{"id":"https://openalex.org/W3022049265","doi":"https://doi.org/10.1109/ciss48834.2020.1570617409","title":"Robust Inference of Neuronal Correlations from Blurred and Noisy Spiking Observations","display_name":"Robust Inference of Neuronal Correlations from Blurred and Noisy Spiking Observations","publication_year":2020,"publication_date":"2020-03-01","ids":{"openalex":"https://openalex.org/W3022049265","doi":"https://doi.org/10.1109/ciss48834.2020.1570617409","mag":"3022049265"},"language":"en","primary_location":{"id":"doi:10.1109/ciss48834.2020.1570617409","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ciss48834.2020.1570617409","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 54th 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/A5079150713","display_name":"Anuththara Rupasinghe","orcid":"https://orcid.org/0000-0003-2143-8709"},"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":true,"raw_author_name":"Anuththara Rupasinghe","raw_affiliation_strings":["Department of Electrical & Computer Engineering, University of Maryland, College Park, MD, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical & Computer Engineering, University of Maryland, College Park, MD, USA","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"last","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 Electrical & Computer Engineering, University of Maryland, College Park, MD, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical & Computer Engineering, University of Maryland, College Park, MD, USA","institution_ids":["https://openalex.org/I66946132"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5079150713"],"corresponding_institution_ids":["https://openalex.org/I66946132"],"apc_list":null,"apc_paid":null,"fwci":0.3346,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.54066881,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10581","display_name":"Neural dynamics and brain function","score":0.9991999864578247,"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":0.9991999864578247,"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/T10540","display_name":"Advanced Fluorescence Microscopy Techniques","score":0.996399998664856,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T12859","display_name":"Cell Image Analysis Techniques","score":0.9900000095367432,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/deconvolution","display_name":"Deconvolution","score":0.7836397290229797},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6833350658416748},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5974330902099609},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5874060392379761},{"id":"https://openalex.org/keywords/spike","display_name":"Spike (software development)","score":0.5154791474342346},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5139896273612976},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5004191398620605},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.47137391567230225},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.44974827766418457},{"id":"https://openalex.org/keywords/premovement-neuronal-activity","display_name":"Premovement neuronal activity","score":0.44193288683891296},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4088233709335327},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3997677266597748},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3417667746543884},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.147659569978714}],"concepts":[{"id":"https://openalex.org/C174576160","wikidata":"https://www.wikidata.org/wiki/Q1183700","display_name":"Deconvolution","level":2,"score":0.7836397290229797},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6833350658416748},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5974330902099609},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5874060392379761},{"id":"https://openalex.org/C2781390188","wikidata":"https://www.wikidata.org/wiki/Q25203449","display_name":"Spike (software development)","level":2,"score":0.5154791474342346},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5139896273612976},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5004191398620605},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.47137391567230225},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.44974827766418457},{"id":"https://openalex.org/C74254510","wikidata":"https://www.wikidata.org/wiki/Q7240508","display_name":"Premovement neuronal activity","level":2,"score":0.44193288683891296},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4088233709335327},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3997677266597748},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3417667746543884},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.147659569978714},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","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/ciss48834.2020.1570617409","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ciss48834.2020.1570617409","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 54th Annual Conference on Information Sciences and Systems (CISS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1506806321","https://openalex.org/W1516111018","https://openalex.org/W1910536141","https://openalex.org/W1998050452","https://openalex.org/W2001222755","https://openalex.org/W2006277118","https://openalex.org/W2040802339","https://openalex.org/W2041060053","https://openalex.org/W2046031057","https://openalex.org/W2067474937","https://openalex.org/W2079960018","https://openalex.org/W2094227853","https://openalex.org/W2099878672","https://openalex.org/W2109843705","https://openalex.org/W2110242299","https://openalex.org/W2112246597","https://openalex.org/W2116804672","https://openalex.org/W2129983824","https://openalex.org/W2132342669","https://openalex.org/W2136242018","https://openalex.org/W2138309709","https://openalex.org/W2225156818","https://openalex.org/W2231009150","https://openalex.org/W2502163955","https://openalex.org/W2564791711","https://openalex.org/W2595012769","https://openalex.org/W2786993517","https://openalex.org/W2797233320","https://openalex.org/W2885162916","https://openalex.org/W2963111108","https://openalex.org/W3101380508"],"related_works":["https://openalex.org/W2580650124","https://openalex.org/W4386190339","https://openalex.org/W3090782779","https://openalex.org/W2968424575","https://openalex.org/W4251527294","https://openalex.org/W3142333283","https://openalex.org/W4250106855","https://openalex.org/W2164129707","https://openalex.org/W4292122269","https://openalex.org/W2949366006"],"abstract_inverted_index":{"Emerging":[0],"large-scale":[1],"neuronal":[2,22,97,119,161],"recording":[3],"technolo-gies,":[4],"such":[5,34,48],"as":[6],"two-photon":[7,100,123],"calcium":[8],"imaging,":[9],"typically":[10],"provide":[11],"blurred":[12],"and":[13,31,59,107,133],"noisy":[14],"surrogates":[15],"of":[16],"spiking":[17,52],"activity.":[18],"Extracting":[19],"the":[20,150,159],"underlying":[21,160],"correlations,":[23],"which":[24,83],"are":[25,44,70],"key":[26],"to":[27,47,50,63,87,116,140],"understanding":[28],"neural":[29],"function":[30],"circuitry,":[32],"from":[33,99,104,121,129],"data":[35,49,101],"is":[36],"thus":[37,102],"a":[38],"challenging":[39],"task.":[40],"Though":[41],"deconvolution":[42],"techniques":[43,128],"often":[45],"applied":[46],"recover":[51],"activity,":[53],"they":[54],"require":[55],"high":[56],"temporal":[57],"resolution":[58],"signal-to-noise":[60],"ratio":[61],"conditions":[62],"be":[64,85],"effective.":[65],"In":[66,109],"addition,":[67],"their":[68],"solutions":[69],"biased":[71],"towards":[72],"obtaining":[73],"accurate":[74],"first-order":[75],"statistics":[76,90],"(i.e.,":[77,91],"spike":[78,142],"detection)":[79],"via":[80],"spatiotemporal":[81],"priors,":[82],"may":[84],"detrimental":[86],"recovering":[88],"second-order":[89],"correlations).":[92],"Existing":[93],"methods":[94],"for":[95],"inferring":[96],"correlations":[98,120],"suffer":[103],"significant":[105],"bias":[106],"variability.":[108],"this":[110],"work,":[111],"we":[112],"propose":[113],"an":[114],"algorithm":[115],"directly":[117],"estimate":[118],"ensemble":[122],"imaging":[124],"data,":[125],"by":[126],"integrating":[127],"point":[130],"process":[131],"modeling":[132],"variational":[134],"Bayesian":[135],"inference,":[136],"with":[137],"no":[138],"recourse":[139],"intermediate":[141],"deconvolution.":[143],"We":[144],"demonstrate":[145],"through":[146],"simulation":[147],"studies":[148],"that":[149],"proposed":[151],"method":[152],"outperforms":[153],"existing":[154],"approaches":[155],"in":[156],"accurately":[157],"capturing":[158],"correlations.":[162]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
