Changes in the left temporal microstate are a sign of cognitive decline in patients with Alzheimer's disease. Issue 6 (27th April 2020)

• Record Type: Journal Article
• Authors: Musaeus, Christian S.; Engedal, Knut; Høgh, Peter; Jelic, Vesna; Khanna, Arjun R.; Kjær, Troels Wesenberg; Mørup, Morten; Naik, Mala; Oeksengaard, Anne‐Rita; Santarnecchi, Emiliano; Snaedal, Jon; Wahlund, Lars‐Olof; Waldemar, Gunhild; Andersen, Birgitte B.
• Is Part Of: Brain and behavior. Volume 10:Issue 6(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-04-27
• Subjects: Alzheimer's disease -- EEG -- microstate -- mild cognitive impairment -- network; Neurology -- Periodicals; Neurosciences -- Periodicals; Psychology -- Periodicals; Psychiatry -- Periodicals; 616.8005
• DOI: 10.1002/brb3.1630
• Languages: English
• ISSNs: 2162-3279

Abstract

Abstract: Introduction: Large‐scale brain networks are disrupted in the early stages of Alzheimer's disease (AD). Electroencephalography microstate analysis, a promising method for studying brain networks, parses EEG signals into topographies representing discrete, sequential network activations. Prior studies indicate that patients with AD show a pattern of global microstate disorganization. We investigated whether any specific microstate changes could be found in patients with AD and mild cognitive impairment (MCI) compared to healthy controls (HC). Materials and methods: Standard EEGs were obtained from 135 HC, 117 patients with MCI, and 117 patients with AD from six Nordic memory clinics. We parsed the data into four archetypal microstates. Results: There was significantly increased duration, occurrence, and coverage of microstate A in patients with AD and MCI compared to HC. When looking at microstates in specific frequency bands, we found that microstate A was affected in delta (1–4 Hz), theta (4–8 Hz), and beta (13–30 Hz), while microstate D was affected only in the delta and theta bands. Microstate features were able to separate HC from AD with an accuracy of 69.8% and HC from MCI with an accuracy of 58.7%. Conclusions: Further studies are needed to evaluate whether microstates represent a valuable disease classifier. Overall, patients with AD and MCI, as compared to HC, show specific microstate alterations, which are limited to specific frequency bands. These alterations suggest disruption of large‐scale cortical networks in AD and MCI, which may be limited to specific frequency bands. Abstract : Large‐scale brain networks are disrupted in the early stages of Alzheimer's disease. Due to the timescale, electroencephalography has shown to be a suitable technique to investigate these cortical networks. By using EEG, we found that large‐scale cortical networks associated with the temporal lobes were disrupted in patients with Alzheimer's disease.