A novel quantitative electroencephalography subtype with high alpha power in ADHD: ADHD or misdiagnosed ADHD?

• Published in: PloS one 2020-11, Vol.15 (11), p.e0242566-e0242566
• Main Authors: Byeon, Jun, Choi, Tae Young, Won, Geun Hui, Lee, Jaewon, Kim, Jun Won
• Format: Article
• Language: English
• Subjects: Attention Deficit Disorder with Hyperactivity - diagnosis; Attention Deficit Disorder with Hyperactivity - metabolism; Attention deficit hyperactivity disorder; Beta Rhythm - physiology; Biology and Life Sciences; Brain - physiology; Brain Mapping - methods; Child; Children; Cluster analysis; Diagnosis; Diagnostic Errors - prevention & control; Diagnostic systems; EEG; Electroencephalography; Electroencephalography - methods; Female; Frequency ranges; Humans; Magnetic resonance imaging; Male; Medical diagnosis; Medicine and Health Sciences; Mental disorders; People and Places; Performance tests; Physical Sciences; Republic of Korea; Research and Analysis Methods; Schedules; Social Sciences; Teenagers; Theta Rhythm - physiology
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0242566

This study investigated quantitative electroencephalography (QEEG) subtypes as auxiliary tools to assess Attention Deficit Hyperactivity Disorder (ADHD). A total of 74 subjects (58 male and 16 female) were assessed using the Korean version of the Diagnostic Interview Schedule for Children Version IV and were assigned to one of three groups: ADHD, ADHD-Not Otherwise specified (NOS), and Neurotypical (NT). We measured absolute and relative EEG power in 19 channels and conducted an auditory continuous performance test. We analyzed QEEG according to the frequency range: delta (1-4 Hz), theta (4-8 Hz), slow alpha (8-10 Hz), fast alpha (10-13.5 Hz), and beta (13.5-30 Hz). The subjects were then grouped by Ward's method of cluster analysis using the squared Euclidian distance to measure dissimilarities. We discovered four QEEG clusters, which were characterized by: (a) elevated delta power with less theta activity, (b) elevated slow alpha relative power, (c) elevated theta with deficiencies of alpha and beta relative power, and (d) elevated fast alpha and beta absolute power. The largest proportion of participants in clusters (a) and (c) were from the ADHD group (48% and 47%, respectively). Conversely, group (b) mostly consisted of the participants from the NOS group (59%), while group (d) had the largest proportion of participants from the NT group (62%). These results indicate that children with ADHD does not neurophysiologically constitute a homogenous group. We also identified a new subtype with increased alpha power in addition to those commonly reported in ADHD. Given the QEEG characteristics with increased alpha power, we should consider the possibility that this subtype may be caused by childhood depression. In conclusion, we believe that these QEEG subtypes of ADHD are expected to provide valuable information for accurately diagnosing ADHD.