Background: Mild cognitive impairment (MCI) is a relatively recent concept that describes a neurological condition depicting the transitional stage between healthy aging and severe cognitive deficits due to dementia pathologies. Because of its intermediate character, MCI is increasingly at the center of scientific interest in an effort to prevent the transition to dementia. Resting-state EEG microstates represent brief periods of global neuronal synchronization of large-scale networks that dynamically change over time.
Aim: This study aims to detect alterations in MCI patients compared to healthy controls during resting-state high-density EEG recordings using the EEG microstate approach and examine associations between intrinsic dynamics of EEG microstates and self-reported thoughts using the Amsterdam Resting-State Questionnaire (ARSQ) (Diaz et al., 2013). To my knowledge, the ARSQ has not been tested on MCI patients before. Cognitive abilities were measured using the Montreal Cognitive Assessment (MoCA) (Nasreddine et al., 2005). The MoCA is a validated and highly sensitive tool to detect cognitive decline due to MCI.
Methods: 143 participants were recruited: 23 MCI patients (9 female; Mage= 70.9), 60 healthy older (HO; 34 female; Mage=71.5) and 60 healthy younger (HY; 33 female; Mage=25.9) participants. The resting-state activity was acquired for 5 minutes in eyes closed condition, using the 257-channel EGI system to characterize microstate alterations in global explained variance, duration, occurrence, and time coverage. After the recording, a subgroup of participants (22 MCIs, 50 HO, and 31 HY) completed the Amsterdam Resting-State Questionnaire (ARSQ), specifying their thoughts during the rest. Furthermore, every participant completed the MoCA to assess their cognitive performance in visuospatial abilities, executive functions, attention, concentration and working memory, language, memory, and orientation.
Results: The four canonical microstates A, B, C, and D were found across the three groups. MCI patients showed significant differences from healthy participants, specifically in microstates A and B. Significant differences between healthy younger and older participants were found in all four microstates. The MoCA results allowed distinguishing the MCI group from the healthy control groups using the scores for executive functions, memory, orientation, and the overall score. The ARSQ presented significantly different values for healthy younger compared to older participants and MCI patients in the dimensions of self, sleepiness, discontinuity of mind, theory of mind, planning, visual thoughts, and verbal thoughts. Correlation analysis between EEG microstates, ARSQ and MoCA revealed associations between microstate A and sleepiness (ARSQ), microstate B and discontinuity of mind (ARSQ), theory of mind (ARSQ), visual thoughts (ARSQ) and verbal thoughts (ARSQ), microstate C and discontinuity of mind (ARSQ), planning (ARSQ), executive function (MoCA), memory (MoCA) and the overall MoCA score; microstate D and comfort (ARSQ), executive function (MoCA), language (MoCA), memory (ARSQ) and the overall MoCA score.
Conclusion: These findings demonstrate the relevance of characterizing microstate dynamics in MCI patients and assessing spontaneous thought for understanding intrinsic brain activity.
