{"id":"https://openalex.org/W1997865175","doi":"https://doi.org/10.1109/acssc.2014.7094552","title":"Neural spike train denoising by point process re-weighted iterative smoothing","display_name":"Neural spike train denoising by point process re-weighted iterative smoothing","publication_year":2014,"publication_date":"2014-11-01","ids":{"openalex":"https://openalex.org/W1997865175","doi":"https://doi.org/10.1109/acssc.2014.7094552","mag":"1997865175"},"language":"en","primary_location":{"id":"doi:10.1109/acssc.2014.7094552","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acssc.2014.7094552","pdf_url":null,"source":{"id":"https://openalex.org/S4363608593","display_name":"2014 48th Asilomar Conference on Signals, Systems and Computers","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 48th Asilomar Conference on Signals, Systems and Computers","raw_type":"proceedings-article"},"type":"conference-paper","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/A5002643771","display_name":"Demba Ba","orcid":"https://orcid.org/0000-0002-1139-1030"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Demba Ba","raw_affiliation_strings":["Department of Anesthesia, Critical Care and Pain Medicine, Boston, MA","Department of BCS, MIT, Cambridge, MA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Anesthesia, Critical Care and Pain Medicine, Boston, MA","institution_ids":[]},{"raw_affiliation_string":"Department of BCS, MIT, Cambridge, MA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041600605","display_name":"Behtash Babadi","orcid":"https://orcid.org/0000-0002-9856-006X"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Behtash Babadi","raw_affiliation_strings":["Department of ECE, University of Maryland, College Park, MD"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of ECE, University of Maryland, College Park, MD","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005240128","display_name":"Patrick L. Purdon","orcid":"https://orcid.org/0000-0003-0080-3340"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Patrick L. Purdon","raw_affiliation_strings":["Department of Anesthesia, Critical Care and Pain Medicine, Boston, MA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Anesthesia, Critical Care and Pain Medicine, Boston, MA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030321614","display_name":"Emery N. Brown","orcid":"https://orcid.org/0000-0003-2668-7819"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Emery N. Brown","raw_affiliation_strings":["Department of Anesthesia, Critical Care and Pain Medicine, Boston, MA","MIT Institute for Medical Engineering and Science, Cambridge, MA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Anesthesia, Critical Care and Pain Medicine, Boston, MA","institution_ids":[]},{"raw_affiliation_string":"MIT Institute for Medical Engineering and Science, Cambridge, MA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"763","last_page":"768"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10977","display_name":"Optical Imaging and Spectroscopy Techniques","score":0.9955000281333923,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10977","display_name":"Optical Imaging and Spectroscopy Techniques","score":0.9955000281333923,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9850000143051147,"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":0.979200005531311,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.6807069778442383},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5742571949958801},{"id":"https://openalex.org/keywords/total-variation-denoising","display_name":"Total variation denoising","score":0.5513737201690674},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5348080396652222},{"id":"https://openalex.org/keywords/point-process","display_name":"Point process","score":0.4866962730884552},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.386107474565506},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.34516263008117676},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.33945053815841675},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.29504403471946716},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.17005380988121033}],"concepts":[{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.6807069778442383},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5742571949958801},{"id":"https://openalex.org/C207282899","wikidata":"https://www.wikidata.org/wiki/Q7828156","display_name":"Total variation denoising","level":3,"score":0.5513737201690674},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5348080396652222},{"id":"https://openalex.org/C88871306","wikidata":"https://www.wikidata.org/wiki/Q7208287","display_name":"Point process","level":2,"score":0.4866962730884552},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.386107474565506},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34516263008117676},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.33945053815841675},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.29504403471946716},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.17005380988121033},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/acssc.2014.7094552","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acssc.2014.7094552","pdf_url":null,"source":{"id":"https://openalex.org/S4363608593","display_name":"2014 48th Asilomar Conference on Signals, Systems and Computers","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 48th Asilomar Conference on Signals, Systems and Computers","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320319990","display_name":"National Institute for Health and Care Research","ror":"https://ror.org/0187kwz08"},{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W2006277118","https://openalex.org/W2015304937","https://openalex.org/W2043439335","https://openalex.org/W2045176118","https://openalex.org/W2067633806","https://openalex.org/W2069037334","https://openalex.org/W2090614493","https://openalex.org/W2103559027","https://openalex.org/W2109843705","https://openalex.org/W2112246597","https://openalex.org/W2119883478","https://openalex.org/W2129983824","https://openalex.org/W2142224912","https://openalex.org/W2169183612","https://openalex.org/W2489822048","https://openalex.org/W4254313632","https://openalex.org/W4292024691","https://openalex.org/W6661621657"],"related_works":["https://openalex.org/W3033981387","https://openalex.org/W2495078643","https://openalex.org/W3010678772","https://openalex.org/W2559187321","https://openalex.org/W2612397051","https://openalex.org/W2053223715","https://openalex.org/W1490451209","https://openalex.org/W2586189899","https://openalex.org/W4387314738","https://openalex.org/W233850645"],"abstract_inverted_index":{"An":[0],"important":[1],"problem":[2],"in":[3,16],"computational":[4],"neuro-science":[5],"is":[6,178],"to":[7,88,128,155,180],"design":[8],"algorithms":[9],"that":[10,130,138],"can":[11,99],"capture":[12,181],"robustly":[13,182],"abrupt":[14],"changes":[15],"the":[17,37,45,53,63,70,90,114,122,131,144,149,172,183,190],"conditional":[18],"intensity":[19],"function":[20],"(CIF)":[21],"of":[22,28,39,44,65,69,113,148,185,187],"a":[23,40,58,66,119],"stochastic":[24],"point":[25,41,54,91,104,110,141,147],"process":[26,42,55,83,92,105,111],"model":[27,68],"neural":[29],"spiking":[30],"data.":[31],"Towards":[32],"this":[33],"end,":[34],"we":[35],"advocate":[36],"use":[38,118],"analogue":[43],"total":[46,59,93],"variation":[47,60,94],"denoising":[48,95],"algorithm,":[49,80],"which":[50,108],"trades":[51],"off":[52],"likelihood":[56],"with":[57,143],"prior":[61],"on":[62],"parameters":[64],"log-linear":[67],"CIF.":[71],"We":[72,117,152],"propose":[73],"an":[74],"iteratively":[75],"re-weighted":[76],"least":[77],"squares":[78],"(IRLS)":[79],"termed":[81],"Point":[82],"Re-weighted":[84],"Iterative":[85],"SMoothing":[86],"(PRISM),":[87],"solve":[89],"(PPTVD)":[96],"problem.":[97,151],"PRISM":[98,135,154,176],"be":[100],"implemented":[101],"using":[102,171],"well-established":[103],"smoothing":[106],"algorithms,":[107],"are":[109],"analogues":[112],"Kalman":[115],"smoother.":[116],"connection":[120],"between":[121],"Expectation-Maximization":[123],"(EM)":[124],"algorithm":[125,177],"and":[126,137,157],"IRLS":[127],"prove":[129],"sequence":[132],"generated":[133],"by":[134],"converges":[136],"its":[139],"limit":[140],"coincides":[142],"unique":[145],"stationary":[146],"PPTVD":[150],"apply":[153],"123":[156],"41":[158],"neuronal":[159],"units":[160],"acquired":[161],"from":[162],"two":[163],"separate":[164],"epileptic":[165],"patients":[166],"during":[167],"general":[168],"anesthesia":[169],"induced":[170],"drug":[173],"propofol.":[174],"The":[175],"able":[179],"onset":[184],"loss":[186],"consciousness":[188],"at":[189],"millisecond":[191],"time":[192],"scale.":[193]},"counts_by_year":[{"year":2018,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}