Pre-intervention test-retest reliability of EEG and ERP over four recording intervals

Ip, Cheng-Teng; Ganz, Melanie; Ozenne, Brice; Sluth, Lasse Breuning; Gram, Mikkel; Viardot, Geoffrey; L’Hostis, Philippe; Danjou, Philippe; Knudsen, Gitte M.; Christensen, Søren Rahn

doi:10.1016/j.ijpsycho.2018.09.007

Cited by 41 publications

(38 citation statements)

References 40 publications

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“…While these results were generally 297 lower than the self-reported counterpart (in the range of .7-.8), our findings are 298 comparable, if not better, than the existing studies on the stability of ERP responses (Ip 299 et al, 2018;Segalowitz & Barnes, 1993). According to previous studies, the reliability 300 of EEG and ERP was affected by various variables, such as age of 301 participants (Alperin, Mott, Rentz, Holcomb, & Daffner, 2014), recording 302 intervals (Sandman & Patterson, 2000), state and other factors (Ip et al, 2018;303 Segalowitz & Barnes, 1993). In our study, one possible source of error may have been 304 if the EEG cap aligned slightly differently between the two data collection sessions.…”

Section: Performances 276supporting

confidence: 65%

Quantitative Personality Predictions from a Brief EEG Recording

et al. 2019

Preprint

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The assessment of personality is crucial not only for scientific inquiries but also for real-world applications such as personnel selection. However, most existing ways to quantify personality traits rely on self-reported scales, which are susceptible to biases such as self-presentational concerns. In this study, we propose and evaluate a novel implicit measure of personality that uses machine learning (ML) algorithms to predict an individual's levels in the Big Five personality traits from 5 minutes of electroencephalography (EEG) recordings. Results from a large test sample of 196 volunteers indicated that the personality scores derived from the proposed measure converged significantly with a commonly used questionnaire, predicted behavioral indices and psychological adjustment in a manner similar to self-reported scores, and were relatively stable across time. These evaluations suggest that the proposed measure can serve as a viable alternative to conventional personality questionnaires in practice.

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Section: Performances 276supporting

confidence: 65%

Quantitative Personality Predictions from a Brief EEG Recording

et al. 2019

Preprint

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“…Prior studies in healthy adults have demonstrated good to excellent test-retest reliability for certain features of the PSD. EEG power for mid-range frequencies (theta, alpha, and beta, as opposed to delta and gamma; Ip et al, 2018) and relative power (as opposed to absolute power; Salinsky et al, 1991) have shown correlation coefficients >0.8 for EEG sessions a few weeks apart; this is in the range of test-retest correlations for commonly used tests of cognitive ability (Elliott, 2007;Canivez and Watkins, 1999). Methodological advances in EEG preprocessing, such as a robust reference to average and wavelet independent component analysis which act to attenuate the effects of data collection artifact, improve test-retest reliability in higher frequency bands such as beta and gamma (Suarez-Revelo et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Day-to-Day Test-Retest Reliability of EEG Profiles in Children With Autism Spectrum Disorder and Typical Development

Levin

Naples

Scheffler

et al. 2020

Front. Integr. Neurosci.

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ABC-CT EEG Test-Retest Reliability exhibit idiosyncratic PSD signatures that are stable over recording sessions using both characterizations. Our data show that EEG activity from a brief 2-min recording provides an efficient window into characterizing brain activity at the single-subject level with desirable psychometric characteristics that persist across different analytical decomposition methods. This is a necessary step towards analytical validation of biomarkers based on the EEG PSD and provides insights into parameters of the PSD that offer short-term reliability (and thus promise as potential biomarkers of trait or diagnosis) vs. those that are more variable over the short term (and thus may index state or other rapidly dynamic measures of brain function). Future research should address the longer-term stability of the PSD, for purposes such as monitoring development or response to treatment.

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“…Prior studies in healthy adults have demonstrated good to excellent test-retest reliability for certain features of the PSD. EEG power for mid-range frequencies (theta, alpha, and beta, as opposed to delta and gamma) 9 and relative power (as opposed to absolute power) 10 have shown correlation coefficients >.8 for EEG sessions a few weeks apart; this is in the range of test-retest correlations for commonly used tests of cognitive ability. 11,12 Methodological advances in EEG pre-processing, such as robust reference to average and wavelet independent component analysis which act to attenuate the effects of data collection artifact, improve test-retest reliability in higher frequency bands such as beta and gamma.…”

Section: Introductionmentioning

confidence: 83%

Within Visit Test-Retest Reliability of EEG Profiles in Children with Autism Spectrum Disorder and Typical Development

Levin

Naples

Scheffler

et al. 2019

Preprint

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37 Biomarker development is currently a high priority in neurodevelopmental disorder research. For 38 many types of biomarkers (particularly biomarkers of diagnosis), reliability over short time periods is 39 critically important. In the field of autism spectrum disorder (ASD), resting electroencephalography 40 (EEG) power spectral densities (PSD) are well-studied for their potential as biomarkers. Classically, 41 such data have been decomposed into pre-specified frequency bands (e.g., delta, theta, alpha, beta, 42 and gamma). Recent technical advances, such as the Fitting Oscillations and One-Over-F (FOOOF) 43 algorithm, allow for targeted characterization of the features that naturally emerge within an EEG 44 PSD, permitting a more detailed characterization of the frequency band-agnostic shape of each 45individual's EEG PSD. Here, using two resting EEGs collected a median of 6 days apart from 22 46 children with ASD and 25 typically developing (TD) controls during the Feasibility Visit of the 47 Autism Biomarkers Consortium for Clinical Trials, we estimate within visit test-retest reliability 48 based on characterization of the PSD shape in two ways: (1) Using the FOOOF algorithm we 49 estimate six parameters (offset, slope, number of peaks, and amplitude, center frequency and 50 bandwidth of the largest alpha peak) that characterize the shape of the EEG PSD; and (2) using 51 nonparametric functional data analyses, we decompose the shape of the EEG PSD into a reduced set 52 of basis functions that characterize individual power spectrum shapes. We show that individuals 53 exhibit idiosyncratic PSD signatures that are stable over recording sessions using both 54 characterizations. Our data show that EEG activity from a brief two-minute recording provides an 55 efficient window into understanding brain activity at the single-subject level with desirable 56 psychometric characteristics that persist across different analytical decomposition methods. This is a 57 necessary step towards analytical validation of biomarkers based on the EEG PSD, and provides 58 insights into parameters of the PSD that offer short-term reliability (and thus promise as potential 59 biomarkers of trait or diagnosis) versus those that are more variable over the short term (and thus 60 may index state or other rapidly dynamic measures of brain function). Future research should 61 address longer-term stability of the PSD, for purposes such as monitoring development or response to 62 treatment. 63 64 65 Development of translational biomarkers is a crucial step towards clinical trial readiness for 66 neurodevelopmental disorders such as Autism Spectrum Disorder (ASD). 1 The recent failure of 67 several promising clinical trials 2,3 underscores the importance of biomarker development, and the 68 need for a range of biomarkers serving a range of purposes. For example, a diagnostic biomarker can 69 confirm presence or absence of a disorder, or identify individuals with a biologically-defined subtype 70 thereof, 4 in order to guide patient s...

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Pre-intervention test-retest reliability of EEG and ERP over four recording intervals

Cited by 41 publications

References 40 publications

Quantitative Personality Predictions from a Brief EEG Recording

Quantitative Personality Predictions from a Brief EEG Recording

Day-to-Day Test-Retest Reliability of EEG Profiles in Children With Autism Spectrum Disorder and Typical Development

Within Visit Test-Retest Reliability of EEG Profiles in Children with Autism Spectrum Disorder and Typical Development

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