{"id":"https://openalex.org/W7166535333","doi":"https://doi.org/10.48550/arxiv.2606.27783","title":"CANNs: A Toolkit for Research on Continuous Attractor Neural Networks","display_name":"CANNs: A Toolkit for Research on Continuous Attractor Neural Networks","publication_year":2026,"publication_date":"2026-06-26","ids":{"openalex":"https://openalex.org/W7166535333","doi":"https://doi.org/10.48550/arxiv.2606.27783"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.27783","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.27783","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.27783","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5104218742","display_name":"Sichao He","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"He, Sichao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5099163751","display_name":"Aiersi Tuerhong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tuerhong, Aiersi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124808529","display_name":"Shangjun She","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"She, Shangjun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043393453","display_name":"Tianhao Chu","orcid":"https://orcid.org/0000-0001-9910-9361"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chu, Tianhao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102794505","display_name":"Yuling Wu","orcid":"https://orcid.org/0000-0003-3927-479X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Yuling","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026227666","display_name":"Junfeng Zuo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zuo, Junfeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5139599577","display_name":"Si Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Si","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10448","display_name":"Memory and Neural Mechanisms","score":0.8434000015258789,"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/T10448","display_name":"Memory and Neural Mechanisms","score":0.8434000015258789,"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/T10581","display_name":"Neural dynamics and brain function","score":0.07039999961853027,"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/T11094","display_name":"Face Recognition and Perception","score":0.020999999716877937,"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/attractor","display_name":"Attractor","score":0.6841999888420105},{"id":"https://openalex.org/keywords/python","display_name":"Python (programming language)","score":0.5770000219345093},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.4765999913215637},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4650999903678894},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.39489999413490295},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.36160001158714294},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.3531000018119812},{"id":"https://openalex.org/keywords/landmark","display_name":"Landmark","score":0.32600000500679016}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7267000079154968},{"id":"https://openalex.org/C164380108","wikidata":"https://www.wikidata.org/wiki/Q507187","display_name":"Attractor","level":2,"score":0.6841999888420105},{"id":"https://openalex.org/C519991488","wikidata":"https://www.wikidata.org/wiki/Q28865","display_name":"Python (programming language)","level":2,"score":0.5770000219345093},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.4765999913215637},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4650999903678894},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.39489999413490295},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.36160001158714294},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3580999970436096},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.3531000018119812},{"id":"https://openalex.org/C2780297707","wikidata":"https://www.wikidata.org/wiki/Q4895393","display_name":"Landmark","level":2,"score":0.32600000500679016},{"id":"https://openalex.org/C184720557","wikidata":"https://www.wikidata.org/wiki/Q7825049","display_name":"Topology (electrical circuits)","level":2,"score":0.3206000030040741},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.31630000472068787},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.30079999566078186},{"id":"https://openalex.org/C162319229","wikidata":"https://www.wikidata.org/wiki/Q175263","display_name":"Data structure","level":2,"score":0.3003000020980835},{"id":"https://openalex.org/C2779623528","wikidata":"https://www.wikidata.org/wiki/Q864377","display_name":"Multiset","level":2,"score":0.2745000123977661},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.27219998836517334},{"id":"https://openalex.org/C96522737","wikidata":"https://www.wikidata.org/wiki/Q17148345","display_name":"Path integration","level":2,"score":0.2671999931335449},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.26489999890327454},{"id":"https://openalex.org/C2983008078","wikidata":"https://www.wikidata.org/wiki/Q863495","display_name":"Grid cell","level":3,"score":0.2581000030040741},{"id":"https://openalex.org/C151927369","wikidata":"https://www.wikidata.org/wiki/Q1981312","display_name":"Neuromorphic engineering","level":3,"score":0.2513999938964844}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.27783","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.27783","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.27783","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.27783","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Continuous":[0],"attractor":[1,63,114,173],"neural":[2,166],"networks":[3],"(CANNs)":[4],"are":[5],"the":[6,12,28,57,81],"canonical":[7],"computational":[8],"framework":[9],"for":[10,128,141,147],"how":[11],"brain":[13],"encodes":[14],"continuous":[15],"variables":[16],"such":[17],"as":[18],"spatial":[19],"position,":[20],"head":[21],"direction,":[22,25],"and":[23,26,37,56,112,125,144,162,171,199],"movement":[24],"explain":[27],"activity":[29],"of":[30],"hippocampal":[31],"place":[32],"cells,":[33,36],"entorhinal":[34],"grid":[35,106],"head-direction":[38],"cells.":[39],"CANN":[40,83,188],"research,":[41],"however,":[42],"is":[43],"fragmented:":[44],"most":[45],"results":[46,189],"rest":[47],"on":[48,97],"lab-specific":[49],"implementations,":[50],"general-purpose":[51],"simulators":[52],"lack":[53],"CANN-specific":[54],"abstractions,":[55],"path":[58,201],"from":[59],"spike":[60],"trains":[61],"to":[62,164,168],"geometry":[64],"in":[65,175,196],"real":[66,176],"recordings":[67,167],"lacks":[68],"a":[69,75,94,134,156],"standardized":[70,101],"toolkit.":[71],"Here,":[72],"we":[73],"present":[74],"comprehensive":[76],"open-source":[77],"toolkit":[78,179],"that":[79,99,185],"unifies":[80],"full":[82],"research":[84],"workflow.":[85],"It":[86],"combines":[87],"three":[88],"tightly":[89],"integrated":[90],"components:":[91],"1)":[92],"canns,":[93],"Python":[95],"library":[96],"BrainPy/JAX":[98],"provides":[100],"1D/2D":[102],"CANNs,":[103],"spike-frequency-adaptation":[104],"variants,":[105],"cell":[107],"networks,":[108],"hierarchical":[109,200],"path-integration":[110],"models,":[111],"brain-inspired":[113],"architectures,":[115],"together":[116],"with":[117,181],"curated":[118],"datasets,":[119],"task":[120],"generators,":[121],"an":[122],"analyzer":[123],"module":[124],"trainer":[126],"modules":[127],"biologically":[129],"plausible":[130],"plasticity;":[131],"2)":[132],"canns-lib,":[133],"Rust":[135],"acceleration":[136],"backend":[137],"delivering":[138],"hundreds-of-times":[139],"speedups":[140],"spatial-navigation":[142],"workloads":[143],"modest":[145],"gains":[146],"Ripser-based":[148],"persistent":[149,160],"homology;":[150],"3)":[151],"ASA":[152],"(Attractor":[153],"Structure":[154],"Analyzer),":[155],"PySide6":[157],"pipeline":[158],"applying":[159],"homology":[161],"cohomology":[163],"experimental":[165],"detect":[169],"ring-like":[170],"toroidal":[172],"signatures":[174],"data.":[177],"The":[178],"ships":[180],"full-detail":[182],"reproducible":[183],"pipelines":[184],"recover":[186],"recent":[187],"including":[190],"SFA-driven":[191],"anticipative":[192],"tracking,":[193],"theta":[194],"sweeps":[195],"head-direction/place/grid":[197],"systems,":[198],"integration.":[202]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-30T00:00:00"}