{"id":"https://openalex.org/W2017737387","doi":"https://doi.org/10.1109/jproc.2014.2346465","title":"Reconstructing Natural Visual Scenes From Spike Times","display_name":"Reconstructing Natural Visual Scenes From Spike Times","publication_year":2014,"publication_date":"2014-08-28","ids":{"openalex":"https://openalex.org/W2017737387","doi":"https://doi.org/10.1109/jproc.2014.2346465","mag":"2017737387"},"language":"en","primary_location":{"id":"doi:10.1109/jproc.2014.2346465","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jproc.2014.2346465","pdf_url":null,"source":{"id":"https://openalex.org/S68686220","display_name":"Proceedings of the IEEE","issn_l":"0018-9219","issn":["0018-9219","1558-2256"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the IEEE","raw_type":"journal-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/A5040758341","display_name":"Aurel A. Lazar","orcid":"https://orcid.org/0000-0003-4261-8709"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Aurel A. Lazar","raw_affiliation_strings":["Department of Electrical Engineering, Columbia University, New York, NY, USA","Dept. of Electr. Eng, Columbia Univ., New York, NY, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Columbia University, New York, NY, USA","institution_ids":["https://openalex.org/I78577930"]},{"raw_affiliation_string":"Dept. of Electr. Eng, Columbia Univ., New York, NY, USA","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091137440","display_name":"Yiyin Zhou","orcid":"https://orcid.org/0000-0003-4618-4039"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yiyin Zhou","raw_affiliation_strings":["Department of Electrical Engineering, Columbia University, New York, NY, USA","Dept. of Electr. Eng, Columbia Univ., New York, NY, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Columbia University, New York, NY, USA","institution_ids":["https://openalex.org/I78577930"]},{"raw_affiliation_string":"Dept. of Electr. Eng, Columbia Univ., New York, NY, USA","institution_ids":["https://openalex.org/I78577930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5040758341"],"corresponding_institution_ids":["https://openalex.org/I78577930"],"apc_list":null,"apc_paid":null,"fwci":0.7656,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.69443407,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"102","issue":"10","first_page":"1500","last_page":"1519"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10581","display_name":"Neural dynamics and brain function","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9983000159263611,"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"}},{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9976999759674072,"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/computer-science","display_name":"Computer science","score":0.7601653337478638},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.7254759669303894},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.48636892437934875},{"id":"https://openalex.org/keywords/spike-sorting","display_name":"Spike sorting","score":0.47936755418777466},{"id":"https://openalex.org/keywords/neural-decoding","display_name":"Neural decoding","score":0.4202684760093689},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41124409437179565},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3279685974121094}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7601653337478638},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.7254759669303894},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.48636892437934875},{"id":"https://openalex.org/C2777613131","wikidata":"https://www.wikidata.org/wiki/Q2003571","display_name":"Spike sorting","level":3,"score":0.47936755418777466},{"id":"https://openalex.org/C40743351","wikidata":"https://www.wikidata.org/wiki/Q7002049","display_name":"Neural decoding","level":3,"score":0.4202684760093689},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41124409437179565},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3279685974121094},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jproc.2014.2346465","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jproc.2014.2346465","pdf_url":null,"source":{"id":"https://openalex.org/S68686220","display_name":"Proceedings of the IEEE","issn_l":"0018-9219","issn":["0018-9219","1558-2256"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the IEEE","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6399999856948853,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":92,"referenced_works":["https://openalex.org/W285212305","https://openalex.org/W316919195","https://openalex.org/W626285023","https://openalex.org/W1236573242","https://openalex.org/W1512746852","https://openalex.org/W1533072162","https://openalex.org/W1565176583","https://openalex.org/W1599353429","https://openalex.org/W1762465686","https://openalex.org/W1844800426","https://openalex.org/W1914401667","https://openalex.org/W1963694549","https://openalex.org/W1964602001","https://openalex.org/W1965673217","https://openalex.org/W1966018938","https://openalex.org/W1968661899","https://openalex.org/W1974570689","https://openalex.org/W1975003449","https://openalex.org/W1979275115","https://openalex.org/W1980178290","https://openalex.org/W1985940938","https://openalex.org/W1986504446","https://openalex.org/W1988849438","https://openalex.org/W1990870244","https://openalex.org/W1993182457","https://openalex.org/W1993214330","https://openalex.org/W1999352990","https://openalex.org/W2002663411","https://openalex.org/W2003596076","https://openalex.org/W2004530591","https://openalex.org/W2011459128","https://openalex.org/W2016574277","https://openalex.org/W2022491393","https://openalex.org/W2036193698","https://openalex.org/W2037030438","https://openalex.org/W2042226254","https://openalex.org/W2042934568","https://openalex.org/W2043630083","https://openalex.org/W2045216483","https://openalex.org/W2046424015","https://openalex.org/W2051115857","https://openalex.org/W2055179977","https://openalex.org/W2063640158","https://openalex.org/W2063861811","https://openalex.org/W2068920964","https://openalex.org/W2069519142","https://openalex.org/W2071147887","https://openalex.org/W2081411433","https://openalex.org/W2086898522","https://openalex.org/W2087314123","https://openalex.org/W2094048200","https://openalex.org/W2096352657","https://openalex.org/W2096964088","https://openalex.org/W2103043773","https://openalex.org/W2116360511","https://openalex.org/W2116531552","https://openalex.org/W2119533571","https://openalex.org/W2119648956","https://openalex.org/W2122541839","https://openalex.org/W2123997046","https://openalex.org/W2127130586","https://openalex.org/W2127388521","https://openalex.org/W2132549992","https://openalex.org/W2132593434","https://openalex.org/W2133665775","https://openalex.org/W2136391913","https://openalex.org/W2137389496","https://openalex.org/W2141729740","https://openalex.org/W2143879519","https://openalex.org/W2145889472","https://openalex.org/W2148008242","https://openalex.org/W2149288007","https://openalex.org/W2149316826","https://openalex.org/W2153940146","https://openalex.org/W2159198041","https://openalex.org/W2161836526","https://openalex.org/W2162572758","https://openalex.org/W2164439699","https://openalex.org/W2166500461","https://openalex.org/W2212384750","https://openalex.org/W2744834436","https://openalex.org/W2950044521","https://openalex.org/W4212952892","https://openalex.org/W4238614602","https://openalex.org/W4239849190","https://openalex.org/W4242870395","https://openalex.org/W4243872399","https://openalex.org/W4249122194","https://openalex.org/W4252713891","https://openalex.org/W4298876635","https://openalex.org/W4301319368","https://openalex.org/W6983726978"],"related_works":["https://openalex.org/W2368824897","https://openalex.org/W1508050556","https://openalex.org/W1910862367","https://openalex.org/W2379365082","https://openalex.org/W2370747590","https://openalex.org/W2030109976","https://openalex.org/W2369260257","https://openalex.org/W2098373948","https://openalex.org/W2742276804","https://openalex.org/W4211069933"],"abstract_inverted_index":{"In":[0,128],"this":[1],"paper,":[2],"we":[3,91,133,195],"investigate":[4,226],"neural":[5,77,105,122],"circuit":[6,123],"architectures":[7],"encoding":[8,78,89,106,186,201],"natural":[9,140,205],"visual":[10,117,141,206],"scenes":[11,207],"with":[12,23,96,124,151,154],"neuron":[13,149],"models":[14,32,150],"consisting":[15],"of":[16,33,35,66,72,76,131,139,161,198,204,211,229],"dendritic":[17,44],"stimulus":[18],"processors":[19],"(DSPs)":[20],"in":[21,184,232],"cascade":[22],"biophysical":[24],"spike":[25,48],"generators":[26],"(BSGs).":[27],"DSPs":[28],"serve":[29],"as":[30,107],"functional":[31],"processing":[34,213],"stimuli":[36,118],"up":[37],"to":[38,58,147,168],"and":[39,80,103,156,202,225,236],"including":[40],"the":[41,51,88,93,129,145,159,162,185,218,227,233],"neuron's":[42],"active":[43],"tree.":[45],"BSGs":[46,67,153],"model":[47],"generation":[49],"at":[50],"axon":[52],"hillock":[53],"level":[54],"where":[55],"neurons":[56],"respond":[57],"aggregated":[59],"synaptic":[60],"currents.":[61],"The":[62],"highly":[63],"nonlinear":[64],"behavior":[65],"calls":[68],"for":[69,84,172,237],"novel":[70,81],"methods":[71],"input/output":[73],"(I/O)":[74],"analysis":[75],"circuits":[79],"decoding":[82,113,165,203],"algorithms":[83],"signal":[85,175,219,230],"recovery.":[86],"On":[87],"side":[90],"characterize":[92],"BSG":[94],"I/O":[95],"a":[97,112,121,173,209],"phase":[98],"response":[99],"curve":[100],"(PRC)":[101],"manifold":[102],"interpret":[104],"generalized":[108],"sampling.":[109],"We":[110,143,216],"provide":[111],"algorithm":[114],"that":[115,181],"recovers":[116],"encoded":[119],"by":[120],"intrinsic":[125],"noise":[126,223],"sources.":[127],"absence":[130],"noise,":[132],"give":[134],"conditions":[135,224],"on":[136,208],"perfect":[137],"reconstruction":[138,220],"scenes.":[142],"extend":[144],"architecture":[146],"encompass":[148],"on-off":[152],"self-":[155],"cross-feedback.":[157],"With":[158],"help":[160],"PRC":[163],"manifold,":[164],"is":[166],"shown":[167],"be":[169,190],"tractable":[170],"even":[171],"wide":[174],"dynamic":[176],"range.":[177],"Consequently,":[178],"bias":[179],"currents":[180],"were":[182],"essential":[183],"process":[187],"can":[188],"largely":[189],"reduced":[191],"or":[192],"eliminated.":[193],"Finally,":[194],"present":[196],"examples":[197],"massively":[199],"parallel":[200],"cluster":[210],"graphical":[212],"units":[214],"(GPUs).":[215],"evaluate":[217],"under":[221],"different":[222,238],"performance":[228],"recovery":[231],"Nyquist":[234],"region":[235],"temporal":[239],"bandwidths.":[240]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":2},{"year":2014,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
