{"id":"https://openalex.org/W1974719952","doi":"https://doi.org/10.1162/neco_a_00157","title":"Firing Variability Is Higher than Deduced from the Empirical Coefficient of Variation","display_name":"Firing Variability Is Higher than Deduced from the Empirical Coefficient of Variation","publication_year":2011,"publication_date":"2011-04-26","ids":{"openalex":"https://openalex.org/W1974719952","doi":"https://doi.org/10.1162/neco_a_00157","mag":"1974719952","pmid":"https://pubmed.ncbi.nlm.nih.gov/21521046"},"language":"en","primary_location":{"id":"doi:10.1162/neco_a_00157","is_oa":false,"landing_page_url":"https://doi.org/10.1162/neco_a_00157","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/A5066654049","display_name":"Susanne Ditlevsen","orcid":"https://orcid.org/0000-0002-1998-2783"},"institutions":[{"id":"https://openalex.org/I124055696","display_name":"University of Copenhagen","ror":"https://ror.org/035b05819","country_code":"DK","type":"education","lineage":["https://openalex.org/I124055696"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Susanne Ditlevsen","raw_affiliation_strings":["Department of Mathematical Sciences, University of Copenhagen, Copenhagen DK-2100, Denmark"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematical Sciences, University of Copenhagen, Copenhagen DK-2100, Denmark","institution_ids":["https://openalex.org/I124055696"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054713013","display_name":"Petr L\u00e1nsk\u00fd","orcid":"https://orcid.org/0000-0003-2725-1160"},"institutions":[{"id":"https://openalex.org/I202391551","display_name":"Czech Academy of Sciences","ror":"https://ror.org/053avzc18","country_code":"CZ","type":"government","lineage":["https://openalex.org/I202391551"]},{"id":"https://openalex.org/I4210166371","display_name":"Czech Academy of Sciences, Institute of Physiology","ror":"https://ror.org/05xw0ep96","country_code":"CZ","type":"facility","lineage":["https://openalex.org/I202391551","https://openalex.org/I4210166371"]}],"countries":["CZ"],"is_corresponding":false,"raw_author_name":"Petr Lansky","raw_affiliation_strings":["Institute of Physiology, Academy of Sciences of the Czech Republic, 142 20 Prague 4, Czech Republic"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Physiology, Academy of Sciences of the Czech Republic, 142 20 Prague 4, Czech Republic","institution_ids":["https://openalex.org/I202391551","https://openalex.org/I4210166371"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.852,"has_fulltext":false,"cited_by_count":22,"citation_normalized_percentile":{"value":0.71359056,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"23","issue":"8","first_page":"1944","last_page":"1966"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10581","display_name":"Neural dynamics and brain function","score":0.9968000054359436,"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":0.9968000054359436,"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/T10971","display_name":"Olfactory and Sensory Function Studies","score":0.9883999824523926,"subfield":{"id":"https://openalex.org/subfields/2809","display_name":"Sensory Systems"},"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/T10423","display_name":"Neurobiology and Insect Physiology Research","score":0.9847999811172485,"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/estimator","display_name":"Estimator","score":0.8922358751296997},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.7135107517242432},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.688241720199585},{"id":"https://openalex.org/keywords/standard-deviation","display_name":"Standard deviation","score":0.6451653242111206},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.550391674041748},{"id":"https://openalex.org/keywords/bias-of-an-estimator","display_name":"Bias of an estimator","score":0.5243138074874878},{"id":"https://openalex.org/keywords/coefficient-of-variation","display_name":"Coefficient of variation","score":0.52348792552948},{"id":"https://openalex.org/keywords/standard-error","display_name":"Standard error","score":0.47595712542533875},{"id":"https://openalex.org/keywords/distribution","display_name":"Distribution (mathematics)","score":0.4224357604980469},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.4121902287006378},{"id":"https://openalex.org/keywords/empirical-distribution-function","display_name":"Empirical distribution function","score":0.4116537868976593},{"id":"https://openalex.org/keywords/minimum-variance-unbiased-estimator","display_name":"Minimum-variance unbiased estimator","score":0.37348902225494385}],"concepts":[{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.8922358751296997},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.7135107517242432},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.688241720199585},{"id":"https://openalex.org/C22679943","wikidata":"https://www.wikidata.org/wiki/Q159375","display_name":"Standard deviation","level":2,"score":0.6451653242111206},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.550391674041748},{"id":"https://openalex.org/C191393472","wikidata":"https://www.wikidata.org/wiki/Q15222032","display_name":"Bias of an estimator","level":4,"score":0.5243138074874878},{"id":"https://openalex.org/C89838059","wikidata":"https://www.wikidata.org/wiki/Q623738","display_name":"Coefficient of variation","level":2,"score":0.52348792552948},{"id":"https://openalex.org/C18747219","wikidata":"https://www.wikidata.org/wiki/Q620994","display_name":"Standard error","level":2,"score":0.47595712542533875},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.4224357604980469},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.4121902287006378},{"id":"https://openalex.org/C98385598","wikidata":"https://www.wikidata.org/wiki/Q1339385","display_name":"Empirical distribution function","level":2,"score":0.4116537868976593},{"id":"https://openalex.org/C165646398","wikidata":"https://www.wikidata.org/wiki/Q3755281","display_name":"Minimum-variance unbiased estimator","level":3,"score":0.37348902225494385},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","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":"D000818","descriptor_name":"Animals","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000818","descriptor_name":"Animals","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000818","descriptor_name":"Animals","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":true},{"descriptor_ui":"D008959","descriptor_name":"Models, Neurological","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":true},{"descriptor_ui":"D008962","descriptor_name":"Models, Theoretical","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D008962","descriptor_name":"Models, Theoretical","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D008962","descriptor_name":"Models, Theoretical","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D009474","descriptor_name":"Neurons","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":false},{"descriptor_ui":"D009474","descriptor_name":"Neurons","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":false},{"descriptor_ui":"D009474","descriptor_name":"Neurons","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":false},{"descriptor_ui":"D051381","descriptor_name":"Rats","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D051381","descriptor_name":"Rats","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D051381","descriptor_name":"Rats","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":4,"locations":[{"id":"doi:10.1162/neco_a_00157","is_oa":false,"landing_page_url":"https://doi.org/10.1162/neco_a_00157","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:21521046","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/21521046","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},{"id":"pmh:oai:asep.lib.cas.cz:CavUnEpca/0365080","is_oa":false,"landing_page_url":"http://hdl.handle.net/11104/0200415","pdf_url":null,"source":{"id":"https://openalex.org/S7407055266","display_name":"ASEP","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":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:pure.atira.dk:openaire_cris_publications/a35f6440-6a2b-11df-928f-000ea68e967b","is_oa":false,"landing_page_url":"https://researchprofiles.ku.dk/da/publications/a35f6440-6a2b-11df-928f-000ea68e967b","pdf_url":null,"source":{"id":"https://openalex.org/S4306401983","display_name":"Research at the University of Copenhagen (University of Copenhagen)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I124055696","host_organization_name":"University of Copenhagen","host_organization_lineage":["https://openalex.org/I124055696"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Ditlevsen , S & Lansky , P 2011 , ' Firing variability is higher than deduced from the empirical coefficient of variation ' , Neural Computation , vol. 23 , pp. 1944-1966 .","raw_type":"article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320310485","display_name":"Natur og Univers, Det Frie Forskningsr\u00e5d","ror":"https://ror.org/03ge1nb22"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":54,"referenced_works":["https://openalex.org/W1967313092","https://openalex.org/W1968033934","https://openalex.org/W1969264030","https://openalex.org/W1976016717","https://openalex.org/W1978285031","https://openalex.org/W1978306818","https://openalex.org/W1978668587","https://openalex.org/W1982067584","https://openalex.org/W1986825443","https://openalex.org/W1988353627","https://openalex.org/W1989597311","https://openalex.org/W1991567646","https://openalex.org/W1998794714","https://openalex.org/W2003773498","https://openalex.org/W2006545642","https://openalex.org/W2022037925","https://openalex.org/W2027173466","https://openalex.org/W2040423213","https://openalex.org/W2041507388","https://openalex.org/W2042173515","https://openalex.org/W2048864062","https://openalex.org/W2063915568","https://openalex.org/W2066905947","https://openalex.org/W2067418529","https://openalex.org/W2068813271","https://openalex.org/W2070170328","https://openalex.org/W2072712259","https://openalex.org/W2081891172","https://openalex.org/W2087056242","https://openalex.org/W2088141169","https://openalex.org/W2097560155","https://openalex.org/W2099437861","https://openalex.org/W2102529861","https://openalex.org/W2116494657","https://openalex.org/W2116721504","https://openalex.org/W2120062331","https://openalex.org/W2128063877","https://openalex.org/W2128773719","https://openalex.org/W2130305130","https://openalex.org/W2146007569","https://openalex.org/W2146797675","https://openalex.org/W2146902331","https://openalex.org/W2152119945","https://openalex.org/W2152629877","https://openalex.org/W2152661514","https://openalex.org/W2160645575","https://openalex.org/W2163976004","https://openalex.org/W2166963621","https://openalex.org/W2168228198","https://openalex.org/W2801179766","https://openalex.org/W2989448192","https://openalex.org/W3016843226","https://openalex.org/W3151409487","https://openalex.org/W4411392672"],"related_works":["https://openalex.org/W2349547417","https://openalex.org/W4237435333","https://openalex.org/W4248185570","https://openalex.org/W4210503132","https://openalex.org/W2999390738","https://openalex.org/W2352602506","https://openalex.org/W3092888124","https://openalex.org/W2093865141","https://openalex.org/W4239491110","https://openalex.org/W2368191880"],"abstract_inverted_index":{"A":[0],"convenient":[1],"and":[2,51,116,154,197],"often":[3],"used":[4,104],"summary":[5],"measure":[6],"to":[7,33,112,163,181,199],"quantify":[8,113],"the":[9,15,22,27,46,57,62,76,81,86,89,96,114,122,141,146,155,165,170,184],"firing":[10],"variability":[11],"in":[12,61,206],"neurons":[13,205],"is":[14,30,59,78,92,111,124,152,178],"coefficient":[16],"of":[17,68,88,108],"variation":[18],"(CV),":[19],"defined":[20],"as":[21],"standard":[23,63,66,166],"deviation":[24,67],"divided":[25,71],"by":[26,72],"mean.":[28],"It":[29],"therefore":[31],"important":[32],"find":[34],"an":[35],"estimator":[36,47,77,97],"that":[37,44,176],"gives":[38],"reliable":[39],"results":[40],"from":[41,131,202],"experimental":[42,200],"data,":[43,132],"is,":[45],"should":[48],"be":[49,129],"unbiased":[50],"have":[52],"low":[53],"estimation":[54,119,147],"variance.":[55],"When":[56,168],"CV":[58],"evaluated":[60,194],"way":[64],"(empirical":[65],"interspike":[69,90],"intervals":[70,91],"their":[73],"average),":[74],"then":[75],"biased,":[79],"underestimating":[80],"true":[82],"CV,":[83],"especially":[84],"if":[85],"distribution":[87,123,151],"positively":[93,159,188],"skewed.":[94],"Moreover,":[95],"has":[98],"a":[99],"large":[100],"variance":[101],"for":[102,187],"commonly":[103],"distributions.":[105,190],"The":[106,191],"aim":[107],"this":[109],"letter":[110],"bias":[115,142],"propose":[117,162],"alternative":[118],"methods.":[120],"If":[121,149],"assumed":[125,153],"known":[126],"or":[127],"can":[128],"determined":[130],"parametric":[133],"estimators":[134,192],"are":[135,157,193],"proposed,":[136],"which":[137],"not":[138],"only":[139],"remove":[140],"but":[143],"also":[144],"decrease":[145],"errors.":[148],"no":[150],"data":[156,201],"very":[158],"skewed,":[160],"we":[161,173],"correct":[164],"estimator.":[167],"defining":[169],"corrected":[171],"estimator,":[172],"simply":[174],"use":[175],"it":[177],"more":[179],"stable":[180],"work":[182],"on":[183],"log":[185],"scale":[186],"skewed":[189],"through":[195],"simulations":[196],"applied":[198],"olfactory":[203],"receptor":[204],"rats.":[207]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":3},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
