Literature DB >> 25501709

Trajectory of frequency stability in typical development.

Joel Frohlich1, Andrei Irimia, Shafali S Jeste.   

Abstract

This work explores a feature of brain dynamics, metastability, by which transients are observed in functional brain data. Metastability is a balance between static (stable) and dynamic (unstable) tendencies in electrophysiological brain activity. Furthermore, metastability is a theoretical mechanism underlying the rapid synchronization of cell assemblies that serve as neural substrates for cognitive states, and it has been associated with cognitive flexibility. While much previous research has sought to characterize metastability in the adult human brain, few studies have examined metastability in early development, in part because of the challenges of acquiring adequate, noise free continuous data in young children. To accomplish this endeavor, we studied a new method for characterizing the stability of EEG frequency in early childhood, as inspired by prior approaches for describing cortical phase resets in the scalp EEG of healthy adults. Specifically, we quantified the variance of the rate of change of the signal phase (i.e., frequency) as a proxy for phase resets (signal instability), given that phase resets occur almost simultaneously across large portions of the scalp. We tested our method in a cohort of 39 preschool age children (age =53 ± 13.6 months). We found that our outcome variable of interest, frequency variance, was a promising marker of signal stability, as it increased with the number of phase resets in surrogate (artificial) signals. In our cohort of children, frequency variance decreased cross-sectionally with age (r = -0.47, p = 0.0028). EEG signal stability, as quantified by frequency variance, increases with age in preschool age children. Future studies will relate this biomarker with the development of executive function and cognitive flexibility in children, with the overarching goal of understanding metastability in atypical development.

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Year:  2015        PMID: 25501709      PMCID: PMC4385521          DOI: 10.1007/s11682-014-9339-3

Source DB:  PubMed          Journal:  Brain Imaging Behav        ISSN: 1931-7557            Impact factor:   3.978


  65 in total

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  3 in total

Review 1.  Brain connectivity in autism spectrum disorder.

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Journal:  Curr Opin Neurol       Date:  2016-04       Impact factor: 5.710

Review 2.  Electrophysiological biomarkers of diagnosis and outcome in neurodevelopmental disorders.

Authors:  Shafali S Jeste; Joel Frohlich; Sandra K Loo
Journal:  Curr Opin Neurol       Date:  2015-04       Impact factor: 5.710

3.  Evolutionary Advantages of Stimulus-Driven EEG Phase Transitions in the Upper Cortical Layers.

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Journal:  Front Syst Neurosci       Date:  2021-12-08
  3 in total

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