{"id":"https://openalex.org/W2546124103","doi":null,"title":"A blind deconvolution method for neural spike identification","display_name":"A blind deconvolution method for neural spike identification","publication_year":2011,"publication_date":"2011-12-12","ids":{"openalex":"https://openalex.org/W2546124103","mag":"2546124103"},"language":"en","primary_location":{"id":"pmh:oai:CiteSeerX.psu:10.1.1.310.6337","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.310.6337","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cns.nyu.edu/pub/lcv/Ekanadham11c-preprint.pdf","raw_type":"text"},"volume":null,"type":"preprint","indexed_in":[],"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/A5079641101","display_name":"Chaitanya Ekanadham","orcid":"https://orcid.org/0009-0006-8029-5284","observed_orcids":["https://orcid.org/0009-0006-8029-5284"]},"institutions":[{"id":"https://openalex.org/I36672615","display_name":"Courant Institute of Mathematical Sciences","ror":"https://ror.org/037tm7f56","country_code":"US","type":"education","lineage":["https://openalex.org/I36672615","https://openalex.org/I57206974"]},{"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":"Chaitanya Ekanadham","raw_affiliation_strings":[", Courant Institute, New York University, New York, NY#TAB#"],"raw_orcid":"https://orcid.org/0009-0006-8029-5284","affiliations":[{"raw_affiliation_string":", Courant Institute, New York University, New York, NY#TAB#","institution_ids":["https://openalex.org/I36672615","https://openalex.org/I57206974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033150336","display_name":"Daniel Tranchina","orcid":"https://orcid.org/0000-0002-0439-8349","observed_orcids":["https://orcid.org/0000-0002-0439-8349"]},"institutions":[{"id":"https://openalex.org/I36672615","display_name":"Courant Institute of Mathematical Sciences","ror":"https://ror.org/037tm7f56","country_code":"US","type":"education","lineage":["https://openalex.org/I36672615","https://openalex.org/I57206974"]},{"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":"Daniel Tranchina","raw_affiliation_strings":[", Courant Institute, New York University, New York, NY#TAB#"],"raw_orcid":"https://orcid.org/0000-0002-0439-8349","affiliations":[{"raw_affiliation_string":", Courant Institute, New York University, New York, NY#TAB#","institution_ids":["https://openalex.org/I36672615","https://openalex.org/I57206974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080476548","display_name":"Eero P. Simoncelli","orcid":"https://orcid.org/0000-0002-1206-527X","observed_orcids":["https://orcid.org/0000-0002-1206-527X"]},"institutions":[{"id":"https://openalex.org/I1344073410","display_name":"Howard Hughes Medical Institute","ror":"https://ror.org/006w34k90","country_code":"US","type":"facility","lineage":["https://openalex.org/I1344073410"]},{"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":"Eero P. Simoncelli","raw_affiliation_strings":["Courant Institute, Center for Neural Science, Howard Hughes Medical Institute, New York University, New York, NY#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Courant Institute, Center for Neural Science, Howard Hughes Medical Institute, New York University, New York, NY#TAB#","institution_ids":["https://openalex.org/I1344073410","https://openalex.org/I57206974"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1440","last_page":"1448"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.420199990272522,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.420199990272522,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10581","display_name":"Neural dynamics and brain function","score":0.1160999983549118,"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/T11601","display_name":"Neuroscience and Neural Engineering","score":0.09390000253915787,"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/blind-deconvolution","display_name":"blind deconvolution","score":0.9940000176429749},{"id":"https://openalex.org/keywords/maximum-a-posteriori-estimation","display_name":"maximum a posteriori estimation","score":0.8119999766349792},{"id":"https://openalex.org/keywords/sparse-coefficients","display_name":"sparse coefficients","score":0.5509999990463257},{"id":"https://openalex.org/keywords/block-coordinate-descent","display_name":"block coordinate descent","score":0.9129999876022339},{"id":"https://openalex.org/keywords/spike-trains","display_name":"spike trains","score":0.574999988079071}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7280628681182861},{"id":"https://openalex.org/C174576160","wikidata":"https://www.wikidata.org/wiki/Q1183700","display_name":"Deconvolution","level":2,"score":0.7162622213363647},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6818947792053223},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6148457527160645},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5957459211349487},{"id":"https://openalex.org/C2781390188","wikidata":"https://www.wikidata.org/wiki/Q25203449","display_name":"Spike (software development)","level":2,"score":0.5896725058555603},{"id":"https://openalex.org/C197424946","wikidata":"https://www.wikidata.org/wiki/Q1165717","display_name":"Waveform","level":3,"score":0.5516532063484192},{"id":"https://openalex.org/C30044814","wikidata":"https://www.wikidata.org/wiki/Q11334452","display_name":"Blind deconvolution","level":3,"score":0.534726619720459},{"id":"https://openalex.org/C2909946758","wikidata":"https://www.wikidata.org/wiki/Q194277","display_name":"Spike train","level":3,"score":0.501237154006958},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.46598854660987854},{"id":"https://openalex.org/C2777613131","wikidata":"https://www.wikidata.org/wiki/Q2003571","display_name":"Spike sorting","level":3,"score":0.4397476017475128},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.4394316077232361},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.40046313405036926},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.33519911766052246},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","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/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"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/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:CiteSeerX.psu:10.1.1.310.6337","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.310.6337","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cns.nyu.edu/pub/lcv/Ekanadham11c-preprint.pdf","raw_type":"text"},{"id":"mag:2546124103","doi":null,"is_oa":false,"landing_page_url":"http://papers.nips.cc/paper/4416-a-blind-sparse-deconvolution-method-for-neural-spike-identification.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4363606243","display_name":"neural information processing systems","issn_l":"1049-5258","issn":["1049-5258"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","norway-2"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"Neural Information Processing Systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W628029314","https://openalex.org/W1510801053","https://openalex.org/W1551494903","https://openalex.org/W1557376630","https://openalex.org/W1991266025","https://openalex.org/W1994194159","https://openalex.org/W2014461681","https://openalex.org/W2039307446","https://openalex.org/W2069519142","https://openalex.org/W2072137340","https://openalex.org/W2107861471","https://openalex.org/W2113606819","https://openalex.org/W2114747787","https://openalex.org/W2119883478","https://openalex.org/W2120077739","https://openalex.org/W2123367539","https://openalex.org/W2136104104","https://openalex.org/W2143148420","https://openalex.org/W2145739449","https://openalex.org/W2145889472","https://openalex.org/W2147691462","https://openalex.org/W2151460259","https://openalex.org/W2162098123","https://openalex.org/W2168745297","https://openalex.org/W2171406132","https://openalex.org/W2334772160","https://openalex.org/W2963909185"],"related_works":["https://openalex.org/W2125857237","https://openalex.org/W1989775522","https://openalex.org/W1999019051","https://openalex.org/W3030116208","https://openalex.org/W2948432200","https://openalex.org/W2104993043","https://openalex.org/W2804896528","https://openalex.org/W7100420765","https://openalex.org/W2729241336","https://openalex.org/W2051347361"],"abstract_inverted_index":{"We":[0,30,82,102],"consider":[1],"the":[2,32,41,49,66,78,90,131],"problem":[3,33,75],"of":[4,36,48,52,65,133],"estimating":[5],"neural":[6],"spikes":[7,69,135],"from":[8],"extracellular":[9],"voltage":[10,43],"recordings.":[11,123],"Most":[12],"current":[13],"methods":[14,160],"are":[15,80],"based":[16,93],"on":[17,94,106],"clustering,":[18],"which":[19,40,77,115],"requires":[20],"substantial":[21],"human":[22],"supervision":[23],"and":[24,68,136],"systematically":[25],"mishandles":[26],"temporally":[27],"overlapping":[28,149],"spikes.":[29,150],"formulate":[31],"as":[34,109,111],"one":[35],"statistical":[37],"inference,":[38],"in":[39,76],"recorded":[42],"is":[44,70,118,162],"a":[45,72,84,142,154],"noisy":[46],"sum":[47],"spike":[50,59],"trains":[51],"each":[53],"neuron":[54],"convolved":[55],"with":[56],"its":[57],"associated":[58],"waveform.":[60],"Joint":[61],"maximum-a-posteriori":[62],"(MAP)":[63],"estimation":[64],"waveforms":[67],"then":[71],"blind":[73],"deconvolution":[74],"coefficients":[79],"sparse.":[81],"develop":[83],"block-coordinate":[85],"descent":[86],"procedure":[87],"to":[88,141,158,165],"approximate":[89],"MAP":[91],"solution,":[92],"our":[95,104,127],"recently":[96],"developed":[97],"continuous":[98],"basis":[99],"pursuit":[100],"method.":[101],"validate":[103],"method":[105,128,152],"simulated":[107],"data":[108,113],"well":[110],"real":[112],"for":[114],"ground":[116],"truth":[117],"available":[119],"via":[120],"simultaneous":[121],"intracellular":[122],"In":[124],"both":[125],"cases,":[126],"substantially":[129],"reduces":[130],"number":[132],"missed":[134],"false":[137],"positives":[138],"when":[139],"compared":[140],"standard":[143],"clustering":[144,159],"algorithm,":[145],"primarily":[146],"by":[147],"recovering":[148],"The":[151],"offers":[153],"fully":[155],"automated":[156],"alternative":[157],"that":[161],"less":[163],"susceptible":[164],"systematic":[166],"errors.":[167]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":2}],"updated_date":"2026-10-06T10:28:23.643775","created_date":"2016-11-04T00:00:00"}