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

Overview

1. Institute for Cognitive and Brain Health, Northeastern University, Boston, MA, United States
2. Department of Psychology, Northeastern University, Boston, MA, United States
3. Division of Developmental Paediatrics, Department of Paediatrics and Child Health, Red Cross War Memorial Children’s Hospital, University of Cape Town, Cape Town, South Africa
4. The Neuroscience Institute, University of Cape Town, Cape Town, South Africa

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.

Reproduced under the paper's license (CC BY), from the paper cited above.

Code

The paper links to its data and to no code of its authors: see the Data section.

Tracing map

A tracing map links a paper to the code its authors published: this paper has none, so it has no map.

Data

Datasets cited

• zenodo:17527065, at Zenodo; found in the text, “Background”

Data availability statement

The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found at: https://zenodo.org/records/17527065.

Reproduced under the paper's license (CC BY), from the paper cited above.

Versions

The history of this record: each version stored by the harvester or made by a correction of its authors or of the maintainers of its code, and what changed in its facts. The texts of the paper (its abstract, its availability statements) are not part of it; versions that changed only those are not listed.

Version 1, 29 September 2026: the first record

Recorded: type, language, journal, volume, pages, dates, 4 authors, 6 keywords, 83 references.

Cite

This paper

Ghosh, P., Sobrino, A. C., Donald, K. A., & Gabard-Durnam, L. J. (2026). Tutorial on using EEG microstates to study moment-to-moment large-scale functional brain network dynamics in neurodevelopment. Frontiers in neuroscience, 20, 1891985.

Similar papers

The papers with a page that share the most with this one: the tools found in their code, their categories, datasets, cited references and authors, the rarest counting most.

[1] doi:10.1162/imag.a.59 [code]

Spatiotemporal dynamics of EEG microstate networks over the first two years of life: A multi-cohort longitudinal study.

Journal: Imaging neuroscience (Cambridge, Mass.)

In common: developmental, EEG, 32 references

[2] doi:10.1007/s10548-024-01043-5

Microstate Analysis of Continuous Infant EEG: Tutorial and Reliability.

Journal: Brain topography

In common: developmental, EEG, 17 references

[3] doi:10.1073/pnas.2414636122 [code]

Infant EEG microstate dynamics relate to fine-grained patterns of infant attention during naturalistic play with caregivers.

Journal: Proceedings of the National Academy of Sciences of the United States of America

In common: developmental, EEG, 17 references

[4] doi:10.1007/s10548-023-00993-6 [code]

EEG-Meta-Microstates: Towards a More Objective Use of Resting-State EEG Microstate Findings Across Studies.

Journal: Brain topography

In common: EEG, 15 references

[5] doi:10.1186/s12868-024-00854-3 [code]

State-transition dynamics of resting-state functional magnetic resonance imaging data: model comparison and test-to-retest analysis.

Journal: BMC neuroscience

In common: EEG, 15 references

[6] doi:10.1007/s10548-023-00982-9 [code]

On the Reliability of the EEG Microstate Approach.

Journal: Brain topography

In common: EEG, 14 references

[7] doi:10.1162/imag_a_00450

Characterizing the temporal dynamics and maturation of brain activity during sleep: An EEG microstate study in preterm and full-term infants.

Journal: Imaging neuroscience (Cambridge, Mass.)

In common: developmental, EEG, 13 references

[8] doi:10.3390/brainsci15060544

Resting Electroencephalography Microstates and Alpha Power Modulation in Preschool-Aged Children with Autism Spectrum Disorder.

Journal: Brain sciences

In common: developmental, EEG, 12 references

[9] doi:10.1016/j.dcn.2022.101134 [code]

Spatiotemporal dynamics of EEG microstates in four- to eight-year-old children: Age- and sex-related effects.

Journal: Developmental cognitive neuroscience

In common: developmental, EEG, 13 references

[10] doi:10.1007/s10548-022-00929-6 [code]

Trait Aggression is Reflected by a Lower Temporal Stability of EEG Resting Networks.

Journal: Brain topography

In common: EEG, 13 references

Contribute

The authors of this paper can claim it, correct its record and validate its tracing map, and the maintainers of its code (its owner, or a public member of its organization) correct what it says of their repository; anyone signed in can ask for its removal. Every request goes to OSCR's own machine, which answers it; your account page follows them.

Request its removal

To ask OSCR to remove this record, the copies of its authors' scripts or its tracing map, use the removal request page: signed in, you say who you are, what to remove and why, then review and confirm the request. Published rules decide every request (how).

Discussion: code errors and mismatches between the code and the paper about this paper and its code, from readers and its authors, beside the paper and its tracing map.

Reproductions: reports from readers who ran the authors' code and did not get the paper's result, what they ran, with which environment, commit and data.

Activity: what happens around this paper: new versions of its record, its map's validation, discussions and reproductions. It opens with sign-in.