{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,9]],"date-time":"2026-09-09T02:49:30Z","timestamp":1788922170079,"version":"build-2803163510"},"reference-count":47,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["2024M750518"],"award-info":[{"award-number":["2024M750518"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]},{"award":["2024M750518"],"award-info":[{"award-number":["2024M750518"]}],"id":[{"id":"https:\/\/ror.org\/0426zh255","id-type":"ROR","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["12304513"],"award-info":[{"award-number":["12304513"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"award":["12304513"],"award-info":[{"award-number":["12304513"]}],"id":[{"id":"https:\/\/ror.org\/01h0zpd94","id-type":"ROR","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005315","name":"Natural Science Foundation of Ningbo","doi-asserted-by":"publisher","award":["2024J235"],"award-info":[{"award-number":["2024J235"]}],"id":[{"id":"10.13039\/501100005315","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005315","name":"Natural Science Foundation of Ningbo","doi-asserted-by":"publisher","award":["20251JCGY010476"],"award-info":[{"award-number":["20251JCGY010476"]}],"id":[{"id":"10.13039\/501100005315","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Biosensors"],"abstract":"<jats:p>Differentiating Alzheimer\u2019s disease (AD) from frontotemporal dementia (FTD) using resting-state electroencephalography (EEG) remains clinically challenging because of their overlapping electrophysiological characteristics. Although EEG suits large-scale dementia screening, current method often overestimates performance because of epoch-level data leakage and multiclass feature competition in unified models. We propose a task-decoupled, two-stage hierarchical deep learning framework utilizing multiband EEG microstate dynamics. Continuous microstate sequences, modeled via Hungarian matching to preserve fine-grained temporal information, are processed using a normalizer-free 1D convolutional neural network (1D-CNN-NFNet) integrated with multi-head attention. By decoupling the workflow, Stage 1 performs generalized dementia screening using alpha and delta microstates, achieving an area under the curve (AUC) of 0.851. Stage 2 disentangles AD from FTD using delta and theta dynamics, yielding an AD-locking specificity of 86.1%. Evaluated under a strict subject-level leave-one-subject-out (LOSO) cross-validation protocol, the two-stage framework achieved 63.9% balanced accuracy, outperforming the single-stage baseline (55.4%) with a negligible inference latency of 0.733 ms. Furthermore, attention-based interpretability analysis links frequency-specific microstate alterations to underlying cortical disconnection syndromes. These results demonstrate that the framework provides a reproducible and interpretable auxiliary reference for dementia screening and subtyping in clinical neurology.<\/jats:p>","DOI":"10.3390\/bios16050258","type":"journal-article","created":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T09:33:17Z","timestamp":1777627997000},"page":"258","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["A Two-Stage EEG Microstate Fusion Framework for Dementia Screening and Alzheimer\u2019s Disease\/Frontotemporal Dementia Differentiation"],"prefix":"10.3390","volume":"16","author":[{"given":"Lei","family":"Jiang","sequence":"first","affiliation":[{"name":"Fudan Institute on Ageing, Fudan University, Shanghai 200433, China"},{"name":"Laboratory of Intelligent Home Appliances, College of Science and Technology, Ningbo University, Ningbo 315300, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yingna","family":"Chen","sequence":"additional","affiliation":[{"name":"Laboratory of Intelligent Home Appliances, College of Science and Technology, Ningbo University, Ningbo 315300, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yan","family":"He","sequence":"additional","affiliation":[{"name":"Laboratory of Intelligent Home Appliances, College of Science and Technology, Ningbo University, Ningbo 315300, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiarui","family":"Liang","sequence":"additional","affiliation":[{"name":"Laboratory of Intelligent Home Appliances, College of Science and Technology, Ningbo University, Ningbo 315300, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xuan","family":"Zhao","sequence":"additional","affiliation":[{"name":"Laboratory of Intelligent Home Appliances, College of Science and Technology, Ningbo University, Ningbo 315300, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiuyan","family":"Guo","sequence":"additional","affiliation":[{"name":"Fudan Institute on Ageing, Fudan University, Shanghai 200433, China"},{"name":"MOE Laboratory for National Development and Intelligent Governance, Fudan University, Shanghai 200433, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,5,1]]},"reference":[{"key":"ref_1","first-page":"495","article-title":"Dementia and its subtypes: A statistical","volume":"Volume 1","author":"Ranjan","year":"2025","journal-title":"Soft Computing: Theories and Applications: Proceedings of SoCTA 2024"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Liu, S., Wu, G., Ma, X., Xu, K., Lan, X., Wang, L., Li, H., Gu, D., Wang, M., and Liu, J. 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