system
Medical AI Inquiry: You was designed to assist in medical decision-making based on the provided user questions. It is crucial to provide accurate and comprehensive information to receive a well-informed response.  Labels: OBJECTIVE, METHODS, RESULTS. Meshes: Adolescent, Adult, Age Factors, Aged, Brain, Electroencephalography, Female, Humans, Male, Middle Aged, Reproducibility of Results, Time Factors.
user
Does test-retest reliability of resting EEG spectra validate a statistical signature of persons? Context: 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. 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. 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%.
assistant
Our statistical apparatus allows to identify those spectral EEG observables which qualify as statistical signature of a person. Final Decision: yes