{"id":"https://openalex.org/W4416041540","doi":"https://doi.org/10.1016/j.neunet.2025.108311","title":"Synaptic pruning facilitates online Bayesian model selection","display_name":"Synaptic pruning facilitates online Bayesian model selection","publication_year":2025,"publication_date":"2025-11-08","ids":{"openalex":"https://openalex.org/W4416041540","doi":"https://doi.org/10.1016/j.neunet.2025.108311","pmid":"https://pubmed.ncbi.nlm.nih.gov/41289617"},"language":"en","primary_location":{"id":"doi:10.1016/j.neunet.2025.108311","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.neunet.2025.108311","pdf_url":null,"source":{"id":"https://openalex.org/S123019304","display_name":"Neural Networks","issn_l":"0893-6080","issn":["0893-6080","1879-2782"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Networks","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1016/j.neunet.2025.108311","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5097222248","display_name":"Ukyo T. Tazawa","orcid":"https://orcid.org/0009-0005-2763-7700"},"institutions":[{"id":"https://openalex.org/I2800939219","display_name":"RIKEN Center for Brain Science","ror":"https://ror.org/04j1n1c04","country_code":"JP","type":"facility","lineage":["https://openalex.org/I2800939219","https://openalex.org/I4210110652"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Ukyo T. Tazawa","raw_affiliation_strings":["Brain Intelligence Theory Unit, RIKEN Center for Brain Science, 2-1 Hirosawa, Wako, Saitama 351- 0198, Japan; Department of Systems Science, Graduate School of Informatics, Kyoto University, Kyoto-shi, Kyoto, 606-8501, Japan; Department of Biological Sciences, Graduate School of Science, The University of Tokyo, Bunkyo-ku, Tokyo, 113-0033, Japan. Electronic address: ukyo.tazawa@riken.jp"],"raw_orcid":"https://orcid.org/0009-0005-2763-7700","affiliations":[{"raw_affiliation_string":"Brain Intelligence Theory Unit, RIKEN Center for Brain Science, 2-1 Hirosawa, Wako, Saitama 351- 0198, Japan; Department of Systems Science, Graduate School of Informatics, Kyoto University, Kyoto-shi, Kyoto, 606-8501, Japan; Department of Biological Sciences, Graduate School of Science, The University of Tokyo, Bunkyo-ku, Tokyo, 113-0033, Japan. Electronic address: ukyo.tazawa@riken.jp","institution_ids":["https://openalex.org/I2800939219"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066085950","display_name":"Takuya Isomura","orcid":"https://orcid.org/0000-0003-2960-4919"},"institutions":[{"id":"https://openalex.org/I2800939219","display_name":"RIKEN Center for Brain Science","ror":"https://ror.org/04j1n1c04","country_code":"JP","type":"facility","lineage":["https://openalex.org/I2800939219","https://openalex.org/I4210110652"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takuya Isomura","raw_affiliation_strings":["Brain Intelligence Theory Unit, RIKEN Center for Brain Science, 2-1 Hirosawa, Wako, Saitama 351- 0198, Japan. Electronic address: takuya.isomura@riken.jp"],"raw_orcid":"https://orcid.org/0000-0003-2960-4919","affiliations":[{"raw_affiliation_string":"Brain Intelligence Theory Unit, RIKEN Center for Brain Science, 2-1 Hirosawa, Wako, Saitama 351- 0198, Japan. Electronic address: takuya.isomura@riken.jp","institution_ids":["https://openalex.org/I2800939219"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I2800939219"],"apc_list":{"value":3350,"currency":"USD","value_usd":3350},"apc_paid":{"value":3350,"currency":"USD","value_usd":3350},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.27609186,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"195","issue":null,"first_page":"108311","last_page":"108311"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.22579999268054962,"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"}},"topics":[{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.22579999268054962,"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"}},{"id":"https://openalex.org/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.11959999799728394,"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/T10581","display_name":"Neural dynamics and brain function","score":0.1185000017285347,"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/pruning","display_name":"Pruning","score":0.7421000003814697},{"id":"https://openalex.org/keywords/synaptic-pruning","display_name":"Synaptic pruning","score":0.5928000211715698},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.49869999289512634},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.4871000051498413},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.44209998846054077},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.43970000743865967},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.42879998683929443},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4156000018119812},{"id":"https://openalex.org/keywords/model-selection","display_name":"Model selection","score":0.350600004196167}],"concepts":[{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.7421000003814697},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7009000182151794},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6766999959945679},{"id":"https://openalex.org/C2778399782","wikidata":"https://www.wikidata.org/wiki/Q2124069","display_name":"Synaptic pruning","level":4,"score":0.5928000211715698},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5695000290870667},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.49869999289512634},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.4871000051498413},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.44209998846054077},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.43970000743865967},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.42879998683929443},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4156000018119812},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.350600004196167},{"id":"https://openalex.org/C71983512","wikidata":"https://www.wikidata.org/wiki/Q7915687","display_name":"Variable-order Bayesian network","level":4,"score":0.3483999967575073},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.33500000834465027},{"id":"https://openalex.org/C82142266","wikidata":"https://www.wikidata.org/wiki/Q3456604","display_name":"Dynamic Bayesian network","level":3,"score":0.3345000147819519},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.33000001311302185},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.3287000060081482},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.3264999985694885},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.31709998846054077},{"id":"https://openalex.org/C155846161","wikidata":"https://www.wikidata.org/wiki/Q1143367","display_name":"Graphical model","level":2,"score":0.31130000948905945},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.29429998993873596},{"id":"https://openalex.org/C27158222","wikidata":"https://www.wikidata.org/wiki/Q5532422","display_name":"Generalizability theory","level":2,"score":0.2761000096797943},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.2667999863624573},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.2556999921798706}],"mesh":[{"descriptor_ui":"D000818","descriptor_name":"Animals","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000818","descriptor_name":"Animals","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000818","descriptor_name":"Animals","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001499","descriptor_name":"Bayes Theorem","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001499","descriptor_name":"Bayes Theorem","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001499","descriptor_name":"Bayes Theorem","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003198","descriptor_name":"Computer Simulation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003198","descriptor_name":"Computer Simulation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003198","descriptor_name":"Computer Simulation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007858","descriptor_name":"Learning","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":false},{"descriptor_ui":"D007858","descriptor_name":"Learning","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":false},{"descriptor_ui":"D007858","descriptor_name":"Learning","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":false},{"descriptor_ui":"D008959","descriptor_name":"Models, Neurological","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D008959","descriptor_name":"Models, Neurological","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D008959","descriptor_name":"Models, Neurological","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D013569","descriptor_name":"Synapses","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":true},{"descriptor_ui":"D013569","descriptor_name":"Synapses","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":true},{"descriptor_ui":"D013569","descriptor_name":"Synapses","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":2,"locations":[{"id":"doi:10.1016/j.neunet.2025.108311","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.neunet.2025.108311","pdf_url":null,"source":{"id":"https://openalex.org/S123019304","display_name":"Neural Networks","issn_l":"0893-6080","issn":["0893-6080","1879-2782"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Networks","raw_type":"journal-article"},{"id":"pmid:41289617","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41289617","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":"Neural networks : the official journal of the International Neural Network Society","raw_type":null}],"best_oa_location":{"id":"doi:10.1016/j.neunet.2025.108311","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.neunet.2025.108311","pdf_url":null,"source":{"id":"https://openalex.org/S123019304","display_name":"Neural Networks","issn_l":"0893-6080","issn":["0893-6080","1879-2782"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Networks","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5625190163","display_name":null,"funder_award_id":"JP23wm0625001","funder_id":"https://openalex.org/F4320311405","funder_display_name":"Japan Agency for Medical Research and Development"},{"id":"https://openalex.org/G6996123391","display_name":null,"funder_award_id":"JPMJCR22P1","funder_id":"https://openalex.org/F4320338075","funder_display_name":"Core Research for Evolutional Science and Technology"},{"id":"https://openalex.org/G862421073","display_name":null,"funder_award_id":"JP23H04973","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320311405","display_name":"Japan Agency for Medical Research and Development","ror":"https://ror.org/004rtk039"},{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"},{"id":"https://openalex.org/F4320334789","display_name":"Japan Science and Technology Agency","ror":"https://ror.org/00097mb19"},{"id":"https://openalex.org/F4320338075","display_name":"Core Research for Evolutional Science and Technology","ror":"https://ror.org/00097mb19"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1483895559","https://openalex.org/W1563427807","https://openalex.org/W1985940938","https://openalex.org/W2009375605","https://openalex.org/W2034388718","https://openalex.org/W2037537409","https://openalex.org/W2050066016","https://openalex.org/W2060386917","https://openalex.org/W2061191702","https://openalex.org/W2061304498","https://openalex.org/W2066887656","https://openalex.org/W2070665556","https://openalex.org/W2073335501","https://openalex.org/W2123713131","https://openalex.org/W2129501932","https://openalex.org/W2135017741","https://openalex.org/W2147008239","https://openalex.org/W2148764920","https://openalex.org/W2170789952","https://openalex.org/W2211598849","https://openalex.org/W2286353276","https://openalex.org/W2574596077","https://openalex.org/W2743911451","https://openalex.org/W2780064148","https://openalex.org/W3037787879","https://openalex.org/W3087248248","https://openalex.org/W3110215849","https://openalex.org/W3164849465","https://openalex.org/W3207964041","https://openalex.org/W4205386412","https://openalex.org/W4385630601","https://openalex.org/W4399849626","https://openalex.org/W4403558626"],"related_works":[],"abstract_inverted_index":{"Identifying":[0],"appropriate":[1],"structures":[2],"for":[3,10,83,101],"generative":[4],"or":[5],"world":[6],"models":[7],"is":[8,41,109],"essential":[9],"both":[11],"biological":[12],"organisms":[13],"and":[14,68,89,114,120,154],"machines.":[15],"This":[16,93],"work":[17],"shows":[18],"that":[19,40,77,126,143],"synaptic":[20,37,55,72,144],"pruning":[21,38,57,145],"facilitates":[22],"efficient":[23,90],"statistical":[24],"structure":[25,100,152],"learning.":[26],"We":[27],"extend":[28],"previously":[29],"established":[30],"canonical":[31],"neural":[32],"networks":[33],"to":[34,44,62,81],"derive":[35],"a":[36,98,148],"scheme":[39],"formally":[42],"equivalent":[43],"an":[45],"online":[46],"Bayesian":[47,54,136],"model":[48,56,91,129,137],"selection.":[49],"The":[50],"proposed":[51],"scheme,":[52],"termed":[53],"(BSyMP),":[58],"utilizes":[59],"connectivity":[60],"parameters":[61,79],"switch":[63],"between":[64],"the":[65,95,102,107,134,157],"presence":[66],"(ON)":[67],"absence":[69],"(OFF)":[70],"of":[71,97],"connections.":[73],"Mathematical":[74],"analyses":[75],"reveal":[76],"these":[78],"converge":[80],"zero":[82],"uninformative":[84],"connections,":[85],"thus":[86],"providing":[87],"reliable":[88],"reduction.":[92],"enables":[94],"identification":[96],"plausible":[99],"environmental":[103],"model,":[104],"particularly":[105],"when":[106],"environment":[108],"characterized":[110],"by":[111],"sparse":[112],"likelihood":[113],"transition":[115],"matrices.":[116],"Through":[117],"causal":[118],"inference":[119],"rule":[121],"learning":[122,153],"simulations,":[123],"we":[124],"demonstrate":[125],"BSyMP":[127],"achieves":[128],"reduction":[130,138],"more":[131],"efficiently":[132],"than":[133],"conventional":[135],"scheme.":[139],"These":[140],"findings":[141],"indicate":[142],"could":[146],"be":[147],"neuronal":[149],"substrate":[150],"underlying":[151],"generalizability":[155],"in":[156],"brain.":[158]},"counts_by_year":[],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-11-08T00:00:00"}
