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Una Smailovic

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3 papers

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YNICL Journal 2026 Journal Article

Cognitive adaptations for memory deficits in MCI and AD patients: A meta-analysis of EEG microstates

Timothy Piton
Una Smailovic
Vesna Jelic
Thomas Koenig
Paul G. Unschuld
Lucie Bréchet

AIM: EEG microstate analysis enables the exploration of the brain's neuronal network activity associated with distinct mental states and cognitive functions in neurodegenerative conditions, such as Alzheimer's disease (AD). Some studies indicated that AD and patients with mild cognitive impairments (MCI) show a reduced presence of microstate C, which is related to self-related memory functions and mind-wandering and involves brain areas of the default mode network (DMN). However, other studies reported an increased presence of microstate A, which is associated with auditory/language functions. Here, we aimed to systematically investigate alterations in the four canonical EEG microstates (A, B, C, and D) in MCI and AD patients compared to healthy older adults. METHODS: We performed a meta-analysis that compared microstate temporal parameters - mean duration, occurrence rate, and time coverage - among MCI and AD patients and healthy older adults. We included 12 experimental studies that examined resting-state, eyes-closed EEG microstate parameters in 1347 participants (448 MCI patients, 514 AD patients, and 385 healthy controls). RESULTS: We found thatAD patients showed increased duration and time coverage of microstate A and increased duration of microstate B, while the occurrence of microstates C and D was reduced. MCI patients also exhibited increased duration, occurrence, and time coverage of microstate A, while all three parameters of microstate D were reduced compared to healthy controls. CONCLUSION: These results suggest that MCI and AD patients suffer from disruption in their cognitive control, memory, and self-referential processes. They may compensate for these deficits by verbalizing and visualizing their inner thoughts to maintain cognitive engagement.

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YNICL Journal 2025 Journal Article

Selective association of EEG microstates with clinical symptoms and mutation status in monogenic Alzheimer disease

Charlotte Johansson
Thomas Koenig
Una Smailovic
Vanessa Hallström
Vesna Jelic
Caroline Graff

EEG microstates are transient and short-lasting periods of stable scalp potential fields that are associated with disturbed temporal dynamics of large-scale brain networks, affected by early synaptic loss in Alzheimer disease (AD). We investigated changes in EEG microstates in presymptomatic (PMC) and symptomatic mutation carriers (SMC) compared to healthy non-carrier (NC) controls in families with autosomal dominant AD (ADAD). A total of 99 EEG recordings from 7 SMC, 17 PMC and 24 NC were selected from a Swedish ADAD cohort. Seven classes (A to G) of microstate topographical maps were fitted to their resting-state EEG. Next, microstate parameters of coverage (fraction of total recording time), duration (average time in milliseconds) and occurrence (frequency per second) of different topographical maps were assessed in repeated-measures analyses to compare differences between NC, PMC and SMC. Selective decreases in coverage of class B (SMC vs NC, p = 0.023) and class C (SMC vs PMC and NC, p = 0.017 and p = 0.004) were observed in symptomatic individuals. In contrast, mutation carriers had a decrease in coverage of class D (SMC and PMC vs NC, p = 0.015 and p = 0.001) and an increase in coverage of class E compared to controls (SMC and PMC vs NC, both p = 0.001). Thus, global brain network dynamics as described by EEG microstate classes were selectively affected in this cohort of monogenic AD, associated with either clinical symptoms (class B and C) or mutation status (class D and E). The latter suggests early mutation-related changes that are detectable already in the presymptomatic stages of disease.

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YNICL Journal 2019 Journal Article

EEG time signature in Alzheimer´s disease: Functional brain networks falling apart

Una Smailovic
Thomas Koenig
Erika J Laukka
Grégoria Kalpouzos
Thomas Andersson
Bengt Winblad
Vesna Jelic

Spontaneous mental activity is characterized by dynamic alterations of discrete and stabile brain states called functional microstates that are thought to represent distinct steps of human information processing. Electroencephalography (EEG) directly reflects functioning of brain synapses with a uniquely high temporal resolution, necessary for investigation of brain network dynamics. Since synaptic dysfunction is an early event and best correlate of cognitive status and decline in patients along Alzheimer's disease (AD) continuum, EEG microstates might serve as valuable early markers of AD. The present study investigated differences in EEG microstate topographies and parameters (duration, occurrence and contribution) between a large cohort of healthy elderly (n = 308) and memory clinic patients: subjective cognitive decline (SCD, n = 210); mild cognitive impairment (MCI, n = 230) and AD (n = 197) and how they correlate to conventional cerebrospinal fluid (CSF) markers of AD. Four most representative microstate maps assigned as classes A, B (asymmetrical), C and D (symmetrical) were computed from the resting state EEGs since it has been shown previously that this is sufficient to explain most of the resting state EEG data. Statistically different topography of microstate maps were found between the controls and the patient groups for microstate classes A, C and D. Changes in the topography of microstate class C were associated with the CSF Aβ42 levels, whereas changes in the topography of class B were linked with the CSF p-tau levels. Gradient-like increase in the contribution of asymmetrical (A and B) and gradient-like decrease in the contribution of symmetrical (C and D) maps were observed with the more severe stage of cognitive impairment. Our study demonstrated extensive relationship of resting state EEG microstates topographies and parameters with the stage of cognitive impairment and AD biomarkers. Resting state EEG microstates might therefore serve as functional markers of early disruption of neurocognitive networks in patients along AD continuum.

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