{"id":"https://openalex.org/W7105692717","doi":"https://doi.org/10.1109/ijcnn64981.2025.11227225","title":"Modelling Reinforcement Learning in the Basal Ganglia: A Neuromodulated Approach on SpiNNaker","display_name":"Modelling Reinforcement Learning in the Basal Ganglia: A Neuromodulated Approach on SpiNNaker","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W7105692717","doi":"https://doi.org/10.1109/ijcnn64981.2025.11227225"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn64981.2025.11227225","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11227225","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","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":null,"display_name":"Enuganti Pavan Kumar","orcid":null},"institutions":[{"id":"https://openalex.org/I4210148827","display_name":"Birla Institute of Technology and Science, Pilani - Goa Campus","ror":"https://ror.org/046sh6j17","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210148827","https://openalex.org/I74796645"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Enuganti Pavan Kumar","raw_affiliation_strings":["BITS Pilani K. K. Birla Goa Campus,Department of Computer Science and Information Systems,Goa,India"],"affiliations":[{"raw_affiliation_string":"BITS Pilani K. K. Birla Goa Campus,Department of Computer Science and Information Systems,Goa,India","institution_ids":["https://openalex.org/I4210148827"]}]},{"author_position":"last","author":{"id":null,"display_name":"Basabdatta Sen Bhattacharya","orcid":null},"institutions":[{"id":"https://openalex.org/I4210148827","display_name":"Birla Institute of Technology and Science, Pilani - Goa Campus","ror":"https://ror.org/046sh6j17","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210148827","https://openalex.org/I74796645"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Basabdatta Sen Bhattacharya","raw_affiliation_strings":["BITS Pilani K. K. Birla Goa Campus,Department of Computer Science and Information Systems,Goa,India"],"affiliations":[{"raw_affiliation_string":"BITS Pilani K. K. Birla Goa Campus,Department of Computer Science and Information Systems,Goa,India","institution_ids":["https://openalex.org/I4210148827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210148827"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.51215849,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.5296000242233276,"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":0.5296000242233276,"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/T10919","display_name":"Neurological disorders and treatments","score":0.20509999990463257,"subfield":{"id":"https://openalex.org/subfields/2728","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.10670000314712524,"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/neuromorphic-engineering","display_name":"Neuromorphic engineering","score":0.8393999934196472},{"id":"https://openalex.org/keywords/neuromodulation","display_name":"Neuromodulation","score":0.5726000070571899},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.5723000168800354},{"id":"https://openalex.org/keywords/substantia-nigra","display_name":"Substantia nigra","score":0.4903999865055084},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.48159998655319214},{"id":"https://openalex.org/keywords/spike","display_name":"Spike (software development)","score":0.4625999927520752},{"id":"https://openalex.org/keywords/basal-ganglia","display_name":"Basal ganglia","score":0.4269999861717224},{"id":"https://openalex.org/keywords/synaptic-weight","display_name":"Synaptic weight","score":0.4244000017642975}],"concepts":[{"id":"https://openalex.org/C151927369","wikidata":"https://www.wikidata.org/wiki/Q1981312","display_name":"Neuromorphic engineering","level":3,"score":0.8393999934196472},{"id":"https://openalex.org/C2780375056","wikidata":"https://www.wikidata.org/wiki/Q905905","display_name":"Neuromodulation","level":3,"score":0.5726000070571899},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.5723000168800354},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5432000160217285},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.5049999952316284},{"id":"https://openalex.org/C2780938664","wikidata":"https://www.wikidata.org/wiki/Q753278","display_name":"Substantia nigra","level":4,"score":0.4903999865055084},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.48159998655319214},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47909998893737793},{"id":"https://openalex.org/C2781390188","wikidata":"https://www.wikidata.org/wiki/Q25203449","display_name":"Spike (software development)","level":2,"score":0.4625999927520752},{"id":"https://openalex.org/C2778187257","wikidata":"https://www.wikidata.org/wiki/Q464210","display_name":"Basal ganglia","level":3,"score":0.4269999861717224},{"id":"https://openalex.org/C66949984","wikidata":"https://www.wikidata.org/wiki/Q7662043","display_name":"Synaptic weight","level":3,"score":0.4244000017642975},{"id":"https://openalex.org/C2778738651","wikidata":"https://www.wikidata.org/wiki/Q16546687","display_name":"Novelty","level":2,"score":0.39579999446868896},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.3930000066757202},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.3869999945163727},{"id":"https://openalex.org/C67203356","wikidata":"https://www.wikidata.org/wiki/Q1321905","display_name":"Reinforcement","level":2,"score":0.3797000050544739},{"id":"https://openalex.org/C166109690","wikidata":"https://www.wikidata.org/wiki/Q4677422","display_name":"Action selection","level":3,"score":0.3603000044822693},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.352400004863739},{"id":"https://openalex.org/C11731999","wikidata":"https://www.wikidata.org/wiki/Q9067355","display_name":"Spiking neural network","level":3,"score":0.3303000032901764},{"id":"https://openalex.org/C2776773494","wikidata":"https://www.wikidata.org/wiki/Q3366041","display_name":"Pars compacta","level":5,"score":0.32690000534057617},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.305400013923645},{"id":"https://openalex.org/C112592302","wikidata":"https://www.wikidata.org/wiki/Q1207387","display_name":"Excitatory postsynaptic potential","level":3,"score":0.2825999855995178},{"id":"https://openalex.org/C513476851","wikidata":"https://www.wikidata.org/wiki/Q170304","display_name":"Dopamine","level":2,"score":0.26440000534057617},{"id":"https://openalex.org/C186565885","wikidata":"https://www.wikidata.org/wiki/Q1651163","display_name":"Biological neuron model","level":3,"score":0.26260000467300415},{"id":"https://openalex.org/C117838684","wikidata":"https://www.wikidata.org/wiki/Q533483","display_name":"Local field potential","level":2,"score":0.25189998745918274}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ijcnn64981.2025.11227225","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11227225","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},{"id":"pmh:oai:pure.atira.dk:openaire_cris_publications/5018e0fe-11e4-4e5b-8ad3-707e456b62a9","is_oa":false,"landing_page_url":"https://research.manchester.ac.uk/en/publications/5018e0fe-11e4-4e5b-8ad3-707e456b62a9","pdf_url":null,"source":{"id":"https://openalex.org/S4306400662","display_name":"Research Explorer (The University of Manchester)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I28407311","host_organization_name":"University of Manchester","host_organization_lineage":["https://openalex.org/I28407311"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Kumar, E P & Bhattacharya, B S 2025, 'Modelling Reinforcement Learning in the Basal Ganglia : A Neuromodulated Approach on SpiNNaker', Proceedings of the International Joint Conference on Neural Networks. https://doi.org/10.1109/IJCNN64981.2025.11227225","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.6841256022453308,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W60353549","https://openalex.org/W1624116415","https://openalex.org/W1905111456","https://openalex.org/W1970761553","https://openalex.org/W1988599808","https://openalex.org/W1995750091","https://openalex.org/W2000230365","https://openalex.org/W2009982011","https://openalex.org/W2011857818","https://openalex.org/W2020925019","https://openalex.org/W2026339353","https://openalex.org/W2035171463","https://openalex.org/W2038511109","https://openalex.org/W2038531929","https://openalex.org/W2049547155","https://openalex.org/W2078827060","https://openalex.org/W2090430619","https://openalex.org/W2092443407","https://openalex.org/W2116701810","https://openalex.org/W2122236492","https://openalex.org/W2147101007","https://openalex.org/W2149661045","https://openalex.org/W2150389614","https://openalex.org/W2164653071","https://openalex.org/W2569736129","https://openalex.org/W2747837840","https://openalex.org/W2787016195","https://openalex.org/W2790788952","https://openalex.org/W2898350988","https://openalex.org/W2969226897","https://openalex.org/W4242770316"],"related_works":[],"abstract_inverted_index":{"We":[0],"have":[1,70],"presented":[2],"brain-inspired":[3],"reinforcement":[4],"learning":[5,51],"using":[6,65],"a":[7,135,145,149,156,166,223],"model":[8,74,111,140,191],"of":[9,22,28,36,82,152],"the":[10,16,26,29,30,40,73,109,113,123,130,190,194,201],"Basal":[11],"Ganglia":[12],"(BG)":[13],"implemented":[14],"on":[15,63,233],"neuromorphic":[17,224,236],"computer":[18],"SpiNNaker.":[19],"The":[20,139,173],"novelty":[21],"this":[23],"work":[24,120,221],"is":[25,57,141,160,170,175,184],"inclusion":[27],"Substantia":[31],"Nigra":[32],"pars":[33],"compacta":[34],"population":[35],"BG":[37,110,203],"that":[38,61,76,200],"releases":[39],"neurochemical":[41],"Dopamine":[42],"(DA).":[43],"Neuromodulation":[44],"by":[45,52,96],"DA":[46],"allows":[47],"dynamic":[48],"synaptic":[49],"weight":[50],"rewarding":[53],"desired":[54],"actions.":[55],"This":[56],"unlike":[58,117],"previous":[59,119],"models":[60],"focused":[62],"action-selection":[64,231],"static":[66],"weights.":[67],"Furthermore,":[68],"we":[69,133],"scaled":[71],"up":[72],"such":[75],"there":[77],"are":[78,84,115],"two":[79],"channels,":[80],"each":[81],"which":[83],"trained":[85,131,205],"to":[86,92,108,143,186,189,192],"select":[87],"specific":[88],"actions":[89],"in":[90,118,148],"response":[91],"input":[93,106],"cues":[94],"provided":[95],"periodic":[97,178],"spike":[98,182],"trains.":[99],"Also,":[100],"both":[101],"fast":[102,124],"and":[103,180,214,230],"slow":[104],"excitatory":[105],"pathways":[107],"from":[112],"cortex":[114],"used,":[116],"where":[121],"only":[122],"synapses":[125],"were":[126],"modelled.":[127],"To":[128],"test":[129],"network,":[132],"simulated":[134],"robotic":[136],"navigation":[137],"system.":[138],"required":[142,195],"demonstrate":[144],"wall-following":[146,217],"behaviour":[147],"room":[150],"environment":[151,174],"different":[153],"dimensions.":[154],"Thus,":[155],"\u2018move":[157],"forward\u2019":[158],"action":[159,169],"selected":[161,171],"for":[162,226],"no":[163],"detected":[164],"obstacle;":[165],"\u2018turn":[167],"left\u2019":[168],"otherwise.":[172],"sensed":[176],"at":[177],"intervals":[179],"live":[181],"injection":[183],"used":[185],"provide":[187],"cue":[188],"take":[193],"action.":[196],"Our":[197],"results":[198],"show":[199],"two-channel":[202],"network":[204],"with":[206],"instrumental":[207],"conditioning":[208],"avoided":[209],"clashing":[210],"into":[211],"corners":[212],"successfully":[213],"retained":[215],"its":[216],"behaviour.":[218],"Overall,":[219],"our":[220],"provides":[222],"framework":[225],"implementing":[227],"robust":[228],"decision-making":[229],"systems":[232],"low-power":[234],"real-time":[235],"devices.":[237]},"counts_by_year":[],"updated_date":"2025-11-15T23:13:30.683059","created_date":"2025-11-14T00:00:00"}
