title: 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.
  
  
  CONCLUSIONS
  Changes in inter-hemispheric EEG functional brain connectivity at rest are useful for ADHD diagnosis in a broad age range.
authors: Department of Physiology, Faculty of Medicine, University of La Laguna, Tenerife, Spain. jugonzal@ull.edu.es
authors: Julián J
authors: JJ
authors: González
authors: Leopoldo D
authors: LD
authors: Méndez
authors: Soledad
authors: S
authors: Mañas
authors: M Rosario
authors: MR
authors: Duque
authors: Ernesto
authors: E
authors: Pereda
authors: Luis
authors: L
authors: De Vera
mesh_terms: D000293:Adolescent; D000465:Algorithms; D000704:Analysis of Variance; D001289:Attention Deficit Disorder with Hyperactivity / Q000175:diagnosis* / Q000503:physiopathology; D002648:Child; D002675:Child, Preschool; D003627:Data Interpretation, Statistical; D004569:Electroencephalography / Q000379:methods* / Q000706:statistics & numerical data; D058407:Electroencephalography Phase Synchronization; D007839:Functional Laterality / Q000502:physiology; D006801:Humans; D016015:Logistic Models; D008297:Male; D009778:Occipital Lobe / Q000503:physiopathology; D012372:ROC Curve; D012984:Software; D013702:Temporal Lobe / Q000503:physiopathology