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Such a mechanism plays a potentially important role in maintaining cognitive function during the early stages of neurodegenerative disorders such as Alzheimer's disease (AD). AD is characterized by severe cognitive decline and involves a long prodromal stage of mild cognitive impairment (MCI). Since MCI subjects are at high risk of converting to AD, identifying MCI individuals is essential for early intervention. To delineate the redundancy profile during AD progression and enable better MCI diagnosis, we define a metric that reflects redundant disjoint connections between brain regions and extract redundancy features in three high\u2010order brain networks\u2014medial frontal, frontoparietal, and default mode networks\u2014based on dynamic functional connectivity (dFC) captured by resting\u2010state functional magnetic resonance imaging (rs\u2010fMRI). We show that redundancy increases significantly from normal control (NC) to MCI individuals and decreases slightly from MCI to AD individuals. We further demonstrate that statistical features of redundancy are highly discriminative and yield state\u2010of\u2010the\u2010art accuracy of up to 96.8\u2009\u00b1\u20091.0% in support vector machine (SVM) classification between NC and MCI individuals. This study provides evidence supporting the notion that redundancy serves as a crucial neuroprotective mechanism in MCI.<\/jats:p>","DOI":"10.1002\/hbm.26257","type":"journal-article","created":{"date-parts":[[2023,3,10]],"date-time":"2023-03-10T05:31:07Z","timestamp":1678426267000},"page":"2993-3006","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["Accumulation of network redundancy marks the early stage of Alzheimer's disease"],"prefix":"10.1002","volume":"44","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2131-7122","authenticated-orcid":false,"given":"Maryam","family":"Ghanbari","sequence":"first","affiliation":[{"name":"Department of Radiology University of North Carolina  Chapel Hill North Carolina USA"},{"name":"Biomedical Research Imaging Center University of North Carolina  Chapel Hill North Carolina 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