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Test-retest reliability of resting EEG spectra validates a statistical signature of persons


Näpflin, M; Wildi, M; Sarnthein, J (2007). Test-retest reliability of resting EEG spectra validates a statistical signature of persons. Clinical Neurophysiology, 118(11):2519-24.

Abstract

OBJECTIVE: When EEG is recorded in humans, the question arises whether the resting EEG remains stable. We compared the inter-individual variation in spectral observables to the intra-individual stability over more than a year. METHODS: We recorded resting EEG in 55 healthy adults with eyes closed. In 20 persons EEG was recorded in a second session with retest intervals 12-40 months. For electrodes AFz, Cz and Pz alpha peak frequency and alpha peak height were transformed into Z-scores. We compared the curve shape of power spectra by first aligning alpha peaks to 10Hz and then regressing spectra pairwise onto each other to calculate a t-value. The t-value and differences of Z-scores for all pairs of sessions were entered into a generalized linear model (GLM) where binary output represents the recognition probability. The results were cross-validated by out-of-sample testing. RESULTS: Of the 40 sessions, 35 were correctly matched. The shape of power spectra contributed most to recognition. Out of all 2960 pairwise comparisons 99.5% were correct, with sensitivity 88% and specificity 99.5%. CONCLUSIONS: Our statistical apparatus allows to identify those spectral EEG observables which qualify as statistical signature of a person. SIGNIFICANCE: The effect of external factors on EEG observables can be contrasted against their normal variability over time.

Abstract

OBJECTIVE: When EEG is recorded in humans, the question arises whether the resting EEG remains stable. We compared the inter-individual variation in spectral observables to the intra-individual stability over more than a year. METHODS: We recorded resting EEG in 55 healthy adults with eyes closed. In 20 persons EEG was recorded in a second session with retest intervals 12-40 months. For electrodes AFz, Cz and Pz alpha peak frequency and alpha peak height were transformed into Z-scores. We compared the curve shape of power spectra by first aligning alpha peaks to 10Hz and then regressing spectra pairwise onto each other to calculate a t-value. The t-value and differences of Z-scores for all pairs of sessions were entered into a generalized linear model (GLM) where binary output represents the recognition probability. The results were cross-validated by out-of-sample testing. RESULTS: Of the 40 sessions, 35 were correctly matched. The shape of power spectra contributed most to recognition. Out of all 2960 pairwise comparisons 99.5% were correct, with sensitivity 88% and specificity 99.5%. CONCLUSIONS: Our statistical apparatus allows to identify those spectral EEG observables which qualify as statistical signature of a person. SIGNIFICANCE: The effect of external factors on EEG observables can be contrasted against their normal variability over time.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > Center for Integrative Human Physiology
04 Faculty of Medicine > University Hospital Zurich > Clinic for Neurosurgery
Dewey Decimal Classification:570 Life sciences; biology
610 Medicine & health
Language:English
Date:November 2007
Deposited On:20 Mar 2009 08:19
Last Modified:06 Dec 2017 15:43
Publisher:Elsevier
ISSN:1388-2457
Publisher DOI:https://doi.org/10.1016/j.clinph.2007.07.022
PubMed ID:17892969

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