{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T23:15:41Z","timestamp":1774048541257,"version":"3.50.1"},"reference-count":46,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100015956","name":"Special Project for Research and Development in Key areas of Guangdong Province","doi-asserted-by":"publisher","award":["2023B0303030001"],"award-info":[{"award-number":["2023B0303030001"]}],"id":[{"id":"10.13039\/501100015956","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100012541","name":"Guangdong Innovative and Entrepreneurial Research Team Program","doi-asserted-by":"publisher","award":["2019ZT08X214"],"award-info":[{"award-number":["2019ZT08X214"]}],"id":[{"id":"10.13039\/100012541","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002855","name":"Ministry of Science and Technology of the People&apos;s Republic of China","doi-asserted-by":"publisher","award":["2021ZD0200700"],"award-info":[{"award-number":["2021ZD0200700"]}],"id":[{"id":"10.13039\/501100002855","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004000","name":"Guangzhou Municipal Science and Technology Program key projects","doi-asserted-by":"publisher","award":["2024A04J6310"],"award-info":[{"award-number":["2024A04J6310"]}],"id":[{"id":"10.13039\/501100004000","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62222603"],"award-info":[{"award-number":["62222603"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Pattern Recognition"],"published-print":{"date-parts":[[2026,10]]},"DOI":"10.1016\/j.patcog.2026.113272","type":"journal-article","created":{"date-parts":[[2026,2,21]],"date-time":"2026-02-21T23:31:24Z","timestamp":1771716684000},"page":"113272","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["CRIA: A cross-view interaction and instance-adapted pre-training framework for generalizable EEG representations"],"prefix":"10.1016","volume":"178","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-5172-6691","authenticated-orcid":false,"given":"Puchun","family":"Liu","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5451-7230","authenticated-orcid":false,"given":"C.L. Philip","family":"Chen","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0008-4346-7942","authenticated-orcid":false,"given":"Yubin","family":"He","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7025-6365","authenticated-orcid":false,"given":"Tong","family":"Zhang","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"issue":"17","key":"10.1016\/j.patcog.2026.113272_bib0001","first-page":"e1750","article-title":"Development of expert-level classification of seizures and rhythmic and periodic patterns during EEG interpretation","volume":"100","author":"Jing","year":"2023","journal-title":"Neurology"},{"issue":"3","key":"10.1016\/j.patcog.2026.113272_bib0002","doi-asserted-by":"crossref","first-page":"441","DOI":"10.1097\/00004691-199207010-00012","article-title":"High-frequency EEG activity at the start of seizures","volume":"9","author":"Arroyo","year":"1992","journal-title":"J. Clin. Neurophysiol."},{"key":"10.1016\/j.patcog.2026.113272_bib0003","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2024.111005","article-title":"PSSS-EEG: a probabilistic-masking self-supervised swin-transformer model for EEG-based drowsiness recognition","volume":"158","author":"Zhang","year":"2025","journal-title":"Pattern Recognit."},{"issue":"1","key":"10.1016\/j.patcog.2026.113272_bib0004","doi-asserted-by":"crossref","first-page":"379","DOI":"10.1109\/TAFFC.2019.2937768","article-title":"GCB-Net: graph convolutional broad network and its application in emotion recognition","volume":"13","author":"Zhang","year":"2019","journal-title":"IEEE Trans. Affect. Comput."},{"key":"10.1016\/j.patcog.2026.113272_bib0005","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2022.108833","article-title":"Visual-to-EEG cross-modal knowledge distillation for continuous emotion recognition","volume":"130","author":"Zhang","year":"2022","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.patcog.2026.113272_bib0006","first-page":"78240","article-title":"Biot: biosignal transformer for cross-data learning in the wild","volume":"36","author":"Yang","year":"2024","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.patcog.2026.113272_bib0007","unstructured":"W.-B. Jiang, L.-M. Zhao, B.-L. Lu, Large brain model for learning generic representations with tremendous EEG data in BCI, (2024). arXiv: 2405.18765."},{"key":"10.1016\/j.patcog.2026.113272_bib0008","unstructured":"J. Pradeepkumar, X. Piao, Z. Chen, J. Sun, Single-channel eeg tokenization through time-frequency modeling, (2025). arXiv: 2502.16060."},{"issue":"3","key":"10.1016\/j.patcog.2026.113272_bib0009","doi-asserted-by":"crossref","first-page":"235","DOI":"10.1109\/TASSP.1977.1162950","article-title":"Short term spectral analysis, synthesis, and modification by discrete Fourier transform","volume":"25","author":"Allen","year":"1977","journal-title":"IEEE Trans. Acoust."},{"issue":"5","key":"10.1016\/j.patcog.2026.113272_bib0010","doi-asserted-by":"crossref","first-page":"961","DOI":"10.1109\/18.57199","article-title":"The wavelet transform, time-frequency localization and signal analysis","volume":"36","author":"Daubechies","year":"1990","journal-title":"IEEE Trans. Inf. Theory"},{"issue":"11","key":"10.1016\/j.patcog.2026.113272_bib0011","doi-asserted-by":"crossref","first-page":"5391","DOI":"10.1002\/hbm.23730","article-title":"Deep learning with convolutional neural networks for EEG decoding and visualization","volume":"38","author":"Schirrmeister","year":"2017","journal-title":"Hum. Brain Mapp."},{"key":"10.1016\/j.patcog.2026.113272_bib0012","series-title":"Conference on Artificial Intelligence in Medicine in Europe","first-page":"47","article-title":"ChronoNet: a deep recurrent neural network for abnormal EEG identification","author":"Roy","year":"2019"},{"key":"10.1016\/j.patcog.2026.113272_bib0013","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2024.110726","article-title":"A novel hybrid decoding neural network for EEG signal representation","volume":"155","author":"Ji","year":"2024","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.patcog.2026.113272_bib0014","doi-asserted-by":"crossref","first-page":"9773","DOI":"10.1109\/TNNLS.2023.3236635","article-title":"LGGNet: learning from local-global-graph representations for brain\u2013computer interface","volume":"35","author":"Ding","year":"2023","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"10.1016\/j.patcog.2026.113272_bib0015","first-page":"14200","article-title":"Attention bottlenecks for multimodal fusion","volume":"34","author":"Nagrani","year":"2021","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.patcog.2026.113272_bib0016","series-title":"2023 11th International IEEE\/EMBS Conference on Neural Engineering (NER)","first-page":"1","article-title":"XANet: cross-attention between EEG of left and right brain for auditory attention decoding","author":"Pahuja","year":"2023"},{"key":"10.1016\/j.patcog.2026.113272_bib0017","series-title":"ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","first-page":"1926","article-title":"Multimodal multi-view spectral-spatial-temporal masked autoencoder for self-supervised emotion recognition","author":"Gao","year":"2024"},{"key":"10.1016\/j.patcog.2026.113272_bib0018","doi-asserted-by":"crossref","DOI":"10.1016\/j.neunet.2024.107066","article-title":"Multi-modal cross-domain self-supervised pre-training for fMRI and EEG fusion","volume":"184","author":"Wei","year":"2025","journal-title":"Neural Netw."},{"key":"10.1016\/j.patcog.2026.113272_bib0019","unstructured":"J. Wang, S. Zhao, Z. Luo, Y. Zhou, H. Jiang, S. Li, T. Li, G. Pan, CBraMod: a criss-cross brain foundation model for EEG decoding, (2024). arXiv: 2412.07236."},{"key":"10.1016\/j.patcog.2026.113272_bib0020","series-title":"2024 IEEE International Symposium on Biomedical Imaging (ISBI)","first-page":"1","article-title":"Neuro-GPT: towards a foundation model for EEG","author":"Cui","year":"2024"},{"key":"10.1016\/j.patcog.2026.113272_bib0021","unstructured":"X. Wei, K. Zhao, Y. Jiao, H. Xie, L. He, Y. Zhang, Pre-training graph contrastive masked autoencoders are strong distillers for EEG, (2024). arXiv: 2411.19230."},{"key":"10.1016\/j.patcog.2026.113272_bib0022","unstructured":"W.-B. Jiang, Y. Wang, B.-L. Lu, D. Li, NeuroLM: a universal multi-task foundation model for bridging the gap between language and EEG signals, (2024). arXiv: 2409.00101."},{"key":"10.1016\/j.patcog.2026.113272_bib0023","first-page":"3988","article-title":"Self-supervised contrastive pre-training for time series via time-frequency consistency","volume":"35","author":"Zhang","year":"2022","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.patcog.2026.113272_bib0024","unstructured":"C. Wang, V. Subramaniam, A.U. Yaari, G. Kreiman, B. Katz, I. Cases, A. Barbu, BrainBERT: self-supervised representation learning for intracranial recordings, (2023). arXiv: 2302.14367."},{"key":"10.1016\/j.patcog.2026.113272_bib0025","first-page":"26304","article-title":"Brant: foundation model for intracranial neural signal","volume":"36","author":"Zhang","year":"2024","journal-title":"Adv. Neural Inf. Process. Syst."},{"issue":"1","key":"10.1016\/j.patcog.2026.113272_bib0026","doi-asserted-by":"crossref","first-page":"108","DOI":"10.1002\/ana.20164","article-title":"High-frequency oscillations recorded in human medial temporal lobe during sleep","volume":"56","author":"Staba","year":"2004","journal-title":"Ann. Neurol."},{"key":"10.1016\/j.patcog.2026.113272_bib0027","unstructured":"S. Wang, B.Z. Li, M. Khabsa, H. Fang, H. Ma, Linformer: Self-attention with linear complexity, (2020). arXiv: 2006.04768."},{"key":"10.1016\/j.patcog.2026.113272_bib0028","doi-asserted-by":"crossref","DOI":"10.1016\/j.neucom.2023.127063","article-title":"Roformer: enhanced transformer with rotary position embedding","volume":"568","author":"Su","year":"2024","journal-title":"Neurocomputing"},{"key":"10.1016\/j.patcog.2026.113272_bib0029","series-title":"International Conference on Medical Image Computing and Computer-Assisted Intervention","first-page":"141","article-title":"DTCA: dual-branch transformer with cross-attention for EEG and eye movement data fusion","author":"Zhang","year":"2024"},{"key":"10.1016\/j.patcog.2026.113272_bib0030","unstructured":"Y. Chen, K. Ren, K. Song, Y. Wang, Y. Wang, D. Li, L. Qiu, EEGFormer: towards transferable and interpretable large-scale EEG foundation model, (2024). arXiv: 2401.10278."},{"issue":"12","key":"10.1016\/j.patcog.2026.113272_bib0031","doi-asserted-by":"crossref","DOI":"10.1088\/1742-5468\/ab3985","article-title":"On the information bottleneck theory of deep learning","volume":"2019","author":"Saxe","year":"2019","journal-title":"J. Stat. Mech: Theory Exp."},{"key":"10.1016\/j.patcog.2026.113272_bib0032","doi-asserted-by":"crossref","unstructured":"T. Lin, Focal loss for dense object detection, (2017). arXiv: 1708.02002.","DOI":"10.1109\/ICCV.2017.324"},{"key":"10.1016\/j.patcog.2026.113272_bib0033","first-page":"8792","article-title":"Generalized cross entropy loss for training deep neural networks with noisy labels","volume":"31","author":"Zhang","year":"2018","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.patcog.2026.113272_bib0034","series-title":"2014 IEEE Signal Processing in Medicine and Biology Symposium (SPMB)","first-page":"1","article-title":"The TUH EEG CORPUS: a big data resource for automated EEG interpretation","author":"Harati","year":"2014"},{"key":"10.1016\/j.patcog.2026.113272_bib0035","unstructured":"J. Guttag, CHB-MIT scalp EEG database (Version 1.0. 0), PhysioNet, 2010, https:\/\/doi.org\/10.13026\/C2K01R."},{"key":"10.1016\/j.patcog.2026.113272_bib0036","series-title":"Application of Machine Learning to Epileptic Seizure Onset Detection and Treatment","author":"Shoeb","year":"2009"},{"issue":"23","key":"10.1016\/j.patcog.2026.113272_bib0037","doi-asserted-by":"crossref","first-page":"e215","DOI":"10.1161\/01.CIR.101.23.e215","article-title":"PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals","volume":"101","author":"Goldberger","year":"2000","journal-title":"Circulation"},{"key":"10.1016\/j.patcog.2026.113272_bib0038","doi-asserted-by":"crossref","first-page":"180","DOI":"10.1016\/j.cmpb.2015.10.013","article-title":"ISRUC-Sleep: a comprehensive public dataset for sleep researchers","volume":"124","author":"Khalighi","year":"2016","journal-title":"Comput. Methods Programs Biomed."},{"issue":"1","key":"10.1016\/j.patcog.2026.113272_bib0039","doi-asserted-by":"crossref","first-page":"740","DOI":"10.1038\/s41597-023-02650-w","article-title":"A large finer-grained affective computing EEG dataset","volume":"10","author":"Chen","year":"2023","journal-title":"Sci. Data"},{"key":"10.1016\/j.patcog.2026.113272_bib0040","unstructured":"C. Yang, D. Xiao, M.B. Westover, J. Sun, Self-supervised EEG representation learning for automatic sleep staging, (2021). arXiv: 2110.15278."},{"key":"10.1016\/j.patcog.2026.113272_bib0041","doi-asserted-by":"crossref","DOI":"10.1016\/j.bspc.2021.103342","article-title":"Motor imagery EEG classification algorithm based on CNN-LSTM feature fusion network","volume":"72","author":"Li","year":"2022","journal-title":"Biomed. Signal Process. Control"},{"key":"10.1016\/j.patcog.2026.113272_bib0042","series-title":"2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)","first-page":"3599","article-title":"Transformer convolutional neural networks for automated artifact detection in scalp EEG","author":"Peh","year":"2022"},{"key":"10.1016\/j.patcog.2026.113272_bib0043","unstructured":"Y. Song, X. Jia, L. Yang, L. Xie, Transformer-based spatial-temporal feature learning for EEG decoding, (2021). arXiv: 2106.11170."},{"key":"10.1016\/j.patcog.2026.113272_bib0044","unstructured":"N.M. Foumani, G. Mackellar, S. Ghane, S. Irtza, N. Nguyen, M. Salehi, EEG2rep: enhancing self-supervised EEG representation through informative masked inputs, (2024). arXiv: 2402.17772."},{"key":"10.1016\/j.patcog.2026.113272_bib0045","first-page":"6309","article-title":"Neural discrete representation learning","volume":"30","author":"Van Den Oord","year":"2017","journal-title":"Adv. Neural Inf. Process. Syst."},{"issue":"6","key":"10.1016\/j.patcog.2026.113272_bib0046","doi-asserted-by":"crossref","first-page":"519","DOI":"10.1097\/00004691-199611000-00007","article-title":"Periodic lateralized epileptiform discharges\u2014a critical review","volume":"13","author":"Pohlmann-Eden","year":"1996","journal-title":"J. Clin. Neurophysiol."}],"container-title":["Pattern Recognition"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0031320326002372?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0031320326002372?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T22:28:20Z","timestamp":1774045700000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0031320326002372"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,10]]},"references-count":46,"alternative-id":["S0031320326002372"],"URL":"https:\/\/doi.org\/10.1016\/j.patcog.2026.113272","relation":{},"ISSN":["0031-3203"],"issn-type":[{"value":"0031-3203","type":"print"}],"subject":[],"published":{"date-parts":[[2026,10]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"CRIA: A cross-view interaction and instance-adapted pre-training framework for generalizable EEG representations","name":"articletitle","label":"Article Title"},{"value":"Pattern Recognition","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.patcog.2026.113272","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Published by Elsevier Ltd.","name":"copyright","label":"Copyright"}],"article-number":"113272"}}