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These differences can be interrogated by examining EEG microstates, which are distinct, reoccurring topographies of the scalp's electrical potentials. Quantifying the temporal properties of the four canonical microstates can elucidate how the dynamics of functional brain networks are altered in neurological conditions. Here we have analysed the properties of microstates to detect and quantify signal\u2010based abnormality in ALS. High\u2010density resting\u2010state EEG data from 129 people with ALS and 78 HC were recorded longitudinally over a 24\u2010month period. EEG topographies were extracted at instances of peak global field power to identify four microstate classes (labelled A\u2010D) using K\u2010means clustering. Each EEG topography was retrospectively associated with a microstate class based on global map dissimilarity. Changes in microstate properties over the course of the disease were assessed in people with ALS and compared with changes in clinical scores. The topographies of microstate classes remained consistent across participants and conditions. Differences were observed in coverage, occurrence, duration, and transition probabilities between ALS and control groups. The duration of microstate class B and coverage of microstate class C correlated with lower limb functional decline. The transition probabilities A to D, C to B and C to B also correlated with cognitive decline (total ECAS) in those with cognitive and behavioural impairments. Microstate characteristics also significantly changed over the course of the disease. Examining the temporal dependencies in the sequences of microstates revealed that the symmetry and stationarity of transition matrices were increased in people with late\u2010stage ALS. These alterations in the properties of EEG microstates in ALS may reflect abnormalities within the sensory network and higher\u2010order networks. Microstate properties could also prospectively predict symptom progression in those with cognitive impairments.<\/jats:p>","DOI":"10.1002\/hbm.26536","type":"journal-article","created":{"date-parts":[[2023,12,13]],"date-time":"2023-12-13T08:14:06Z","timestamp":1702455246000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":25,"title":["Functional network dynamics revealed by <scp>EEG<\/scp> microstates reflect cognitive decline in amyotrophic lateral sclerosis"],"prefix":"10.1002","volume":"45","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-5463-1931","authenticated-orcid":false,"given":"Marjorie","family":"Metzger","sequence":"first","affiliation":[{"name":"Academic Unit of Neurology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College Dublin University of Dublin  Dublin 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