ArticleBrain and behavior2025
Microstate Dynamics in Working Memory: Exploring Spatial Information Coding of Stimulus and Behavioral Performance.
Article in Brain and behavior, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Association Between Spatiotemporal Properties of Global Brain Activity and Childhood Emotional and Behavioral Problems: Evidence from Microstate C.Brain topography · 2026Article
- EEG microstate alterations in Parkinson's disease dementia.Scientific reports · 2026Article
- Microstate Dynamics in Working Memory: Exploring Spatial Information Coding of Stimulus and Behavioral Performance.Brain and behavior · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundEEG microstate analysis provides insights into the spatial and temporal dynamics of brain activity during cognitive tasks. The four canonical microstates (classes A, B, C, and D) have been widely reported and associated with various cognitive functions. However, the relationship between microstate parameters and behavioral responses in cognitive functions, such as working memory (WM), has not been sufficiently investigated. This study investigates how microstate dynamics relate to WM performance during a memory-guided saccade (MGS) task. Methods EEG and Eye-tracking data were recorded from participants performing an MGS task at two target eccentricities (near and far). Saccade error was used as a behavioral index of WM performance. Microstate parameters (occurrence, coverage, duration, and transition probability) were computed for the four canonical microstates during the trials. Results Our analysis revealed a significant reduction in the coverage of microstate C, often associated with the default mode network, during the memory maintenance interval compared to baseline. Moreover, a notable increase was observed in the duration of microstate D, considering polarity during the memory interval, which could be related to the frontoparietal control network (FPCN). Notably, the transition probability (TP) from D+ to D- during the memory duration correlated with saccade errors, indicating a behavioral predictive capacity. Furthermore, we identified distinct patterns of microstate D transitions to other microstates that differed significantly between the near and far target conditions, suggesting a functional role in spatial coding. Conclusion Microstate dynamics, particularly those of microstate D, play a dual role in spatial WM by supporting information coding and predicting behavioral accuracy. The polarity-specific transitions within microstate D provide a neural signature of WM performance, with implications for understanding network-level mechanisms underlying spatial memory and saccade control.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.