Generalized linear model
Generalized linear model relates to brain function and cognitive performance. Peak Brain Institute explores how QEEG brain mapping and neurofeedback training connect to generalized linear model through evidence-based approaches. Browse our 1 research paper on this topic.
Research Papers
Test–retest reliability of resting EEG spectra validates a statistical signature of persons
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 α peak frequency and α peak height were transformed into Z-scores. We compared the curve shape of power spectra by first aligning α 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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