{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,16]],"date-time":"2026-10-16T06:52:25Z","timestamp":1792133545765,"version":"4.4.0"},"reference-count":71,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,9,12]],"date-time":"2025-09-12T00:00:00Z","timestamp":1757635200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Aging Neurosci."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Mild cognitive impairment (MCI) exhibits abnormal resting-state EEG oscillations in delta (1\u20134\u202fHz), theta (4\u20137\u202fHz), and alpha (8\u201313\u202fHz) bands, though findings remain inconsistent. Moreover, dynamic functional connectivity (FC) alterations in these bands are poorly understood. To address this, we aimed to characterize resting-state EEG oscillations and dynamic FC in these frequency bands in MCI.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Method<\/jats:title>\n                    <jats:p>We recruited 21 MCI and 20 age\u2212\/education-matched normal controls (NC). Resting-state EEG was recorded for 5\u202fmin (eyes-open). We utilized power spectral density to investigate abnormalities in neural oscillations, and employed the directed transfer function (DTF) to explore dynamic functional connectivity (FC) alterations within the delta, alpha, and theta frequency bands 4among two groups.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Compared to NC, for neural oscillation, MCI showed significantly increased delta oscillation (prefrontal, parietal, temporal, and central regions) mainly located in the frontal and parietal lobes, significantly decreased alpha oscillation of the entire brain region mainly located in the frontal lobe, and both significantly increased and decreased theta oscillation (prefrontal, parietal, and occipital lobes) with fewer electrodes. For dynamic brain FC, in the delta band, the MCI exhibited significantly enhanced bidirectional FC between the prefrontal and parietal lobes, as well as two bottom-up FC from the occipital lobe to the central and parietal regions; In the theta band, the MCI showed significant enhancement of two FC from the temporal lobe to the frontal lobe, two FC from the occipital lobe to the parietal lobe, and one FC from the parietal lobe to the frontal lobe; In the alpha band, the MCI had one significantly enhanced bottom-up FC from the occipital lobe to the prefrontal lobe.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>During the eyes-open resting-state, differences of two groups in neural oscillations were primarily observed in the alpha and delta bands. The MCI exhibited significantly decreased alpha oscillations in the frontal lobe and increased delta oscillations in the frontal and parietal lobes. However, dynamic FC differences were most prominent in the delta and theta bands, including significantly increased interconnectivity of the prefrontal parietal network and significantly increased bottom-up FC. These findings emphasize the necessity of comprehensive analysis of local activity and large-scale network dynamics in MCI.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fnagi.2025.1640966","type":"journal-article","created":{"date-parts":[[2025,9,12]],"date-time":"2025-09-12T05:44:59Z","timestamp":1757655899000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":12,"title":["Abnormal resting-state EEG neural oscillations and functional connectivity in mild cognitive impairment"],"prefix":"10.3389","volume":"17","author":[{"given":"Yi","family":"Jiang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhiwei","family":"Guo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rubing","family":"Jiao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haoru","family":"He","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ning","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiayuan","family":"He","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2025,9,12]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"1553","DOI":"10.3390\/e23111553","article-title":"A comparative study of functional connectivity measures for brain network analysis in the context of AD detection with EEG","volume":"23","author":"Abazid","year":"2021","journal-title":"Entropy"},{"key":"ref2","doi-asserted-by":"publisher","first-page":"6981268","DOI":"10.1155\/2019\/6981268","article-title":"Early electrophysiological disintegration of hippocampal neural networks in a novel locus Coeruleus tau-seeding mouse model of Alzheimer's disease","volume":"2019","author":"Ahnaou","year":"2019","journal-title":"Neural Plast."},{"key":"ref3","doi-asserted-by":"crossref","DOI":"10.1109\/ICCME.2009.4906629","article-title":"A model of Alzheimer's disease and mild cognitive impairment based on EEG coherence","author":"Akrofi","year":"2009"},{"key":"ref4","doi-asserted-by":"publisher","first-page":"1598","DOI":"10.1002\/alz.13016","article-title":"2023 Alzheimer's disease facts and figures","volume":"19","author":"Alzheimer\u2019s Association Report","year":"2023","journal-title":"Alzheimers Dement."},{"key":"ref5","doi-asserted-by":"publisher","first-page":"1528","DOI":"10.1002\/alz.12311","article-title":"Measures of resting state EEG rhythms for clinical trials in Alzheimer's disease: recommendations of an expert panel","volume":"17","author":"Babiloni","year":"2021","journal-title":"Alzheimers Dement."},{"key":"ref6","doi-asserted-by":"publisher","first-page":"285","DOI":"10.1016\/j.clinph.2019.06.234","article-title":"International Federation of Clinical Neurophysiology (IFCN) \u2013 EEG research workgroup: recommendations on frequency and topographic analysis of resting state EEG rhythms. part 1: applications in clinical research studies","volume":"131","author":"Babiloni","year":"","journal-title":"Clin. 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