ArticleFrontiers in human neuroscience2019
EEG Microstates Analysis in Young Adults With Autism Spectrum Disorder During Resting-State.
Article in Frontiers in human neuroscience, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers, 2 of them syntheses that pooled it.
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Who cites it
39 citing papers in PubMed, 2 syntheses or guidelines pooled it, 81 citations in OpenAlex.
- Distinct features of EEG microstates in autism spectrum disorder revealed by meta-analysis: the contribution of individual age to heterogeneity across studies.Frontiers in psychiatry · 2025Pooled it
- Detecting electrophysiological alterations in psychiatric disorders through event-related microstates: a systematic review.Frontiers in psychiatry · 2025Pooled it
- Atypical Resting-State and Task-Evoked EEG Signatures in Children with Developmental Language Disorder.Bioengineering (Basel, Switzerland) · 2026Article
- Explainable AI uncovers novel EEG microstate candidate neurophysiological markers for autism spectrum disorder.Frontiers in computational neuroscience · 2026Article
- PRISMA Systematic Review of Electroencephalographic (EEG) Microstates as Biomarkers: Secondary Findings in Memory Functions.Neurology international · 2025Review
- Heterogeneous Brain Dynamics Between Acute Cerebellar and Brainstem Infarction.Cerebellum (London, England) · 2024Article
- Resting state EEG microstate profiling and a machine-learning based classifier model in epilepsy.Cognitive neurodynamics · 2024Article
- EEG Spatial-temporal Dynamics of Resting-state Activity in Young Women with Anorexia Nervosa: Preliminary Evidence.Brain topography · 2024Article
- EEG Microstates as Markers for Cognitive Impairments in Fragile X Syndrome.Brain topography · 2024Article
- Resting-state EEG Microstate Features Can Quantitatively Predict Autistic Traits in Typically Developing Individuals.Brain topography · 2024Article
- Altered EEG Patterns in Individuals with Disorganized Attachment: An EEG Microstates Study.Brain topography · 2024Article
- Dynamics of Cerebral Function in Patients with Acute Cerebellar Infarction.Cerebellum (London, England) · 2024Article
- Frequency Analysis of EEG Microstate Sequences in Wakefulness and NREM Sleep.Brain topography · 2024Article
- Effect of topographic comparison of electroencephalographic microstates on the diagnosis and prognosis prediction of patients with prolonged disorders of consciousness.CNS neuroscience & therapeutics · 2024Article
- On the Reliability of the EEG Microstate Approach.Brain topography · 2024Article
- Temporal and spatial variability of dynamic microstate brain network in disorders of consciousness.CNS neuroscience & therapeutics · 2024Article
- EEG microstates in early-to-middle childhood show associations with age, biological sex, and alpha power.Human brain mapping · 2023Article
- Spatiotemporal Dynamics of Memory Encoding and Memory Retrieval States.Journal of cognitive neuroscience · 2023Article
- Electroencephalography microstates imbalance across the spectrum of early psychosis, autism, and mood disorders.European psychiatry : the journal of the Association of European Psychiatrists · 2023Article
- The effect of acupuncture at theFrontiers in integrative neuroscience · 2023Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Electroencephalography (EEG) is a useful tool to inspect the brain activity in resting state and allows to characterize spontaneous brain activity that is not detected when a subject is cognitively engaged. Moreover, taking advantage of the high time resolution in EEG, it is possible to perform fast topographical reference-free analysis, since different scalp potential fields correspond to changes in the underlying sources within the brain. In this study, the spontaneous EEG resting state (eyes closed) was compared between 10 young adults ages 18-30 years with autism spectrum disorder (ASD) and 13 neurotypical controls. A microstate analysis was applied, focusing on four temporal parameters: mean duration, the frequency of occurrence, the ratio of time coverage, and the global explained variance (GEV). Using data that were acquired from a 65-channel EEG system, six resting-state topographies that best describe the dataset across all subjects were identified by running a two-step cluster analysis labeled as microstate classes A-F. The results indicated that microstates B and E displayed statistically significant differences between both groups among the temporal parameters evaluated. Classes B, D, E, and F were consistently more present in ASD, and class C in controls. The combination of these findings with the putative functional significance of the different classes suggests that during resting state, the ASD group was more focused on visual scene reconstruction, while the control group was more engaged with self-memory retrieval. Furthermore, from a connectivity perspective, the resting-state networks that have been previously associated with each microstate class overlap the brain regions implicated in impaired social communication and repetitive behaviors that characterize ASD.
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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.