{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,12]],"date-time":"2026-06-12T06:49:14Z","timestamp":1781246954681,"version":"3.54.1"},"reference-count":41,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2022,1,24]],"date-time":"2022-01-24T00:00:00Z","timestamp":1642982400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,24]],"date-time":"2022-01-24T00:00:00Z","timestamp":1642982400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100013112","name":"transformation program of scientific and technological achievements of jiangsu provence","doi-asserted-by":"publisher","award":["2020-GX-12"],"award-info":[{"award-number":["2020-GX-12"]}],"id":[{"id":"10.13039\/501100013112","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003392","name":"natural science foundation of fujian province","doi-asserted-by":"publisher","award":["2019J01242"],"award-info":[{"award-number":["2019J01242"]}],"id":[{"id":"10.13039\/501100003392","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Cogn Comput"],"published-print":{"date-parts":[[2022,3]]},"DOI":"10.1007\/s12559-021-09971-1","type":"journal-article","created":{"date-parts":[[2022,1,24]],"date-time":"2022-01-24T00:05:27Z","timestamp":1642982727000},"page":"887-899","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["A Calibration-free Approach to Implementing P300-based Brain\u2013computer Interface"],"prefix":"10.1007","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5710-5231","authenticated-orcid":false,"given":"Zhihua","family":"Huang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiannan","family":"Guo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenming","family":"Zheng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yingjie","family":"Wu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhixiong","family":"Lin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huiru","family":"Zheng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2022,1,24]]},"reference":[{"key":"9971_CR1","doi-asserted-by":"crossref","unstructured":"Wolpaw JR, Wolpaw EW, editors. Brain-Computer Interfaces: Principles and Practice. New York, USA: Oxford University Press; 2012.","DOI":"10.1093\/acprof:oso\/9780195388855.001.0001"},{"key":"9971_CR2","doi-asserted-by":"crossref","unstructured":"Edelman BJ, Meng J, Suma D, Zurn C, Nagarajan E, Baxter BS, Cline CC, He B. Noninvasive neuroimaging enhances continuous neural tracking for device control.\u00a0Sci Robot.\u00a02019;4(31):eaaw6844.","DOI":"10.1126\/scirobotics.aaw6844"},{"key":"9971_CR3","doi-asserted-by":"crossref","unstructured":"Shukla PK, Chaurasiya RK, Verma S. Performance improvement of P300-based home appliances control classification using convolution neural network. Biomed Signal Process Control. 2021;63:102220.","DOI":"10.1016\/j.bspc.2020.102220"},{"key":"9971_CR4","doi-asserted-by":"crossref","unstructured":"Bauer R, Gharabaghi A. Reinforcement learning for adaptive threshold control of restorative brain-computer interfaces: a Bayesian simulation. Front Neurosci. 2015;9: Article 36.","DOI":"10.3389\/fnins.2015.00036"},{"key":"9971_CR5","doi-asserted-by":"crossref","unstructured":"Abiri R, Borhani S, Sellers EW, Jiang Y, Zhao X. A comprehensive review of EEG-based brain-computer interface paradigms. J Neural Eng. 2019;16(1):011001.","DOI":"10.1088\/1741-2552\/aaf12e"},{"issue":"1\u20132","key":"9971_CR6","doi-asserted-by":"publisher","first-page":"151","DOI":"10.1007\/s10994-009-5152-4","volume":"79","author":"S Ben-David","year":"2010","unstructured":"Ben-David S, Blitzer J, Crammer K, Kulesza A, Pereira F, Vaughan JW. A theory of learning from different domains. Mach Learn. 2010;79(1\u20132):151\u201375.","journal-title":"Mach Learn"},{"issue":"10","key":"9971_CR7","doi-asserted-by":"publisher","first-page":"1345","DOI":"10.1109\/TKDE.2009.191","volume":"22","author":"SJ Pan","year":"2010","unstructured":"Pan SJ, Yang Q. A survey on transfer learning. IEEE Trans Knowl Data Eng. 2010;22(10):1345\u201359.","journal-title":"IEEE Trans Knowl Data Eng"},{"issue":"1","key":"9971_CR8","doi-asserted-by":"publisher","first-page":"20","DOI":"10.1109\/MCI.2015.2501545","volume":"11","author":"V Jayaram","year":"2016","unstructured":"Jayaram V, Alamgir M, Altun Y, Scholkopf B, Grosse-Wentrup M. Transfer learning in brain-computer interfaces. IEEE Comput Intell Mag. 2016;11(1):20\u201331.","journal-title":"IEEE Comput Intell Mag"},{"key":"9971_CR9","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.neucom.2020.09.017","volume":"421","author":"Z Wan","year":"2021","unstructured":"Wan Z, Yang R, Huang M, Zeng N, Liu X. A review on transfer learning in EEG signal analysis. Neurocomputing. 2021;421:1\u201314.","journal-title":"Neurocomputing"},{"key":"9971_CR10","doi-asserted-by":"publisher","first-page":"237","DOI":"10.1613\/jair.301","volume":"4","author":"LP Kaelbling","year":"1996","unstructured":"Kaelbling LP, Littman ML, Moore AW. Reinforcement learning: A survey. J Artif Intell Res. 1996;4:237\u201385.","journal-title":"J Artif Intell Res"},{"issue":"3","key":"9971_CR11","first-page":"551","volume":"7","author":"K Crammer","year":"2006","unstructured":"Crammer K, Dekel O, Shalev-Shwartz S, Singer Y. Online passive-aggressive algorithms. J Mach Learn Res. 2006;7(3):551\u201385.","journal-title":"J Mach Learn Res"},{"issue":"3\u20134","key":"9971_CR12","first-page":"157","volume":"2","author":"E Hazan","year":"2015","unstructured":"Hazan E. Introduction to online convex optimization. Foundations and Trends in Optimization. 2015;2(3\u20134):157\u2013325.","journal-title":"Foundations and Trends in Optimization"},{"issue":"9","key":"9971_CR13","doi-asserted-by":"publisher","first-page":"1305","DOI":"10.1016\/j.neunet.2009.06.003","volume":"22","author":"S Fazli","year":"2009","unstructured":"Fazli S, Popescu F, Dan\u00f3czy M, Blankertz B, M\u00fcller K-R, Grozea C. Subject-independent mental state classification in single trials. Neural Netw. 2009;22(9):1305\u201312.","journal-title":"Neural Netw"},{"key":"9971_CR14","doi-asserted-by":"crossref","unstructured":"Kindermans P-J, Tangermann M, M\u00fcller K-R, Schrauwen B. Integrating dynamic stopping, transfer learning and language models in an adaptive zero-training ERP speller. J Neural Eng. 2014;11(3):035005.","DOI":"10.1088\/1741-2560\/11\/3\/035005"},{"key":"9971_CR15","unstructured":"Gayraud NT, Rakotomamonjy A, Clerc M. Optimal transport applied to transfer learning for p300 detection. In: BCI 2017-7th Graz Brain-Computer Interface Conference.\u00a02017. p.\u00a06."},{"issue":"3","key":"9971_CR16","doi-asserted-by":"publisher","first-page":"602","DOI":"10.1109\/TNSRE.2018.2801887","volume":"26","author":"H Qi","year":"2018","unstructured":"Qi H, Xue Y, Xu L, Cao Y, Jiao X. A speedy calibration method using riemannian geometry measurement and other-subject samples on a P300 speller. IEEE Trans Neural Syst Rehabil Eng. 2018;26(3):602\u20138.","journal-title":"IEEE Trans Neural Syst Rehabil Eng"},{"key":"9971_CR17","doi-asserted-by":"crossref","unstructured":"H\u00fcbner D, Kindermans P-J, Verhoeven T, M\u00fcller K-R, Tangermann M. Rethinking BCI paradigm and machine learning algorithm as a symbiosis: Zero calibration, guaranteed convergence and high decoding performance. In: Brain-Computer Interface Research. Springer.\u00a02019. p.\u00a063\u201373.","DOI":"10.1007\/978-3-030-05668-1_6"},{"key":"9971_CR18","doi-asserted-by":"publisher","first-page":"74385","DOI":"10.1109\/ACCESS.2020.2988057","volume":"8","author":"J Lee","year":"2020","unstructured":"Lee J, Won K, Kwon M, Jun SC, Ahn M. CNN with large data achieves true zero-training in online P300 brain-computer interface. IEEE Access. 2020;8:74385\u2013400.","journal-title":"IEEE Access"},{"issue":"5","key":"9971_CR19","doi-asserted-by":"publisher","first-page":"1804","DOI":"10.3390\/app10051804","volume":"10","author":"F Li","year":"2020","unstructured":"Li F, Xia Y, Wang F, Zhang D, Li X, He F. Transfer learning algorithm of P300-EEG signal based on xdawn spatial filter and riemannian geometry classifier. Appl Sci. 2020;10(5):1804.","journal-title":"Appl Sci"},{"issue":"2","key":"9971_CR20","doi-asserted-by":"publisher","first-page":"164","DOI":"10.1109\/TNSRE.2006.875555","volume":"14","author":"A Buttfield","year":"2006","unstructured":"Buttfield A, Ferrez PW, Millan JR. Towards a robust BCI: error potentials and online learning. IEEE Trans Neural Syst Rehabil Eng. 2006;14(2):164\u20138.","journal-title":"IEEE Trans Neural Syst Rehabil Eng"},{"key":"9971_CR21","doi-asserted-by":"crossref","unstructured":"Kindermans P-J, Schreuder M, Schrauwen B, M\u00fcller K-R, Tangermann M. True zero-training brain-computer interfacing-an online study. PloS One. 2014;9(7):e102504.","DOI":"10.1371\/journal.pone.0102504"},{"key":"9971_CR22","doi-asserted-by":"crossref","unstructured":"Grizou J, Iturrate I, Montesano L, Oudeyer P-Y, Lopes M. Calibration-Free BCI Based Control. In: Twenty-Eighth AAAI Conference on Artificial Intelligence. Quebec, Canada;\u00a02014.\u00a0p.\u00a01\u20138.","DOI":"10.1609\/aaai.v28i1.8923"},{"key":"9971_CR23","doi-asserted-by":"publisher","first-page":"123","DOI":"10.1016\/j.patrec.2017.06.004","volume":"107","author":"W Liu","year":"2018","unstructured":"Liu W, Zhang L, Tao D, Cheng J. Reinforcement online learning for emotion prediction by using physiological signals. Pattern Recogn Lett. 2018;107:123\u201330.","journal-title":"Pattern Recogn Lett"},{"key":"9971_CR24","doi-asserted-by":"crossref","unstructured":"Ma Z, Cheng J, Tao D. Online learning using projections onto shrinkage closed balls for adaptive brain-computer interface. Pattern Recogn. 2020;97:107017.","DOI":"10.1016\/j.patcog.2019.107017"},{"issue":"6","key":"9971_CR25","doi-asserted-by":"publisher","first-page":"510","DOI":"10.1016\/0013-4694(88)90149-6","volume":"70","author":"LA Farwell","year":"1988","unstructured":"Farwell LA, Donchin E. Talking off the top of your head\u202f: toward a mental prosthesis utilizing event-related brain potentials. Electroencephalogr Clin Neurophysiol. 1988;70(6):510\u201323.","journal-title":"Electroencephalogr Clin Neurophysiol"},{"key":"9971_CR26","doi-asserted-by":"crossref","unstructured":"Li L, Chu W, Langford J, Schapire RE. A contextual-bandit approach to personalized news article recommendation. In: Proceedings of the 19th international conference on World wide web. 2010.\u00a0p.\u00a0661\u2013670.","DOI":"10.1145\/1772690.1772758"},{"key":"9971_CR27","doi-asserted-by":"publisher","first-page":"17562","DOI":"10.1038\/s41598-017-17682-7","volume":"7","author":"SK Kim","year":"2017","unstructured":"Kim SK, Kirchner EA, Stefes A, Kirchner F. Intrinsic interactive reinforcement learning-using error-related potentials for real world human-robot interaction. Sci Rep. 2017;7:17562.","journal-title":"Sci Rep"},{"issue":"6","key":"9971_CR28","doi-asserted-by":"publisher","first-page":"1034","DOI":"10.1109\/TBME.2004.827072","volume":"51","author":"G Schalk","year":"2004","unstructured":"Schalk G, McFarland DJ, Hinterberger T, Birbaumer N, Wolpaw JR. BCI2000: a general-purpose brain-computer interface (BCI) system. IEEE Trans Biomed Eng. 2004;51(6):1034\u201343.","journal-title":"IEEE Trans Biomed Eng"},{"key":"9971_CR29","doi-asserted-by":"crossref","unstructured":"Lotte F, Bougrain L, Cichocki A, Clerc M, Congedo M, Rakotomamonjy A, Yger F. A review of classification algorithms for EEG-based brain-computer interfaces: a 10 year update. J Neural Eng. 2018;15(3):031005.","DOI":"10.1088\/1741-2552\/aab2f2"},{"key":"9971_CR30","doi-asserted-by":"publisher","first-page":"524","DOI":"10.3389\/fnhum.2018.00524","volume":"12","author":"M Arvaneh","year":"2019","unstructured":"Arvaneh M, Robertson IH, Ward TE. A P300-based brain-computer interface for improving attention. Front Hum Neurosci. 2019;12:524.","journal-title":"Front Hum Neurosci"},{"key":"9971_CR31","doi-asserted-by":"crossref","unstructured":"Allison BZ, K\u00fcbler A, Jin J. 30+ years of P300 brain-computer interfaces. Psychophysiology. 2020;57(7):e13569.","DOI":"10.1111\/psyp.13569"},{"key":"9971_CR32","doi-asserted-by":"publisher","first-page":"63","DOI":"10.1016\/j.cobeha.2019.04.011","volume":"29","author":"AGE Collins","year":"2019","unstructured":"Collins AGE. Reinforcement learning: bringing together computation and cognition. Curr Opin Behav Sci. 2019;29:63\u20138.","journal-title":"Curr Opin Behav Sci"},{"key":"9971_CR33","doi-asserted-by":"publisher","first-page":"113","DOI":"10.1016\/j.neuroimage.2013.10.069","volume":"88","author":"EJ Lawrence","year":"2014","unstructured":"Lawrence EJ, Su L, Barker GJ, Medford N, Dalton J, Williams S, Birbaumer N, Veit R, Ranganatha S, Bodurka J. Self-regulation of the anterior insula: Reinforcement learning using real-time fMRI neurofeedback. Neuroimage. 2014;88:113\u201324.","journal-title":"Neuroimage"},{"key":"9971_CR34","doi-asserted-by":"publisher","first-page":"4429","DOI":"10.1038\/s41467-020-17828-8","volume":"11","author":"A Cortese","year":"2020","unstructured":"Cortese A, Lau H, Kawato M. Unconscious reinforcement learning of hidden brain states supported by confidence. Nat Commun. 2020;11:4429.","journal-title":"Nat Commun"},{"issue":"1","key":"9971_CR35","doi-asserted-by":"publisher","first-page":"80","DOI":"10.1080\/00401706.2000.10485983","volume":"42","author":"AE Hoerl","year":"2000","unstructured":"Hoerl AE, Kennard RW. Ridge regression: Biased estimation for nonorthogonal problems. Technometrics. 2000;42(1):80\u20136.","journal-title":"Technometrics"},{"key":"9971_CR36","unstructured":"Walsh TJ, Szita I, Diuk C, Littman ML. Exploring compact reinforcement-learning representations with linear regression. arXiv preprint\u00a0arXiv:1205.2606. 2012."},{"key":"9971_CR37","doi-asserted-by":"crossref","unstructured":"Huang Z, Zheng W, Wu Y, Wang Y. Ensemble or pool: A comprehensive study on transfer learning for c-VEP BCI during interpersonal interaction. J Neurosci Methods. 2020;343(4)108855.","DOI":"10.1016\/j.jneumeth.2020.108855"},{"issue":"7","key":"9971_CR38","doi-asserted-by":"publisher","first-page":"1109","DOI":"10.1016\/j.clinph.2010.01.030","volume":"121","author":"G Townsend","year":"2010","unstructured":"Townsend G, LaPallo B, Boulay C, Krusienski D, Frye G, Hauser C, Schwartz N, Vaughan T, Wolpaw J, Sellers E. A novel P300-based brain-computer interface stimulus presentation paradigm: Moving beyond rows and columns. Clin Neurophysiol. 2010;121(7):1109\u201320.","journal-title":"Clin Neurophysiol"},{"issue":"8","key":"9971_CR39","doi-asserted-by":"publisher","first-page":"861","DOI":"10.1016\/j.patrec.2005.10.010","volume":"27","author":"T Fawcett","year":"2006","unstructured":"Fawcett T. An introduction to ROC analysis. Pattern Recogn Lett. 2006;27(8):861\u201374.","journal-title":"Pattern Recogn. Lett."},{"key":"9971_CR40","doi-asserted-by":"crossref","unstructured":"Yuan P, Gao X, Allison B, Wang Y, Bin G, Gao S. A study of the existing problems of estimating the information transfer rate in online brain-computer interfaces. J Neural Eng. 2013;10(2):026014.","DOI":"10.1088\/1741-2560\/10\/2\/026014"},{"key":"9971_CR41","doi-asserted-by":"crossref","unstructured":"Mladenovic J, Frey J, Joffily M, Maby E, Lotte F, Mattout J. Active inference as a unifying, generic and adaptive framework for a P300-based BCI. J Neural Eng. 2020;17(1):016054.","DOI":"10.1088\/1741-2552\/ab5d5c"}],"container-title":["Cognitive Computation"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12559-021-09971-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s12559-021-09971-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12559-021-09971-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,24]],"date-time":"2023-01-24T07:33:11Z","timestamp":1674545591000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s12559-021-09971-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,1,24]]},"references-count":41,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2022,3]]}},"alternative-id":["9971"],"URL":"https:\/\/doi.org\/10.1007\/s12559-021-09971-1","relation":{},"ISSN":["1866-9956","1866-9964"],"issn-type":[{"value":"1866-9956","type":"print"},{"value":"1866-9964","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,1,24]]},"assertion":[{"value":"17 June 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 November 2021","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 January 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"All procedures performed in the study involving human participants were in accordance with the ethical standards of the Institutional Review Board at Fuzhou University and with the 1964 Helsinki declaration and its later amendments.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical Approval"}},{"value":"Informed consent was obtained from all individual participants included in the study.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed Consent"}},{"value":"No conflict of interest exists.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflicts of Interest"}}]}}