{"id":"https://openalex.org/W4379794492","doi":"https://doi.org/10.3389/fncom.2023.1140782","title":"Information-theoretic analysis of Hierarchical Temporal Memory-Spatial Pooler algorithm with a new upper bound for the standard information bottleneck method","display_name":"Information-theoretic analysis of Hierarchical Temporal Memory-Spatial Pooler algorithm with a new upper bound for the standard information bottleneck method","publication_year":2023,"publication_date":"2023-06-07","ids":{"openalex":"https://openalex.org/W4379794492","doi":"https://doi.org/10.3389/fncom.2023.1140782","pmid":"https://pubmed.ncbi.nlm.nih.gov/37351534"},"language":"en","primary_location":{"id":"doi:10.3389/fncom.2023.1140782","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3389/fncom.2023.1140782","pdf_url":"https://www.frontiersin.org/articles/10.3389/fncom.2023.1140782/pdf?isPublishedV2=False","source":{"id":"https://openalex.org/S19778766","display_name":"Frontiers in Computational Neuroscience","issn_l":"1662-5188","issn":["1662-5188"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Computational Neuroscience","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.frontiersin.org/articles/10.3389/fncom.2023.1140782/pdf?isPublishedV2=False","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5087632616","display_name":"Shiva Sanati","orcid":null},"institutions":[{"id":"https://openalex.org/I86958956","display_name":"Ferdowsi University of Mashhad","ror":"https://ror.org/00g6ka752","country_code":"IR","type":"education","lineage":["https://openalex.org/I86958956"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Shiva Sanati","raw_affiliation_strings":["Department of Computer Engineering, Ferdowsi University of Mashhad, Mashhad, Iran"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Ferdowsi University of Mashhad, Mashhad, Iran","institution_ids":["https://openalex.org/I86958956"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019671134","display_name":"Modjtaba Rouhani","orcid":"https://orcid.org/0000-0003-2423-6715"},"institutions":[{"id":"https://openalex.org/I86958956","display_name":"Ferdowsi University of Mashhad","ror":"https://ror.org/00g6ka752","country_code":"IR","type":"education","lineage":["https://openalex.org/I86958956"]}],"countries":["IR"],"is_corresponding":true,"raw_author_name":"Modjtaba Rouhani","raw_affiliation_strings":["Department of Computer Engineering, Ferdowsi University of Mashhad, Mashhad, Iran"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Ferdowsi University of Mashhad, Mashhad, Iran","institution_ids":["https://openalex.org/I86958956"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038472266","display_name":"Ghosheh Abed Hodtani","orcid":"https://orcid.org/0000-0002-4337-1624"},"institutions":[{"id":"https://openalex.org/I86958956","display_name":"Ferdowsi University of Mashhad","ror":"https://ror.org/00g6ka752","country_code":"IR","type":"education","lineage":["https://openalex.org/I86958956"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Ghosheh Abed Hodtani","raw_affiliation_strings":["Department of Electrical Engineering, Ferdowsi University of Mashhad, Mashhad, Iran"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Ferdowsi University of Mashhad, Mashhad, Iran","institution_ids":["https://openalex.org/I86958956"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5019671134"],"corresponding_institution_ids":["https://openalex.org/I86958956"],"apc_list":{"value":3150,"currency":"CHF","value_usd":3801},"apc_paid":{"value":3150,"currency":"CHF","value_usd":3801},"fwci":0.5162,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.71525162,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"17","issue":null,"first_page":"1140782","last_page":"1140782"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.992900013923645,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.992900013923645,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9858999848365784,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11321","display_name":"Error Correcting Code Techniques","score":0.9768000245094299,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/mnist-database","display_name":"MNIST database","score":0.7113300561904907},{"id":"https://openalex.org/keywords/information-bottleneck-method","display_name":"Information bottleneck method","score":0.6412367820739746},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6333621740341187},{"id":"https://openalex.org/keywords/upper-and-lower-bounds","display_name":"Upper and lower bounds","score":0.5789201855659485},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5477525591850281},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5449063777923584},{"id":"https://openalex.org/keywords/fisher-information","display_name":"Fisher information","score":0.538950502872467},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.48748111724853516},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.46925732493400574},{"id":"https://openalex.org/keywords/logical-matrix","display_name":"Logical matrix","score":0.42606645822525024},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.42339539527893066},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3577776551246643},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.33765706419944763},{"id":"https://openalex.org/keywords/mutual-information","display_name":"Mutual information","score":0.32588815689086914},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.29126662015914917},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.27353137731552124},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.146497905254364}],"concepts":[{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.7113300561904907},{"id":"https://openalex.org/C60008888","wikidata":"https://www.wikidata.org/wiki/Q6031013","display_name":"Information bottleneck method","level":3,"score":0.6412367820739746},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6333621740341187},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.5789201855659485},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5477525591850281},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5449063777923584},{"id":"https://openalex.org/C29406490","wikidata":"https://www.wikidata.org/wiki/Q1420659","display_name":"Fisher information","level":2,"score":0.538950502872467},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.48748111724853516},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.46925732493400574},{"id":"https://openalex.org/C163561899","wikidata":"https://www.wikidata.org/wiki/Q1994977","display_name":"Logical matrix","level":3,"score":0.42606645822525024},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.42339539527893066},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3577776551246643},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33765706419944763},{"id":"https://openalex.org/C152139883","wikidata":"https://www.wikidata.org/wiki/Q252973","display_name":"Mutual information","level":2,"score":0.32588815689086914},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.29126662015914917},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.27353137731552124},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.146497905254364},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.0},{"id":"https://openalex.org/C2781311116","wikidata":"https://www.wikidata.org/wiki/Q83306","display_name":"Group (periodic table)","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3389/fncom.2023.1140782","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3389/fncom.2023.1140782","pdf_url":"https://www.frontiersin.org/articles/10.3389/fncom.2023.1140782/pdf?isPublishedV2=False","source":{"id":"https://openalex.org/S19778766","display_name":"Frontiers in Computational Neuroscience","issn_l":"1662-5188","issn":["1662-5188"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Computational Neuroscience","raw_type":"journal-article"},{"id":"pmid:37351534","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37351534","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in computational neuroscience","raw_type":"Journal Article"},{"id":"pmh:oai:pubmedcentral.nih.gov:10282945","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/10282945","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC10282945/pdf/fncom-17-1140782.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"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":"Front Comput Neurosci","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:9b5fb8a2728f4e1d8b3425e8f9fe78b9","is_oa":true,"landing_page_url":"https://doaj.org/article/9b5fb8a2728f4e1d8b3425e8f9fe78b9","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":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Frontiers in Computational Neuroscience, Vol 17 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3389/fncom.2023.1140782","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3389/fncom.2023.1140782","pdf_url":"https://www.frontiersin.org/articles/10.3389/fncom.2023.1140782/pdf?isPublishedV2=False","source":{"id":"https://openalex.org/S19778766","display_name":"Frontiers in Computational Neuroscience","issn_l":"1662-5188","issn":["1662-5188"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Computational Neuroscience","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2781629534","display_name":null,"funder_award_id":"10466","funder_id":"https://openalex.org/F4320313459","funder_display_name":"Cognitive Sciences and Technologies Council"}],"funders":[{"id":"https://openalex.org/F4320313459","display_name":"Cognitive Sciences and Technologies Council","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4379794492.pdf","grobid_xml":"https://content.openalex.org/works/W4379794492.grobid-xml"},"referenced_works_count":65,"referenced_works":["https://openalex.org/W59811500","https://openalex.org/W1686946872","https://openalex.org/W1994016554","https://openalex.org/W2033842946","https://openalex.org/W2042996829","https://openalex.org/W2073227393","https://openalex.org/W2074376560","https://openalex.org/W2085710442","https://openalex.org/W2086085567","https://openalex.org/W2104939199","https://openalex.org/W2113606819","https://openalex.org/W2126375903","https://openalex.org/W2133636714","https://openalex.org/W2141039087","https://openalex.org/W2145889472","https://openalex.org/W2150877487","https://openalex.org/W2152077395","https://openalex.org/W2165043502","https://openalex.org/W2169500239","https://openalex.org/W2222971467","https://openalex.org/W2403035479","https://openalex.org/W2414486637","https://openalex.org/W2473020868","https://openalex.org/W2899003677","https://openalex.org/W2913421131","https://openalex.org/W2922783569","https://openalex.org/W2946094116","https://openalex.org/W2950860789","https://openalex.org/W2963609447","https://openalex.org/W2964080999","https://openalex.org/W2964184826","https://openalex.org/W2991254490","https://openalex.org/W3007813665","https://openalex.org/W3014256626","https://openalex.org/W3022414928","https://openalex.org/W3039918539","https://openalex.org/W3083978735","https://openalex.org/W3108837972","https://openalex.org/W3126268389","https://openalex.org/W3133281257","https://openalex.org/W3156433428","https://openalex.org/W3197863729","https://openalex.org/W3213620795","https://openalex.org/W3217058134","https://openalex.org/W4200315381","https://openalex.org/W4210414750","https://openalex.org/W4281787199","https://openalex.org/W4283818141","https://openalex.org/W4284974723","https://openalex.org/W4285164152","https://openalex.org/W4287758328","https://openalex.org/W4290058690","https://openalex.org/W4292971241","https://openalex.org/W4293469690","https://openalex.org/W4297749952","https://openalex.org/W6637108112","https://openalex.org/W6676903177","https://openalex.org/W6679223688","https://openalex.org/W6688889381","https://openalex.org/W6729906282","https://openalex.org/W6733862737","https://openalex.org/W6752757957","https://openalex.org/W6760581627","https://openalex.org/W6779985859","https://openalex.org/W6839405725"],"related_works":["https://openalex.org/W2939693078","https://openalex.org/W2783047733","https://openalex.org/W4301016710","https://openalex.org/W4287238667","https://openalex.org/W3149287595","https://openalex.org/W3173203577","https://openalex.org/W4225670787","https://openalex.org/W2978039092","https://openalex.org/W4283805326","https://openalex.org/W3035096847"],"abstract_inverted_index":{"Hierarchical":[0],"Temporal":[1],"Memory":[2],"(HTM)":[3],"is":[4,21,51,108,193,228],"an":[5],"unsupervised":[6],"algorithm":[7,59,117,138,142,209],"in":[8,56,103,118,161,165,184,206],"machine":[9],"learning.":[10],"It":[11],"models":[12],"several":[13],"fundamental":[14],"neocortical":[15],"computational":[16],"principles.":[17],"Spatial":[18],"Pooler":[19],"(SP)":[20],"one":[22],"of":[23,27,34,63,114,125,239],"the":[24,28,49,54,57,61,67,92,112,115,136,158,166,169,177,185,189,207,222,240,248,252],"main":[25,82],"components":[26],"HTM,":[29],"which":[30,97],"continuously":[31],"encodes":[32],"streams":[33],"binary":[35],"input":[36,159,186],"from":[37,60],"various":[38,123],"layers":[39],"and":[40,74,122,130,173,201,216,251],"regions":[41],"into":[42],"sparse":[43,178],"distributed":[44],"representations.":[45],"In":[46,188],"this":[47,104],"paper,":[48],"goal":[50],"to":[52,100,110,135,147,150,154,157,211,229,236,258],"evaluate":[53,111],"sparsification":[55],"SP":[58,116,137,141,179,208,217,241],"perspective":[62],"information":[64,68,76,94],"theory":[65],"by":[66],"bottleneck":[69,95],"(IB),":[70],"Cramer-Rao":[71,253],"lower":[72,198,254],"bound,":[73],"Fisher":[75],"matrix.":[77],"This":[78,106],"paper":[79],"makes":[80],"two":[81],"contributions.":[83],"First,":[84],"we":[85,98],"introduce":[86],"a":[87,197,202,212],"new":[88],"upper":[89],"bound":[90,255],"for":[91],"standard":[93],"relation,":[96,191],"refer":[99],"as":[101],"modified-IB":[102,190],"paper.":[105],"measure":[107],"used":[109],"performance":[113,238],"different":[119,263],"sparsity":[120,204,220,234,264],"levels":[121],"amounts":[124],"noise.":[126,151],"The":[127,140,243],"MNIST,":[128],"Fashion-MNIST":[129],"NYC-Taxi":[131],"datasets":[132],"were":[133],"fed":[134],"separately.":[139],"with":[143,218],"learning":[144],"was":[145,182,246,256],"found":[146],"be":[148],"resistant":[149],"Adding":[152],"up":[153],"40%":[155],"noise":[156,199],"resulted":[160],"no":[162],"discernible":[163],"change":[164],"output.":[167],"Using":[168],"probabilistic":[170],"mapping":[171],"method":[172],"Hidden":[174],"Markov":[175],"Model,":[176],"output":[180,261],"representation":[181],"reconstructed":[183],"space.":[187],"it":[192],"numerically":[194],"calculated":[195],"that":[196,232],"level":[200,205],"higher":[203],"lead":[210],"more":[213,233],"effective":[214],"reconstruction":[215],"2%":[219],"produces":[221],"best":[223],"results.":[224],"Our":[225],"second":[226],"contribution":[227],"prove":[230],"mathematically":[231],"leads":[235],"better":[237],"algorithm.":[242],"data":[244],"distribution":[245],"considered":[247],"Cauchy":[249],"distribution,":[250],"analyzed":[257],"estimate":[259],"SP's":[260],"at":[262],"levels.":[265]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1}],"updated_date":"2026-08-24T07:32:12.397491","created_date":"2025-10-10T00:00:00"}
