{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,14]],"date-time":"2026-05-14T18:16:01Z","timestamp":1778782561622,"version":"3.51.4"},"reference-count":62,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/100012548","name":"Heilongjiang Postdoctoral Science Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100012548","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100010009","name":"Heilongjiang Provincial Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["200323004"],"award-info":[{"award-number":["200323004"]}],"id":[{"id":"10.13039\/501100010009","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Expert Systems with Applications"],"published-print":{"date-parts":[[2026,5]]},"DOI":"10.1016\/j.eswa.2026.131526","type":"journal-article","created":{"date-parts":[[2026,2,6]],"date-time":"2026-02-06T00:31:51Z","timestamp":1770337911000},"page":"131526","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["NeuroVision: EEG-to-image reconstruction via progressive neural encoding and cross-modal distillation"],"prefix":"10.1016","volume":"312","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-7474-2134","authenticated-orcid":false,"given":"Tianwei","family":"Qu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-9750-1603","authenticated-orcid":false,"given":"Zexue","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7603-8748","authenticated-orcid":false,"given":"Qixian","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"key":"10.1016\/j.eswa.2026.131526_bib0001","doi-asserted-by":"crossref","DOI":"10.1016\/j.bspc.2023.105497","article-title":"Visual image reconstruction based on eeg signals using a generative adversarial and deep fuzzy neural network","volume":"87","author":"Ahmadieh","year":"2024","journal-title":"Biomedical Signal Processing and Control"},{"key":"10.1016\/j.eswa.2026.131526_bib0002","unstructured":"Bai, Y., Wang, X., Cao, Y., Ge, Y., Yuan, C., & Shan, Y. (2023). DreamDiffusion: Generating high-quality images from brain eeg signals. arXiv: 2306.16934."},{"key":"10.1016\/j.eswa.2026.131526_bib0003","unstructured":"Benchetrit, Y., Banville, H., & King, J.-R. (2023). Brain decoding: Toward real-time reconstruction of visual perception. arXiv: 2308.02510."},{"key":"10.1016\/j.eswa.2026.131526_bib0004","first-page":"127","article-title":"Brain decoding: Toward real-time reconstruction of visual perception","volume":"6","author":"Benchetrit","year":"2024","journal-title":"Nature Machine Intelligence"},{"key":"10.1016\/j.eswa.2026.131526_bib0005","unstructured":"Chen, C.-S., & Wei, C.-S. (2024a). Mind\u2019s eye: Image recognition by eeg via multimodal similarity-keeping contrastive learning. arXiv: 2406.16910."},{"issue":"1","key":"10.1016\/j.eswa.2026.131526_bib0006","first-page":"183","article-title":"Mind\u2019s eye: Image recognition by eeg via multimodal similarity-keeping contrastive learning","volume":"32","author":"Chen","year":"2024","journal-title":"IEEE Transactions on Neural Systems and Rehabilitation Engineering"},{"key":"10.1016\/j.eswa.2026.131526_bib0007","unstructured":"Chen, H., He, L., Liu, Y., & Yang, L. (2024). Visual neural decoding via improved visual-EEG semantic consistency. arXiv: 2408.06788."},{"key":"10.1016\/j.eswa.2026.131526_bib0008","series-title":"International conference on machine learning","first-page":"1597","article-title":"A simple framework for contrastive learning of visual representations","author":"Chen","year":"2020"},{"issue":"12","key":"10.1016\/j.eswa.2026.131526_bib0009","first-page":"14715","article-title":"Foundation models for biomedical image computing: A survey","volume":"45","author":"Chen","year":"2023","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"10.1016\/j.eswa.2026.131526_bib0010","series-title":"International conference on learning representations","first-page":"1","article-title":"An image is worth 16x16 words: Transformers for image recognition at scale","author":"Dosovitskiy","year":"2020"},{"issue":"9","key":"10.1016\/j.eswa.2026.131526_bib0011","doi-asserted-by":"crossref","first-page":"10760","DOI":"10.1109\/TPAMI.2023.3263181","article-title":"Decoding visual neural representations by multimodal learning of brain-visual-linguistic features","volume":"45","author":"Du","year":"2023","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"10.1016\/j.eswa.2026.131526_bib0012","doi-asserted-by":"crossref","DOI":"10.1016\/j.compbiomed.2024.108701","article-title":"Decoding visual brain representations from electroencephalography through knowledge distillation and latent diffusion models","volume":"178","author":"Ferrante","year":"2024","journal-title":"Computers in Biology and Medicine"},{"issue":"1","key":"10.1016\/j.eswa.2026.131526_bib0013","doi-asserted-by":"crossref","DOI":"10.1038\/s41598-024-66228-1","article-title":"Image classification and reconstruction from low-density eeg","volume":"14","author":"Guenther","year":"2024","journal-title":"Scientific Reports"},{"issue":"1","key":"10.1016\/j.eswa.2026.131526_bib0014","first-page":"3723","article-title":"Deep learning-based reconstruction of natural movies from brain activity","volume":"14","author":"Horikawa","year":"2023","journal-title":"Nature Communications"},{"key":"10.1016\/j.eswa.2026.131526_bib0015","series-title":"The thirty-ninth annual conference on neural information processing systems","article-title":"Need: Cross-subject and cross-task generalization for video and image reconstruction from eeg signals","author":"Huang","year":"2025"},{"key":"10.1016\/j.eswa.2026.131526_bib0016","doi-asserted-by":"crossref","DOI":"10.1016\/j.inffus.2025.103022","article-title":"CCSUMSP: A cross-subject chinese speech decoding framework with unified topology and multi-modal semantic pre-training","volume":"119","author":"Huang","year":"2025","journal-title":"Information Fusion"},{"key":"10.1016\/j.eswa.2026.131526_bib0017","doi-asserted-by":"crossref","unstructured":"Huang, S., Wang, Y., & Luo, H. (2025c). A dual-branch generative adversarial network with self-supervised enhancement for robust auditory attention decoding. Engineering Applications of Artificial Intelligence, (p. 111122).","DOI":"10.1016\/j.engappai.2025.111122"},{"key":"10.1016\/j.eswa.2026.131526_bib0018","series-title":"ICASSP 2025-2025 IEEE international conference on acoustics, speech and signal processing","first-page":"1","article-title":"SSAAD: A multi-scale temporal-frequency graph network for binary auditory attention detection with self-supervised learning","author":"Huang","year":"2025"},{"key":"10.1016\/j.eswa.2026.131526_bib0019","series-title":"Proceedings of the 33rd ACM international conference on multimedia the 33rd ACM international conference on multimedia","first-page":"3350","article-title":"MinDev: Multi-modal integrated diffusion framework for video reconstruction from EEG signals","author":"Huang","year":"2025"},{"key":"10.1016\/j.eswa.2026.131526_bib0020","series-title":"Proceedings of the 25th ACM international conference on multimedia","first-page":"1809","article-title":"Brain2Image: Converting brain signals into images","author":"Kavasidis","year":"2017"},{"key":"10.1016\/j.eswa.2026.131526_bib0021","series-title":"IEEE conference on computer vision and pattern recognition","first-page":"7482","article-title":"Multi-task learning using uncertainty to weigh losses for scene geometry and semantics","author":"Kendall","year":"2018"},{"key":"10.1016\/j.eswa.2026.131526_bib0022","doi-asserted-by":"crossref","DOI":"10.1016\/j.bspc.2022.104221","article-title":"Developing an efficient functional connectivity-based geometric deep network for automatic eeg-based visual decoding","volume":"80","author":"Khaleghi","year":"2023","journal-title":"Biomedical Signal Processing and Control"},{"issue":"8","key":"10.1016\/j.eswa.2026.131526_bib0023","doi-asserted-by":"crossref","first-page":"5979","DOI":"10.1007\/s00521-021-06774-1","article-title":"NeuroVision: Perceived image regeneration using cprogan","volume":"34","author":"Khare","year":"2022","journal-title":"Neural Computing and Applications"},{"issue":"1","key":"10.1016\/j.eswa.2026.131526_bib0024","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1109\/T-AFFC.2011.15","article-title":"DEAP: A database for emotion analysis using physiological signals","volume":"3","author":"Koelstra","year":"2011","journal-title":"IEEE Transactions on Affective Computing"},{"key":"10.1016\/j.eswa.2026.131526_bib0025","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1016\/j.patrec.2021.11.019","article-title":"Automated visual stimuli evoked multi-channel EEG signal classification using eegcapsnet","volume":"153","author":"Kumari","year":"2022","journal-title":"Pattern Recognition Letters"},{"key":"10.1016\/j.eswa.2026.131526_bib0026","unstructured":"Lan, Y.-T., Ren, K., Wang, Y., Zheng, W.-L., Li, D., Lu, B.-L., & Qiu, L. (2023). Seeing through the brain: Image reconstruction of visual perception from human brain signals. arXiv: 2308.02510."},{"issue":"1","key":"10.1016\/j.eswa.2026.131526_bib0027","first-page":"1","article-title":"EEG-based brain-computer interfaces: A thorough literature survey","volume":"52","author":"Lee","year":"2019","journal-title":"ACM Computing Surveys"},{"key":"10.1016\/j.eswa.2026.131526_bib0028","series-title":"RealMind: Advancing visual decoding and language interaction via EEG signals","author":"Li","year":"2024"},{"key":"10.1016\/j.eswa.2026.131526_bib0029","doi-asserted-by":"crossref","unstructured":"Li, D., Wei, C., Li, S., Zou, J., Qin, H., & Liu, Q. (2024b). Visual decoding and reconstruction via EEG embeddings with guided diffusion. arXiv: 2403.07721.","DOI":"10.52202\/079017-3266"},{"issue":"1","key":"10.1016\/j.eswa.2026.131526_bib0030","doi-asserted-by":"crossref","first-page":"1123","DOI":"10.1038\/s41467-022-28793-9","article-title":"Visual decoding and reconstruction via EEG embeddings with guided diffusion","volume":"15","author":"Li","year":"2024","journal-title":"Nature Communications"},{"issue":"4","key":"10.1016\/j.eswa.2026.131526_bib0031","first-page":"219","article-title":"EEG signal classification based on deep neural network","volume":"40","author":"Li","year":"2019","journal-title":"IRBM"},{"issue":"9","key":"10.1016\/j.eswa.2026.131526_bib0032","first-page":"10641","article-title":"Brain encoding and decoding in human vision: A survey","volume":"45","author":"Liu","year":"2023","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"issue":"10","key":"10.1016\/j.eswa.2026.131526_bib0033","first-page":"6501","article-title":"Hierarchical vision transformer using low-level feature distillation","volume":"44","author":"Liu","year":"2022","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"10.1016\/j.eswa.2026.131526_bib0034","unstructured":"Lopez, E., Sigillo, L., Colonnese, F., Panella, M., & Comminiello, D. (2024). Guess what i think: Streamlined EEG-to-image generation with latent diffusion models. arXiv: 2410.02780."},{"issue":"12","key":"10.1016\/j.eswa.2026.131526_bib0035","first-page":"9181","article-title":"NeuroGAN: Image reconstruction from eeg signals via an attention-based gan","volume":"35","author":"Mishra","year":"2023","journal-title":"Neural Computing and Applications"},{"key":"10.1016\/j.eswa.2026.131526_bib0036","series-title":"International conference on machine learning","first-page":"8748","article-title":"Learning transferable visual models from natural language supervision","author":"Radford","year":"2021"},{"key":"10.1016\/j.eswa.2026.131526_bib0037","unstructured":"Ruder, S. (2017). An Overview of multi-task learning in deep neural networks. arXiv: 1706.05098."},{"key":"10.1016\/j.eswa.2026.131526_bib0038","series-title":"International conference on learning representations","first-page":"1","article-title":"How much can clip benefit vision-and-language tasks","author":"Shen","year":"2021"},{"key":"10.1016\/j.eswa.2026.131526_bib0039","series-title":"Icassp 2023-2023 IEEE international conference on acoustics, speech and signal processing","first-page":"1","article-title":"EEG2Image: Image reconstruction from EEG brain signals","author":"Singh","year":"2023"},{"issue":"1","key":"10.1016\/j.eswa.2026.131526_bib0040","article-title":"EEG2Image: Image reconstruction from EEG brain signals","volume":"13","author":"Singh","year":"2023","journal-title":"Scientific Reports"},{"key":"10.1016\/j.eswa.2026.131526_bib0041","unstructured":"Song, Y., Liu, B., Li, X., Shi, N., Wang, Y., & Gao, X. (2023). Decoding natural images from EEG for object recognition. arXiv: 2308.13234."},{"key":"10.1016\/j.eswa.2026.131526_bib0042","article-title":"Decoding natural images from EEG for object recognition","volume":"285","author":"Song","year":"2024","journal-title":"NeuroImage"},{"key":"10.1016\/j.eswa.2026.131526_bib0043","series-title":"IEEE conference on computer vision and pattern recognition","first-page":"6809","article-title":"Deep learning human mind for automated visual classification","author":"Spampinato","year":"2017"},{"issue":"12","key":"10.1016\/j.eswa.2026.131526_bib0044","first-page":"2987","article-title":"A survey on visual transformer","volume":"42","author":"Sun","year":"2020","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"10.1016\/j.eswa.2026.131526_bib0045","series-title":"Cross-subject EEG feedback for implicit image generation","author":"Torre-Ortiz","year":"2024"},{"key":"10.1016\/j.eswa.2026.131526_bib0046","first-page":"5998","article-title":"Attention is all you need","volume":"30","author":"Vaswani","year":"2017","journal-title":"Advances in Neural Information Processing Systems"},{"key":"10.1016\/j.eswa.2026.131526_bib0047","first-page":"159","article-title":"Visual decoding from EEG to recover original stimuli using diffusion models","volume":"520","author":"Wang","year":"2023","journal-title":"Neurocomputing"},{"key":"10.1016\/j.eswa.2026.131526_bib0048","series-title":"International conference on computer vision","first-page":"16227","article-title":"CrossFormer: A versatile vision transformer based on cross-scale attention","author":"Wang","year":"2021"},{"key":"10.1016\/j.eswa.2026.131526_bib0049","doi-asserted-by":"crossref","first-page":"386","DOI":"10.1038\/s41597-023-02287-9","article-title":"EEG-based BCI dataset of semantic concepts for imagination and perception tasks","volume":"10","author":"Wilson","year":"2023","journal-title":"Scientific Data"},{"key":"10.1016\/j.eswa.2026.131526_bib0050","first-page":"17632","article-title":"Visual attention methods in deep learning: An in-depth survey","volume":"11","author":"Wu","year":"2023","journal-title":"IEEE Access"},{"key":"10.1016\/j.eswa.2026.131526_bib0051","series-title":"IEEE conference on computer vision and pattern recognition","first-page":"12716","article-title":"Contrastive learning visual representations with data augmentation","author":"Wu","year":"2021"},{"issue":"1","key":"10.1016\/j.eswa.2026.131526_bib0052","doi-asserted-by":"crossref","DOI":"10.1038\/s41598-024-77923-4","article-title":"A hybrid local-global neural network for visual classification using raw EEG signals","volume":"14","author":"Xue","year":"2024","journal-title":"Scientific Reports"},{"key":"10.1016\/j.eswa.2026.131526_bib0053","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2023.109915","article-title":"Self-supervised cross-modal visual retrieval from brain activities","volume":"145","author":"Ye","year":"2024","journal-title":"Pattern Recognition"},{"key":"10.1016\/j.eswa.2026.131526_bib0054","doi-asserted-by":"crossref","DOI":"10.1016\/j.bspc.2022.104440","article-title":"DCAE: A dual conditional autoencoder framework for the reconstruction from EEG into image","volume":"81","author":"Zeng","year":"2023","journal-title":"Biomedical Signal Processing and Control"},{"key":"10.1016\/j.eswa.2026.131526_bib0055","doi-asserted-by":"crossref","DOI":"10.1016\/j.bspc.2023.105125","article-title":"DM-RE2I: A framework based on diffusion model for the reconstruction from EEG to image","volume":"86","author":"Zeng","year":"2023","journal-title":"Biomedical Signal Processing and Control"},{"key":"10.1016\/j.eswa.2026.131526_bib0056","series-title":"Neural information processing systems","first-page":"20996","article-title":"Contrastive learning of global and local features for medical image segmentation with limited annotations","author":"Zhang","year":"2021"},{"issue":"11","key":"10.1016\/j.eswa.2026.131526_bib0057","first-page":"7845","article-title":"Neuro-symbolic visual dialog","volume":"44","author":"Zhang","year":"2022","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"10.1016\/j.eswa.2026.131526_bib0058","series-title":"IEEE international conference on multimedia and expo","first-page":"1","article-title":"Exploring versatile generative architecture for network-based EEG decoding","author":"Zhao","year":"2020"},{"issue":"9","key":"10.1016\/j.eswa.2026.131526_bib0059","first-page":"2337","article-title":"Swin transformer v2: Scaling up capacity and resolution","volume":"130","author":"Zheng","year":"2022","journal-title":"International Journal of Computer Vision"},{"key":"10.1016\/j.eswa.2026.131526_bib0060","unstructured":"Zhu, S., Ye, Z., Ai, Q., & Liu, Y. (2024a). EEG-ImageNet: An electroencephalogram dataset and benchmarks with image visual stimuli of multi-granularity labels. arXiv: 2406.07151."},{"key":"10.1016\/j.eswa.2026.131526_bib0061","doi-asserted-by":"crossref","DOI":"10.1016\/j.ins.2024.121141","article-title":"OPT-CO: Optimizing pre-trained transformer models for efficient covid-19 classification with stochastic configuration networks","volume":"680","author":"Zhu","year":"2024","journal-title":"Information Sciences"},{"issue":"12","key":"10.1016\/j.eswa.2026.131526_bib0062","first-page":"6719","article-title":"Brain activity decoding with deep learning: A survey","volume":"33","author":"Zhuang","year":"2022","journal-title":"IEEE Transactions on Neural Networks and Learning Systems"}],"container-title":["Expert Systems with Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0957417426004392?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0957417426004392?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,5,14]],"date-time":"2026-05-14T17:46:55Z","timestamp":1778780815000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0957417426004392"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,5]]},"references-count":62,"alternative-id":["S0957417426004392"],"URL":"https:\/\/doi.org\/10.1016\/j.eswa.2026.131526","relation":{},"ISSN":["0957-4174"],"issn-type":[{"value":"0957-4174","type":"print"}],"subject":[],"published":{"date-parts":[[2026,5]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"NeuroVision: EEG-to-image reconstruction via progressive neural encoding and cross-modal distillation","name":"articletitle","label":"Article Title"},{"value":"Expert Systems with Applications","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.eswa.2026.131526","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"131526"}}