{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,19]],"date-time":"2026-03-19T13:52:37Z","timestamp":1773928357301,"version":"3.50.1"},"reference-count":59,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62072219"],"award-info":[{"award-number":["62072219"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62227807"],"award-info":[{"award-number":["62227807"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100013804","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100013804","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["lzujbky-2022-ey13"],"award-info":[{"award-number":["lzujbky-2022-ey13"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["lzujbky-2024-it15"],"award-info":[{"award-number":["lzujbky-2024-it15"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004775","name":"Gansu Provincial Natural Science Foundation","doi-asserted-by":"publisher","award":["22JR5RA401"],"award-info":[{"award-number":["22JR5RA401"]}],"id":[{"id":"10.13039\/501100004775","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Neurocomputing"],"published-print":{"date-parts":[[2026,3]]},"DOI":"10.1016\/j.neucom.2025.132368","type":"journal-article","created":{"date-parts":[[2025,12,9]],"date-time":"2025-12-09T16:50:38Z","timestamp":1765299038000},"page":"132368","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["FDDGNet: An information bottleneck-inspired feature disentanglement network for cross-subject EEG-based emotion recognition"],"prefix":"10.1016","volume":"668","author":[{"given":"Yikun","family":"Yang","sequence":"first","affiliation":[]},{"given":"Lifei","family":"Duan","sequence":"additional","affiliation":[]},{"given":"Kechen","family":"Hou","sequence":"additional","affiliation":[]},{"given":"Zhongfeng","family":"Kang","sequence":"additional","affiliation":[]},{"given":"Xiaowei","family":"Zhang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3514-5413","authenticated-orcid":false,"given":"Bin","family":"Hu","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.neucom.2025.132368_bib0005","first-page":"1","article-title":"Automatic emotion recognition using deep neural network","author":"Sujatha","year":"2025","journal-title":"Multimed. Tools Appl."},{"issue":"1","key":"10.1016\/j.neucom.2025.132368_bib0010","first-page":"1","article-title":"Deep emotion recognition in textual conversations: a survey","volume":"58","author":"Pereira","year":"2025","journal-title":"Artif. Intell. Rev."},{"issue":"9","key":"10.1016\/j.neucom.2025.132368_bib0015","doi-asserted-by":"crossref","first-page":"4386","DOI":"10.1109\/TCYB.2020.2987575","article-title":"Emotion recognition from multimodal physiological signals using a regularized deep fusion of kernel machine","volume":"51","author":"Zhang","year":"2020","journal-title":"IEEE Trans. Cybern."},{"issue":"5","key":"10.1016\/j.neucom.2025.132368_bib0020","doi-asserted-by":"crossref","first-page":"3079","DOI":"10.1109\/TCYB.2023.3320107","article-title":"Emotion recognition from multimodal physiological signals via discriminative correlation fusion with a temporal alignment mechanism","volume":"54","author":"Hou","year":"2023","journal-title":"IEEE Trans. Cybern."},{"issue":"3","key":"10.1016\/j.neucom.2025.132368_bib0025","doi-asserted-by":"crossref","first-page":"374","DOI":"10.1109\/TAFFC.2017.2714671","article-title":"Emotions recognition using EEG signals: a survey","volume":"10","author":"Alarcao","year":"2017","journal-title":"IEEE Trans. Affect. Comput."},{"issue":"4","key":"10.1016\/j.neucom.2025.132368_bib0030","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3524499","article-title":"EEG based emotion recognition: a tutorial and review","volume":"55","author":"Li","year":"2022","journal-title":"ACM Comput. Surv."},{"issue":"11","key":"10.1016\/j.neucom.2025.132368_bib0035","doi-asserted-by":"crossref","first-page":"1617","DOI":"10.1111\/j.1469-8986.2012.01471.x","article-title":"How about taking a low-cost, small, and wireless EEG for a walk?","volume":"49","author":"Debener","year":"2012","journal-title":"Psychophysiology"},{"key":"10.1016\/j.neucom.2025.132368_bib0040","series-title":"Epileptic Seizures and the EEG: Measurement, Models, Detection and Prediction","author":"Varsavsky","year":"2011"},{"issue":"10","key":"10.1016\/j.neucom.2025.132368_bib0045","doi-asserted-by":"crossref","first-page":"1608","DOI":"10.3390\/math13101608","article-title":"A portable and affordable four-channel EEG system for emotion recognition with self-supervised feature learning","volume":"13","author":"Luo","year":"2025","journal-title":"Mathematics"},{"issue":"1","key":"10.1016\/j.neucom.2025.132368_bib0050","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1109\/MCI.2015.2501545","article-title":"Transfer learning in brain-computer interfaces","volume":"11","author":"Jayaram","year":"2016","journal-title":"IEEE Comput. Intell. Mag."},{"issue":"3","key":"10.1016\/j.neucom.2025.132368_bib0055","doi-asserted-by":"crossref","first-page":"2496","DOI":"10.1109\/TAFFC.2022.3164516","article-title":"Contrastive learning of subject-invariant EEG representations for cross-subject emotion recognition","volume":"14","author":"Shen","year":"2022","journal-title":"IEEE Trans. Affect. Comput."},{"issue":"10","key":"10.1016\/j.neucom.2025.132368_bib0060","doi-asserted-by":"crossref","first-page":"1345","DOI":"10.1109\/TKDE.2009.191","article-title":"A survey on transfer learning","volume":"22","author":"Pan","year":"2010","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"10.1016\/j.neucom.2025.132368_bib0065","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s40537-016-0043-6","article-title":"A survey of transfer learning","volume":"3","author":"Weiss","year":"2016","journal-title":"J. Big Data"},{"key":"10.1016\/j.neucom.2025.132368_bib0070","doi-asserted-by":"crossref","DOI":"10.1016\/j.neucom.2024.128354","article-title":"Toward cross-subject and cross-session generalization in EEG-based emotion recognition: systematic review, taxonomy, and methods","volume":"604","author":"Apicella","year":"2024","journal-title":"Neurocomputing"},{"issue":"6","key":"10.1016\/j.neucom.2025.132368_bib0075","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3712259","article-title":"Toward the construction of affective brain-computer interface: a systematic review","volume":"57","author":"Chen","year":"2025","journal-title":"ACM Comput. Surv."},{"key":"10.1016\/j.neucom.2025.132368_bib0080","doi-asserted-by":"crossref","DOI":"10.1016\/j.neunet.2024.106230","article-title":"Source-free unsupervised domain adaptation: a survey","author":"Fang","year":"2024","journal-title":"Neural Netw."},{"key":"10.1016\/j.neucom.2025.132368_bib0085","doi-asserted-by":"crossref","DOI":"10.1016\/j.inffus.2024.102862","article-title":"Multi-source multi-modal domain adaptation","volume":"117","author":"Zhao","year":"2025","journal-title":"Inf. Fusion"},{"key":"10.1016\/j.neucom.2025.132368_bib0090","doi-asserted-by":"crossref","DOI":"10.1016\/j.inffus.2023.102156","article-title":"Multi-view domain-adaptive representation learning for EEG-based emotion recognition","volume":"104","author":"Li","year":"2024","journal-title":"Inf. Fusion."},{"key":"10.1016\/j.neucom.2025.132368_bib0095","series-title":"Proceedings of the AAAI Conference on Artificial Intelligence","first-page":"863","article-title":"Plug-and-play domain adaptation for cross-subject EEG-based emotion recognition","volume":"vol. 35","author":"Zhao","year":"2021"},{"key":"10.1016\/j.neucom.2025.132368_bib0100","series-title":"Proceedings of the AAAI Conference on Artificial Intelligence","first-page":"628","article-title":"DMMR: cross-subject domain generalization for EEG-based emotion recognition via denoising mixed mutual reconstruction","volume":"vol. 38","author":"Wang","year":"2024"},{"key":"10.1016\/j.neucom.2025.132368_bib0105","doi-asserted-by":"crossref","first-page":"347","DOI":"10.1007\/s00371-015-1183-y","article-title":"Real-time EEG-based emotion monitoring using stable features","volume":"32","author":"Lan","year":"2016","journal-title":"Vis. Comput."},{"issue":"8","key":"10.1016\/j.neucom.2025.132368_bib0110","first-page":"8052","article-title":"Generalizing to unseen domains: a survey on domain generalization","volume":"35","author":"Wang","year":"2022","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"10.1016\/j.neucom.2025.132368_bib0115","doi-asserted-by":"crossref","first-page":"112","DOI":"10.3389\/fnhum.2012.00112","article-title":"Correlated components of ongoing EEG point to emotionally laden attention\u2013a possible marker of engagement?","volume":"6","author":"Dmochowski","year":"2012","journal-title":"Front. Hum. Neurosci."},{"issue":"1","key":"10.1016\/j.neucom.2025.132368_bib0120","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1109\/TAFFC.2018.2849758","article-title":"Inter-brain EEG feature extraction and analysis for continuous implicit emotion tagging during video watching","volume":"12","author":"Ding","year":"2018","journal-title":"IEEE Trans. Affect. Comput."},{"issue":"11","key":"10.1016\/j.neucom.2025.132368_bib0125","doi-asserted-by":"crossref","first-page":"15427","DOI":"10.1109\/TNNLS.2023.3286890","article-title":"Disentangling stochastic PDE dynamics for unsupervised video prediction","volume":"35","author":"Wu","year":"2023","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"issue":"5","key":"10.1016\/j.neucom.2025.132368_bib0130","doi-asserted-by":"crossref","first-page":"612","DOI":"10.1109\/JPROC.2021.3058954","article-title":"Toward causal representation learning","volume":"109","author":"Sch\u00f6lkopf","year":"2021","journal-title":"Proc. IEEE"},{"issue":"12","key":"10.1016\/j.neucom.2025.132368_bib0135","doi-asserted-by":"crossref","first-page":"11954","DOI":"10.1109\/JSEN.2022.3172133","article-title":"A feature-fused convolutional neural network for emotion recognition from multichannel EEG signals","volume":"22","author":"Yao","year":"2022","journal-title":"IEEE Sens. J."},{"key":"10.1016\/j.neucom.2025.132368_bib0140","doi-asserted-by":"crossref","first-page":"162","DOI":"10.3389\/fnins.2018.00162","article-title":"Exploring EEG features in cross-subject emotion recognition","volume":"12","author":"Li","year":"2018","journal-title":"Front. Neurosci."},{"key":"10.1016\/j.neucom.2025.132368_bib0145","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.neucom.2020.09.017","article-title":"A review on transfer learning in EEG signal analysis","volume":"421","author":"Wan","year":"2021","journal-title":"Neurocomputing"},{"key":"10.1016\/j.neucom.2025.132368_bib0150","series-title":"2019 IEEE International Conference on Bioinformatics and Biomedicine (Bibm)","first-page":"1156","article-title":"Individual similarity guided transfer modeling for EEG-based emotion recognition","author":"Zhang","year":"2019"},{"issue":"7","key":"10.1016\/j.neucom.2025.132368_bib0155","first-page":"3281","article-title":"Multisource transfer learning for cross-subject EEG emotion recognition","volume":"50","author":"Li","year":"2019","journal-title":"IEEE Trans. Cybern."},{"issue":"3","key":"10.1016\/j.neucom.2025.132368_bib0160","doi-asserted-by":"crossref","first-page":"1502","DOI":"10.1109\/TAFFC.2024.3357656","article-title":"CFDa-CSF: a multi-modal domain adaptation method for cross-subject emotion recognition","volume":"15","author":"Jim\u00e9nez-Guarneros","year":"2024","journal-title":"IEEE Trans. Affect. Comput."},{"key":"10.1016\/j.neucom.2025.132368_bib0165","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2021.107982","article-title":"Easy domain adaptation for cross-subject multi-view emotion recognition","volume":"239","author":"Chen","year":"2022","journal-title":"Knowl.-Based Syst."},{"key":"10.1016\/j.neucom.2025.132368_bib0170","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2024.112669","article-title":"Semi-supervised pairwise transfer learning based on multi-source domain adaptation: a case study on EEG-based emotion recognition","volume":"305","author":"Ren","year":"2024","journal-title":"Knowl.-Based Syst."},{"key":"10.1016\/j.neucom.2025.132368_bib0175","article-title":"EEGMatch: learning with incomplete labels for semisupervised EEG-based cross-subject emotion recognition","author":"Zhou","year":"2024","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"issue":"1","key":"10.1016\/j.neucom.2025.132368_bib0180","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1109\/TETCI.2023.3306253","article-title":"Towards domain generalization for ECG and EEG classification: algorithms and benchmarks","volume":"8","author":"Ballas","year":"2024","journal-title":"IEEE Trans. Emerg. Top. Comput. Intell."},{"issue":"4","key":"10.1016\/j.neucom.2025.132368_bib0185","doi-asserted-by":"crossref","first-page":"2484","DOI":"10.1109\/JBHI.2024.3431230","article-title":"EEG-DG: a multi-source domain generalization framework for motor imagery EEG classification","volume":"29","author":"Zhong","year":"2024","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"10.1016\/j.neucom.2025.132368_bib0190","series-title":"ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","first-page":"1236","article-title":"Domain-invariant representation learning from EEG with private encoders","author":"Bethge","year":"2022"},{"key":"10.1016\/j.neucom.2025.132368_bib0195","doi-asserted-by":"crossref","first-page":"3285","DOI":"10.1109\/TNSRE.2023.3300961","article-title":"Domain-generalized EEG classification with category-oriented feature decorrelation and cross-view consistency learning","volume":"31","author":"Liang","year":"2023","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"issue":"5","key":"10.1016\/j.neucom.2025.132368_bib0200","doi-asserted-by":"crossref","DOI":"10.1088\/1741-2552\/abb7a7","article-title":"Thinker invariance: enabling deep neural networks for BCI across more people","volume":"17","author":"Kostas","year":"2020","journal-title":"J. Neural Eng."},{"issue":"10","key":"10.1016\/j.neucom.2025.132368_bib0205","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3654664","article-title":"Domain adaptation and generalization of functional medical data: a systematic survey of brain data","volume":"56","author":"Sarafraz","year":"2024","journal-title":"ACM Comput. Surv."},{"key":"10.1016\/j.neucom.2025.132368_bib0210","article-title":"Domain separation networks","volume":"29","author":"Bousmalis","year":"2016","journal-title":"Adv. Neural Inf. Process. Syst."},{"issue":"2","key":"10.1016\/j.neucom.2025.132368_bib0215","doi-asserted-by":"crossref","first-page":"765","DOI":"10.1109\/JBHI.2023.3337072","article-title":"Noise-factorized disentangled representation learning for generalizable motor imagery EEG classification","volume":"28","author":"Han","year":"2023","journal-title":"IEEE J. Biomed. Health Inform."},{"issue":"1","key":"10.1016\/j.neucom.2025.132368_bib0220","doi-asserted-by":"crossref","first-page":"319","DOI":"10.1109\/TAFFC.2024.3433613","article-title":"Grop: graph orthogonal purification network for EEG emotion recognition","volume":"16","author":"Wu","year":"2024","journal-title":"IEEE Trans. Affect. Comput."},{"issue":"2","key":"10.1016\/j.neucom.2025.132368_bib0225","doi-asserted-by":"crossref","first-page":"739","DOI":"10.1109\/TNNLS.2021.3100583","article-title":"Mutual information-driven subject-invariant and class-relevant deep representation learning in BCI","volume":"34","author":"Jeon","year":"2023","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"10.1016\/j.neucom.2025.132368_bib0230","doi-asserted-by":"crossref","first-page":"3508","DOI":"10.1109\/TIP.2024.3404241","article-title":"Insure: an information theory inspired disentanglement and purification model for domain generalization","volume":"33","author":"Yu","year":"2024","journal-title":"IEEE Trans. Image Process."},{"issue":"2","key":"10.1016\/j.neucom.2025.132368_bib0235","first-page":"230","article-title":"Deep physiological affect network for the recognition of human emotions","volume":"11","author":"Kim","year":"2020","journal-title":"IEEE Trans. Affect. Comput."},{"key":"10.1016\/j.neucom.2025.132368_bib0240","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"6631","article-title":"Decoupled multimodal distilling for emotion recognition","author":"Li","year":"2023"},{"key":"10.1016\/j.neucom.2025.132368_bib0245","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"1522","article-title":"Farewell to mutual information: variational distillation for cross-modal person re-identification","author":"Tian","year":"2021"},{"key":"10.1016\/j.neucom.2025.132368_bib0250","author":"Federici"},{"key":"10.1016\/j.neucom.2025.132368_bib0255","article-title":"Sequence to sequence learning with neural networks","volume":"27","author":"Sutskever","year":"2014","journal-title":"Adv. Neural Inf. Process. Syst."},{"issue":"2","key":"10.1016\/j.neucom.2025.132368_bib0260","doi-asserted-by":"crossref","first-page":"479","DOI":"10.1109\/TAFFC.2018.2884461","article-title":"AMIGOS: a dataset for affect, personality and mood research on individuals and groups","volume":"12","author":"Miranda-Correa","year":"2018","journal-title":"IEEE Trans. Affect. Comput."},{"issue":"1","key":"10.1016\/j.neucom.2025.132368_bib0265","doi-asserted-by":"crossref","first-page":"98","DOI":"10.1109\/JBHI.2017.2688239","article-title":"DREAMER: a database for emotion recognition through EEG and ECG signals from wireless low-cost off-the-shelf devices","volume":"22","author":"Katsigiannis","year":"2017","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"10.1016\/j.neucom.2025.132368_bib0270","series-title":"2019 International Joint Conference on Neural Networks (IJCNN)","first-page":"1","article-title":"Depersonalized cross-subject vigilance estimation with adversarial domain generalization","author":"Ma","year":"2019"},{"key":"10.1016\/j.neucom.2025.132368_bib0275","doi-asserted-by":"crossref","first-page":"1900","DOI":"10.1109\/TNSRE.2023.3257319","article-title":"IFNet: an interactive frequency convolutional neural network for enhancing motor imagery decoding from EEG","volume":"31","author":"Wang","year":"2023","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"issue":"4","key":"10.1016\/j.neucom.2025.132368_bib0280","doi-asserted-by":"crossref","first-page":"2740","DOI":"10.1109\/TAFFC.2022.3179717","article-title":"EEG-based subject-independent emotion recognition using gated recurrent unit and minimum class confusion","volume":"14","author":"Cui","year":"2023","journal-title":"IEEE Trans. Affect. Comput."},{"key":"10.1016\/j.neucom.2025.132368_bib0285","first-page":"1","article-title":"Exploiting the intrinsic neighborhood semantic structure for domain adaptation in EEG-based emotion recognition","author":"Yang","year":"2025","journal-title":"IEEE Trans. Affect. Comput."},{"issue":"11","key":"10.1016\/j.neucom.2025.132368_bib0290","article-title":"Visualizing data using t-SNE","volume":"9","author":"Van der Maaten","year":"2008","journal-title":"J. Mach. Learn. Res."},{"issue":"Jan","key":"10.1016\/j.neucom.2025.132368_bib0295","first-page":"1","article-title":"Statistical comparisons of classifiers over multiple data sets","volume":"7","author":"Dem\u0161ar","year":"2006","journal-title":"J. Mach. Learn. Res."}],"container-title":["Neurocomputing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0925231225030401?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0925231225030401?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,3,19]],"date-time":"2026-03-19T10:32:21Z","timestamp":1773916341000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0925231225030401"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3]]},"references-count":59,"alternative-id":["S0925231225030401"],"URL":"https:\/\/doi.org\/10.1016\/j.neucom.2025.132368","relation":{},"ISSN":["0925-2312"],"issn-type":[{"value":"0925-2312","type":"print"}],"subject":[],"published":{"date-parts":[[2026,3]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"FDDGNet: An information bottleneck-inspired feature disentanglement network for cross-subject EEG-based emotion recognition","name":"articletitle","label":"Article Title"},{"value":"Neurocomputing","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.neucom.2025.132368","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"132368"}}