Evidence map›Paper›PMID 42807752›Full record

ArticleFrontiers in neuroscience2026

Tutorial on using EEG microstates to study moment-to-moment large-scale functional brain network dynamics in neurodevelopment.

Priyanka Ghosh, Ana C Sobrino, Kirsten A Donald, Laurel J Gabard-Durnam

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Article in Frontiers in neuroscience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Priyanka GhoshInstitute for Cognitive and Brain Health, Northeastern University, Boston, MA, United States.
Ana C SobrinoInstitute for Cognitive and Brain Health, Northeastern University, Boston, MA, United States.
Kirsten A DonaldDivision of Developmental Paediatrics, Department of Paediatrics and Child Health, Red Cross War Memorial Children's Hospital, University of Cape Town, Cape Town, South Africa.
Laurel J Gabard-DurnamInstitute for Cognitive and Brain Health, Northeastern University, Boston, MA, United States.

Funding

Wellcome Trust
6 · The paper itself

Abstract

EEG microstates are topographical patterns of EEG activity that offer a lens into the fast temporal dynamics of large-scale functional network activity and whole-brain functional organization. Microstates can capture temporal patterns of network configurations and transitions between these configurations at the millisecond scale. Although extensively studied in adults, microstates remain underutilized in developmental neuroscience, despite their potential for tracking significant developmental changes in brain network dynamics indicated by developmental fMRI studies. Extracting EEG microstates from developmental populations with relatively high artifact levels compared to adults remains a challenge due to the sensitivity of the method to such artifacts. Our tutorial provides a practical guide that walks the readers through the microstate analysis pipeline with a focus on special considerations for developmental data within the free, open-source software HAPPE (Harvard Automated Processing Pipeline for Electroencephalography) that is optimized for developmental artifacts. We first detail the conceptual foundations and current status of EEG microstates in developmental literature and then present a step-by-step tutorial on computing and interpreting microstates from resting-state and task-based EEG in developmental cohorts. All de-identified datasets used in the tutorial and the annotated microstate analysis code are freely available for public access at https://zenodo.org/records/17527065 and https://github.com/PINE-Lab/HAPPE/blob/master/3.%20generate/generateMicroStates.m. This article aims to make microstate computation more accessible, robust, and reproducible in developmental cognitive neuroscience.

Indexed as

developmental populationsEEG microstate analysisHAPPElarge scale brain networksneurodevelopmenttutorial

Identifiers

PMID42807752
PMCPMC13617483

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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.