{"id":"https://openalex.org/W4414991730","doi":"https://doi.org/10.1371/journal.pcbi.1014059","title":"Benchmarking spike source localization algorithms in high density probes","display_name":"Benchmarking spike source localization algorithms in high density probes","publication_year":2025,"publication_date":"2025-08-19","ids":{"openalex":"https://openalex.org/W4414991730","doi":"https://doi.org/10.1371/journal.pcbi.1014059"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2508.13451","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2508.13451","pdf_url":"https://arxiv.org/pdf/2508.13451","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","doaj"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2508.13451","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101525266","display_name":"Hao Zhao","orcid":"https://orcid.org/0009-0000-6441-2723"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Hao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101660886","display_name":"Xinhe Zhang","orcid":"https://orcid.org/0000-0002-1223-220X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Xinhe","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093227446","display_name":"Arnau Marin\u2010Llobet","orcid":"https://orcid.org/0009-0008-8128-4119"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Marin-Llobet, Arnau","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101740762","display_name":"Xinyi Lin","orcid":"https://orcid.org/0009-0006-7041-3187"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lin, Xinyi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5100409727","display_name":"Jia Liu","orcid":"https://orcid.org/0000-0002-8383-4048"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Jia","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10662","display_name":"Ultrasonics and Acoustic Wave Propagation","score":0.9678000211715698,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10662","display_name":"Ultrasonics and Acoustic Wave Propagation","score":0.9678000211715698,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T14117","display_name":"Integrated Circuits and Semiconductor Failure Analysis","score":0.9312000274658203,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10752","display_name":"Terahertz technology and applications","score":0.9189000129699707,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.6722000241279602},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6610999703407288},{"id":"https://openalex.org/keywords/heuristics","display_name":"Heuristics","score":0.6413000226020813},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5738999843597412},{"id":"https://openalex.org/keywords/spike","display_name":"Spike (software development)","score":0.5508999824523926},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.5110999941825867},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.48399999737739563},{"id":"https://openalex.org/keywords/ideal","display_name":"Ideal (ethics)","score":0.42879998683929443},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3540000021457672}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7473999857902527},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6735000014305115},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.6722000241279602},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6610999703407288},{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.6413000226020813},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5738999843597412},{"id":"https://openalex.org/C2781390188","wikidata":"https://www.wikidata.org/wiki/Q25203449","display_name":"Spike (software development)","level":2,"score":0.5508999824523926},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.5110999941825867},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.48399999737739563},{"id":"https://openalex.org/C2776639384","wikidata":"https://www.wikidata.org/wiki/Q840396","display_name":"Ideal (ethics)","level":2,"score":0.42879998683929443},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4065000116825104},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3540000021457672},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.3537999987602234},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.3379000127315521},{"id":"https://openalex.org/C121927907","wikidata":"https://www.wikidata.org/wiki/Q1952516","display_name":"Multiresolution analysis","level":5,"score":0.328900009393692},{"id":"https://openalex.org/C126980161","wikidata":"https://www.wikidata.org/wiki/Q863783","display_name":"Simulated annealing","level":2,"score":0.2913999855518341},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.287200003862381},{"id":"https://openalex.org/C2986897749","wikidata":"https://www.wikidata.org/wiki/Q231761","display_name":"Potential field","level":2,"score":0.28209999203681946},{"id":"https://openalex.org/C117838684","wikidata":"https://www.wikidata.org/wiki/Q533483","display_name":"Local field potential","level":2,"score":0.27410000562667847},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.27140000462532043},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.26989999413490295},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2630000114440918},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.2533999979496002},{"id":"https://openalex.org/C186565885","wikidata":"https://www.wikidata.org/wiki/Q1651163","display_name":"Biological neuron model","level":3,"score":0.25270000100135803},{"id":"https://openalex.org/C2781170535","wikidata":"https://www.wikidata.org/wiki/Q30587856","display_name":"Noisy data","level":2,"score":0.25189998745918274}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2508.13451","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2508.13451","pdf_url":"https://arxiv.org/pdf/2508.13451","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":null,"raw_type":"text"},{"id":"pmh:oai:doaj.org/article:3a6fba4ab2b7466c90083d33f6c69280","is_oa":false,"landing_page_url":"https://doaj.org/article/3a6fba4ab2b7466c90083d33f6c69280","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"PLoS Computational Biology, Vol 22, Iss 3, p e1014059 (2026)","raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2508.13451","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2508.13451","pdf_url":"https://arxiv.org/pdf/2508.13451","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320309622","display_name":"Harvard University","ror":"https://ror.org/03vek6s52"},{"id":"https://openalex.org/F4320337395","display_name":"Division of Emerging Frontiers in Research and Innovation","ror":"https://ror.org/0388pet74"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4414991730.pdf","grobid_xml":"https://content.openalex.org/works/W4414991730.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Estimating":[0],"neuron":[1,14,80],"location":[2],"from":[3],"extracellular":[4],"recordings":[5],"is":[6,51],"essential":[7],"for":[8,55,161,170],"developing":[9,175],"advanced":[10],"brain-machine":[11,185],"interfaces.":[12,186],"Accurate":[13],"localization":[15,43,81,172],"improves":[16],"spike":[17],"sorting,":[18],"which":[19,36],"involves":[20],"detecting":[21],"action":[22],"potentials":[23],"and":[24,53,97,102,111,119,135,151,174],"assigning":[25],"them":[26,158],"to":[27,149,180],"individual":[28],"neurons.":[29],"It":[30],"also":[31],"helps":[32],"monitor":[33],"probe":[34,39],"drift,":[35],"affects":[37],"long-term":[38,120,162],"reliability.":[40],"Although":[41],"several":[42],"algorithms":[44,86,115,173,179],"are":[45,61],"currently":[46],"in":[47,116,141,154],"use,":[48],"the":[49,108,182],"field":[50],"nascent":[52],"arguments":[54],"using":[56,87],"one":[57],"algorithm":[58],"over":[59],"another":[60],"largely":[62],"theoretical":[63],"or":[64],"based":[65],"on":[66],"visual":[67],"analysis":[68],"of":[69,77,113,184],"clustering":[70],"results.":[71],"We":[72,83,105],"present":[73],"a":[74,92,168],"first-of-its-kind":[75],"benchmarking":[76],"commonly":[78],"used":[79],"algorithms.":[82],"tested":[84],"these":[85,114],"two":[88],"ground":[89],"truth":[90],"datasets:":[91],"biophysically":[93],"realistic":[94,137],"simulated":[95],"dataset,":[96],"experimental":[98,155],"data":[99],"combining":[100],"patch-clamp":[101],"Neuropixels":[103],"probes.":[104],"systematically":[106],"evaluate":[107],"accuracy,":[109],"robustness,":[110],"runtime":[112],"ideal":[117,142],"conditions":[118,122],"recording":[121],"with":[123],"electrode":[124,152],"decay.":[125],"Our":[126],"findings":[127],"highlight":[128],"significant":[129],"performance":[130],"differences;":[131],"while":[132],"more":[133,159],"complex":[134],"physically":[136],"models":[138],"perform":[139],"better":[140],"situations,":[143],"simple":[144],"heuristics":[145],"demonstrate":[146],"superior":[147],"robustness":[148],"noise":[150],"degradation":[153],"datasets,":[156],"making":[157],"suitable":[160],"neural":[163],"recordings.":[164],"This":[165],"work":[166],"provides":[167],"framework":[169],"assessing":[171],"robust,":[176],"biologically":[177],"grounded":[178],"advance":[181],"development":[183]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-06-27T06:13:17.587685","created_date":"2025-10-09T00:00:00"}