{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,5]],"date-time":"2026-08-05T04:48:38Z","timestamp":1785905318727,"version":"3.56.0"},"reference-count":52,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2026,7,31]],"date-time":"2026-07-31T00:00:00Z","timestamp":1785456000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Youth Fund Project for Humanities and Social Sciences Research of the Ministry of Education","award":["24YJCZH366 and 25YJCZH280"],"award-info":[{"award-number":["24YJCZH366 and 25YJCZH280"]}]},{"name":"Youth Science Research Project of Basic Research Program of Shanxi Province","award":["202403021212185 and 202503021212275"],"award-info":[{"award-number":["202403021212185 and 202503021212275"]}]},{"name":"Science and Technology Innovation Project of Higher Education Institutions of Shanxi Province","award":["2024L158"],"award-info":[{"award-number":["2024L158"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Brain Sci.","Brain Sciences"],"abstract":"<jats:p>Background: Alzheimer\u2019s disease (AD) and mild cognitive impairment (MCI) are associated with abnormalities in brain networks. However, differences in the control architecture of directed brain effective networks among normal controls (NC), patients with MCI, and patients with AD remain insufficiently characterized. This study investigated diagnostic-group differences in driving structures and controllability patterns in structurally constrained brain effective networks. Methods: Multimodal neuroimaging data, including diffusion MRI and resting-state functional MRI, were used to construct brain effective networks in the NC, MCI, and AD groups. Directed interregional interactions were estimated using multivariate autoregressive modeling under structural connectivity constraints. A structural controllability framework based on maximum matching was then applied to identify group-level driving nodes and driving edges. Controllability index was compared across groups separately at the whole-brain, resting-state network (RSN), and regional levels. Results: Group-level driving structures differed among the NC, MCI, and AD groups. Driving nodes were mainly distributed within the default mode network, with additional somatosensory and motor network drivers in MCI and a frontoparietal network driver in AD. The whole-brain controllability index decreased from NC to MCI and increased from MCI to AD. Similar nonmonotonic patterns were observed in the default mode and frontoparietal networks, whereas the somatosensory and motor and visual networks showed different group patterns. Regional node controllability was negatively associated with indegree and positively associated with outdegree, and driving nodes were more likely to correspond to outdegree hubs. Hub-level controllability showed a pattern opposite to that of the whole brain. Several regional indices were associated with cognitive scores, although these pooled cross-sectional associations may partly reflect diagnostic-group separation. Conclusions: MCI and AD were associated with differences in driving structures and controllability patterns in directed brain effective networks. These findings provide preliminary network-level observations on altered directed information propagation across the AD clinical spectrum and require validation in larger, independent, and longitudinal cohorts.<\/jats:p>","DOI":"10.3390\/brainsci16080820","type":"journal-article","created":{"date-parts":[[2026,7,31]],"date-time":"2026-07-31T15:02:01Z","timestamp":1785510121000},"page":"820","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Altered Driving Structures and Controllability Patterns of Brain Effective Networks in Mild Cognitive Impairment and Alzheimer\u2019s Disease"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-3494-2723","authenticated-orcid":false,"given":"Jiayue","family":"Xue","sequence":"first","affiliation":[{"name":"School of Information, Shanxi University of Finance and Economics, Taiyuan 030006, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-7282-5274","authenticated-orcid":false,"given":"Xinyi","family":"Yan","sequence":"additional","affiliation":[{"name":"School of Information, Shanxi University of Finance and Economics, Taiyuan 030006, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8710-7369","authenticated-orcid":false,"given":"Jing","family":"Wei","sequence":"additional","affiliation":[{"name":"School of Information, Shanxi University of Finance and Economics, Taiyuan 030006, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Min","family":"Gao","sequence":"additional","affiliation":[{"name":"School of Information, Shanxi University of Finance and Economics, Taiyuan 030006, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ke","family":"Liang","sequence":"additional","affiliation":[{"name":"School of Statistics, Shanxi University of Finance and Economics, Taiyuan 030006, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,7,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2227","DOI":"10.1056\/NEJMcp0910237","article-title":"Mild Cognitive Impairment","volume":"364","author":"Petersen","year":"2011","journal-title":"N. 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