136],"rapid":[138],"analysis":[139],"long":[141],"trains":[143],"high":[145]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2015,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}