Performance analysis of univariate and multivariate EEG measurements in the diagnosis of ADHD

Abstract

Objective: To investigate the performance of univariate and multivariate EEG measurements in diagnosing ADHD subjects in a broad age range.

Methods: EEG from eight cortical regions were recorded at rest during eyes open and eyes closed in 22 male ADHD subjects of combined type and 21 healthy male controls (age range 4-15 years). Univariate and interdependence measurements calculated from the frequency domain and from the reconstructed state spaces of EEG signals were computed, and their performance in discriminating ADHD from healthy subjects was analyzed.

Results: Significant between-group differences in univariate measures were age-dependent. However, certain interdependence inter-hemispheric measures during eyes closed showed significant, age-independent between-groups differences. Among them, coherence in the beta band between inter-occipital regions and between left/occipital-right/central regions provided an overall accuracy classification rate of 74.4%. Even greater accuracy (86.7%) was obtained by an interdependence index of generalized synchronization between left/occipital-right/central regions and left/central-right/temporal regions.

Conclusions: EEG beta coherence and especially the degree of generalized synchronization between a few inter-hemispheric regions during resting state with eyes closed allow a high accuracy classification rate of ADHD subjects.

Significance: Changes in inter-hemispheric EEG functional brain connectivity at rest are useful for ADHD diagnosis in a broad age range.