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Physiologic artifacts in resting state oscillations in young children: methodological considerations for noisy data

  • SI: Developing Brain
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Abstract

We quantified the potential effects of physiologic artifact on the estimation of EEG band power in a cohort of typically developing children in order to guide artifact rejection methods in quantitative EEG data analysis in developmental populations. High density EEG was recorded for 2 min while children, ages 2–6, watched a video of bubbles. Segments of data were categorized as blinks, saccades, EMG or artifact-free, and both absolute and relative power in the theta (4–7 Hz), alpha (8–12 Hz), beta (13–30 Hz) and gamma (35–45 Hz) bands were calculated in 9 regions for each category. Using a linear mixed model approach with artifact type, region and their interaction as predictors, we compared mean band power between clean data and each type of artifact. We found significant differences in mean relative and absolute power between artifacts and artifact-free segments in all frequency bands. The magnitude and direction of the differences varied based on power type, region, and frequency band. The most significant differences in mean band power were found in the gamma band for EMG artifact and the theta band for ocular artifacts. Artifact detection strategies need to be sensitive to the oscillations of interest for a given analysis, with the most conservative approach being the removal of all EMG and ocular artifact from EEG data. Quantitative EEG holds considerable promise as a clinical biomarker of both typical and atypical development. However, there needs to be transparency in the choice of power type, regions of interest, and frequency band, as each of these variables are differentially vulnerable to noise, and therefore, their interpretation depends on the methods used to identify and remove artifacts.

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Acknowledgments

This research was funded by NIMH 5K23MH094517 – 02 (PI Jeste) and the Autism Speaks Weatherstone Predoctoral Fellowship 7845 (McEvoy, Kevin).

Conflict of Interest

Kevin McEvoy Kyle Hasenstab, Damla Senturk, Andrew Sanders, and Shafali S. Jeste declare that they have no conflicts of interest.

Informed Consent

All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1975, and the applicable revisions at the time of the investigation. Informed consent was obtained from all patients for being included in the study.

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  1. Semel Institute for Neuroscience and Human Behavior, Center for Autism Research and Treatment, University of California Los Angeles, 760 Westwood Plaza, Suite 68-237, Los Angeles, CA, 90095, USA

    Kevin McEvoy, Kyle Hasenstab, Damla Senturk, Andrew Sanders & Shafali S. Jeste

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  1. Kevin McEvoy
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Correspondence to Shafali S. Jeste.

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McEvoy, K., Hasenstab, K., Senturk, D. et al. Physiologic artifacts in resting state oscillations in young children: methodological considerations for noisy data. Brain Imaging and Behavior 9, 104–114 (2015). https://doi.org/10.1007/s11682-014-9343-7

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