The aim of this study was to explore neural oscillation features (resting-state + oddball-EROs) of ADHD symptoms in children in a dimensional approach and to construct a multi-metric model combining objective EEG measures and subjective parental ratings to predict children’s behavioral performance.
Method:
Seventy-seven children (age range: 6–12 years) participated in laboratory assessment. ADHD symptoms were first evaluated using the Integrated Visual and Auditory Continuous Performance Test (IVA-CPT), followed by EEG recordings during both resting-state and oddball task conditions. Three parent rating scales were also used to evaluate children’s behavioral performance: the ADHD Rating Scale-IV (ADHD RS-IV): Home Version, the Child Behavior Checklist (CBCL), and the Conners’ Parent Rating Scales (CPRS).
Results:
Seventy-one children with valid IVA-CPT results were included in data analysis. The main results revealed a relationship between poorer attention performance and decreased eye-open alpha1 power in the resting state, reduced N2 delta power in the oddball condition, and elevated non-delta band power in the standard condition of the oddball task. Poorer response control performance was associated with increased eye-closed alpha1 power, as well as increased eye-open alpha2 and beta2 power. Stepwise regression analysis showed that the inattention subscale from parental assessments on the RS-IV, combined with P3 alpha power in the standard condition of the oddball task, was the strongest predictor of children’s attention performance.
Conclusion:
The current study identified important neural oscillation features of ADHD symptoms in both the resting state and during an oddball task and offers new insights into multi-metric prediction for ADHD assessment and diagnosis.
AchenbachT. M. (1991). Manual for the child behavior checklist/4-18 and 1991 profile. University of Vermont Department of Psychiatry.
2.
AlbaG.PeredaE.MañasS.MéndezL. D.DuqueM. R.GonzálezA.GonzálezJ. J. (2016). The variability of EEG functional connectivity of young ADHD subjects in different resting states. Clinical Neurophysiology, 127(2), 1321–1330. https://doi.org/10.1016/j.clinph.2015.09.134
3.
AhireN.AwaleR. N.WaghA. (2025). Electroencephalogram (EEG) based prediction of attention deficit hyperactivity disorder (ADHD) using machine learning. Applied Neuropsychology Adult, 32(4), 966–977. https://doi.org/10.1080/23279095.2023.2247702
4.
American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). American Psychiatric Publishing.
5.
ArnoldL. E.HodgkinsP.KahleJ.MadhooM.KewleyG. (2020). Long-term outcomes of ADHD: Academic achievement and performance. Journal of Attention Disorders, 24(1), 73–85. https://doi.org/10.1177/1087054714566076
6.
ArnsM.ConnersC. K.KraemerH. C. (2013). A decade of EEG Theta/Beta ratio research in ADHD: A meta-analysis. Journal of Attention Disorders, 17(5), 374–383. https://doi.org/10.1177/1087054712460087
7.
ArpaiaP.CovinoA.CristaldiL.FrosoloneM.GargiuloL.MancinoF.MantileF.MoccaldiN. (2022). A systematic review on feature extraction in electroencephalography-based diagnostics and therapy in attention deficit hyperactivity disorder. Sensors, 22(13), 4934. https://doi.org/10.3390/s22134934
8.
BalconiM.PozzoliU. (2008). Event-related oscillations (ERO) and event-related potentials (ERP) in emotional face recognition. The International Journal of Neuroscience, 118(10), 1412–1424. https://doi.org/10.1080/00207450601047119
9.
BarryR. J.JohnstoneS. J.ClarkeA. R. (2003). A review of electrophysiology in attention-deficit/hyperactivity disorder: II. Event-related potentials. Clinical Neurophysiology, 114(2), 184–198. https://doi.org/10.1016/s1388-2457(02)00363-2
BaşarE.SchürmannM.DemiralpT.Başar-ErogluC.AdemogluA. (2001). Event-related oscillations are ‘real brain responses’–wavelet analysis and new strategies. International Journal of Psychophysiology, 39(2-3), 91–127. https://doi.org/10.1016/s0167-8760(00)00135-5
13.
BollimuntaA.MoJ.SchroederC. E.DingM. (2011). Neuronal mechanisms and attentional modulation of corticothalamic α oscillations. The Journal of Neuroscienc, 31(13), 4935–4943. https://doi.org/10.1523/JNEUROSCI.5580-10.2011
14.
CaoM.MartinE.LiX. (2023). Machine learning in attention-deficit/hyperactivity disorder: New approaches toward understanding the neural mechanisms. Translational Psychiatry, 13(1), 236. https://doi.org/10.1038/s41398-023-02536-w
15.
ChangL. Y.WangM. Y.TsaiP. S. (2016). Diagnostic accuracy of rating scales for attention-deficit/hyperactivity disorder: A meta-analysis. Pediatrics, 137(3), e20152749. https://doi.org/10.1542/peds.2015-2749
16.
ClarkeA. R.BarryR. J.DupuyF. E.McCarthyR.SelikowitzM.JohnstoneS. J. (2013). Excess beta activity in the EEG of children with attention-deficit/hyperactivity disorder: A disorder of arousal?International Journal of Psychophysiology, 89(3), 314–319. https://doi.org/10.1016/j.ijpsycho.2013.04.009
17.
ClarkeA. R.BarryR. J.JohnstoneS. (2020). Resting state EEG power research in Attention-Deficit/Hyperactivity Disorder: A review update. Clinical Neurophysiology, 131(7), 1463–1479. https://doi.org/10.1016/j.clinph.2020.03.029
18.
ClarkeA. R.BarryR. J.McCarthyR.SelikowitzM. (2001a). Electroencephalogram differences in two subtypes of attention-deficit/hyperactivity disorder. Psychophysiology, 38(2), 212–221.
19.
ClarkeA. R.BarryR. J.McCarthyR.SelikowitzM. (2001b). EEG-defined subtypes of children with attention-deficit/hyperactivity disorder. Clinical Neurophysiology, 112(11), 2098–2105. https://doi.org/10.1016/s1388-2457(01)00668-x
20.
Dallmer-ZerbeI.PoppF.LamA. P.PhilipsenA.HerrmannC. S. (2020). Transcranial alternating current stimulation (tACS) as a Tool to Modulate P300 amplitude in attention deficit hyperactivity disorder (ADHD): Preliminary findings. Brain Topography, 33(2), 191–207. https://doi.org/10.1007/s10548-020-00752-x
21.
DanielsonM. L.BitskoR. H.GhandourR. M.HolbrookJ. R.KoganM. D.BlumbergS. J. (2018). Prevalence of parent-reported ADHD diagnosis and associated treatment among U.S. children and adolescents, 2016. Journal of Clinical Child and Adolescent Psychology, 47(2), 199–212. https://doi.org/10.1080/15374416.2017.1417860
22.
DebS.DhaliwalA. J.RoyM. (2008). The usefulness of Conners’ Rating Scales-Revised in screening for attention deficit hyperactivity disorder in children with intellectual disabilities and borderline intelligence. Journal of Intellectual Disability Research: JIDR, 52(11), 950–965. https://doi.org/10.1111/j.1365-2788.2007.01035.x
23.
DemiralpT.AdemogluA.IstefanopulosY.Başar-ErogluC.BaşarE. (2001). Wavelet analysis of oddball P300. International Journal of Psychophysiology, 39(2–3), 221–227. https://doi.org/10.1016/s0167-8760(00)00143-4
24.
DeSerisyM.HirschE.RoyA. K. (2019). The contribution of sensory sensitivity to emotional lability in children with ADHD symptoms. Evidence-based Practice in Child and Adolescent Mental Health, 4(4), 319–327. https://doi.org/10.1080/23794925.2019.1647122
25.
DeshmukhM.KhemchandaniM.ThakurP. M. (2024). Contributions of brain regions to machine learning-based classifications of attention deficit hyperactivity disorder (ADHD) utilizing EEG signals. Applied neuropsychology. Adult. Advance online publication. https://doi.org/10.1080/23279095.2024.2368655
26.
DoesburgS. M.BedoN.WardL. M. (2016). Top-down alpha oscillatory network interactions during visuospatial attention orienting. NeuroImage, 132, 512–519. https://doi.org/10.1016/j.neuroimage.2016.02.076
27.
DrechslerR.BremS.BrandeisD.GrünblattE.BergerG.WalitzaS. (2020). ADHD: Current concepts and treatments in children and adolescents. Neuropediatrics, 51(5), 315–335. https://doi.org/10.1055/s-0040-1701658
28.
DuPaulG. J.AnastopoulosA. D.PowerT. J.ReidR.McGoeyK. E.IkedaM. J. (1998a). Parent ratings of ADHD symptoms: Factor structure, normative data, and psychometric properties. Journal of Psychopathology and Behavioral Assessment, 20, 83–102.
El-SayedE.LarssonJ. O.PerssonH. E.SantoshP. J.RydeliusP. A. (2003). “Maturational lag” hypothesis of attention deficit hyperactivity disorder: An update. Acta Paediatrica, 92(7), 776–784.
31.
ElyamanyO.LeichtG.HerrmannC. S.MulertC. (2021). Transcranial alternating current stimulation (tACS): From basic mechanisms towards first applications in psychiatry. European Archives of Psychiatry and Clinical Neuroscience, 271(1), 135–156. https://doi.org/10.1007/s00406-020-01209-9
32.
FinkA.GrabnerR. H.NeuperC.NeubauerA. C. (2005). EEG alpha band dissociation with increasing task demands. Brain Research. Cognitive Brain Research, 24(2), 252–259. https://doi.org/10.1016/j.cogbrainres.2005.02.002
33.
FoxeJ. J.SnyderA. C. (2011). The role of alpha-band brain oscillations as a sensory suppression mechanism during selective attention. Frontiers in Psychology, 2, 154. https://doi.org/10.3389/fpsyg.2011.00154
34.
GallowayH.NewmanE.MillerN.YuillC. (2019). Does parent stress predict the quality of life of children with a diagnosis of ADHD? A comparison of parent and child perspectives. Journal of Attention Disorders, 23(5), 435–450. https://doi.org/10.1177/1087054716647479
35.
GeorgeD.MalleryP. (2003). SPSS for Windows step by step: A simple guide and reference 11.0 update (4th ed.). Allyn & Bacon
36.
GomezR.VanceA.WatsonS.StavropoulosV. (2021). ROC analyses of relevant Conners 3-short forms, CBCL, and TRF scales for screening ADHD and ODD. Assessment, 28(1), 73–85. https://doi.org/10.1177/1073191119876023
37.
GoyetteC. H.ConnersC. K.UlrichR. F. (1978). Normative data on revised Conners Parent and Teacher Rating Scales. Journal of Abnormal Child Psychology, 6(2), 221–236. https://doi.org/10.1007/BF00919127
38.
HaleT. S.SmalleyS. L.WalshawP. D.HanadaG.MacionJ.McCrackenJ. T.McGoughJ. J.LooS. K. (2010). Atypical EEG beta asymmetry in adults with ADHD. Neuropsychologia, 48(12), 3532–3539. https://doi.org/10.1016/j.neuropsychologia.2010.08.002
39.
HarpinV.MazzoneL.RaynaudJ. P.KahleJ.HodgkinsP. (2016). Long-term outcomes of ADHD: A systematic review of self-esteem and social function. Journal of Attention Disorders, 20(4), 295–305. https://doi.org/10.1177/1087054713486516
40.
HeinrichH.BuschK.StuderP.ErbeK.MollG. H.KratzO. (2014). EEG spectral analysis of attention in ADHD: Implications for neurofeedback training?Frontiers in Human Neuroscience, 8, 611. https://doi.org/10.3389/fnhum.2014.00611
HerrmannC. S.StrüberD.HelfrichR. F.EngelA. K. (2016). EEG oscillations: From correlation to causality. International Journal of Psychophysiology, 103, 12–21. https://doi.org/10.1016/j.ijpsycho.2015.02.003
43.
HongS. B.DwyerD.KimJ. W.ParkE. J.ShinM. S.KimB. N.YooH. J.ChoI. H.BhangS. Y.HongY. C.PantelisC.ChoS. C. (2014). Subthreshold attention-deficit/hyperactivity disorder is associated with functional impairments across domains: A comprehensive analysis in a large-scale community study. European Child & Adolescent Psychiatry, 23(8), 627–636. https://doi.org/10.1007/s00787-013-0501-z
44.
HughesS. W.CrunelliV. (2005). Thalamic mechanisms of EEG alpha rhythms and their pathological implications. The Neuroscientist, 11(4), 357–372. https://doi.org/10.1177/1073858405277450
45.
JmailN.GavaretM.WendlingF.KachouriA.HamadiG.BadierJ. M.BénarC. G. (2011). A comparison of methods for separation of transient and oscillatory signals in EEG. Journal of Neuroscience Methods, 199(2), 273–289. https://doi.org/10.1016/j.jneumeth.2011.04.028
46.
JohnstoneS. J.BarryR. J.ClarkeA. R. (2013). Ten years on: A follow-up review of ERP research in attention-deficit/hyperactivity disorder. Clinical Neurophysiology, 124(4), 644–657. https://doi.org/10.1016/j.clinph.2012.09.006
47.
KaiserA.AggensteinerP. M.BaumeisterS.HolzN. E.BanaschewskiT.BrandeisD. (2020). Earlier versus later cognitive event-related potentials (ERPs) in attention-deficit/hyperactivity disorder (ADHD): A meta-analysis. Neuroscience and Biobehavioral Reviews, 112, 117–134. https://doi.org/10.1016/j.neubiorev.2020.01.019
48.
KarchS.ThalmeierT.LutzJ.CeroveckiA.Opgen-RheinM.HockB.LeichtG.Hennig-FastK.MeindlT.RiedelM.MulertC.PogarellO. (2010). Neural correlates (ERP/fMRI) of voluntary selection in adult ADHD patients. European Archives of Psychiatry and Clinical Neuroscience, 260(5), 427–440. https://doi.org/10.1007/s00406-009-0089-y
49.
KielingR.RohdeL. A. (2012). ADHD in children and adults: Diagnosis and prognosis. Current Topics in Behavioral Neurosciences, 9, 1–16. https://doi.org/10.1007/7854_2010_115
50.
KlimeschW. (2012). α-band oscillations, attention, and controlled access to stored information. Trends in Cognitive Sciences, 16(12), 606–617. https://doi.org/10.1016/j.tics.2012.10.007
51.
KlimeschW.VogtF.DoppelmayrM. (1999). Interindividual differences in alpha and theta power reflect memory performance. Intelligence, 27(4), 347–362. https://doi.org/10.1016/S0160-2896(99)00027-6
52.
KoehlerS.LauerP.SchreppelT.JacobC.HeineM.Boreatti-HümmerA.FallgatterA. J.HerrmannM. J. (2009). Increased EEG power density in alpha and theta bands in adult ADHD patients. Journal of Neural Transmission, 116(1), 97–104. https://doi.org/10.1007/s00702-008-0157-x
LangenerA. M.KramerA. W.van den BosW.HuizengaH. M. (2022). A shortened version of Raven’s standard progressive matrices for children and adolescents. The British Journal of Developmental Psychology, 40(1), 35–45. https://doi.org/10.1111/bjdp.12381
56.
LarsonM. J.ClaysonP. E.ClawsonA. (2014). Making sense of all the conflict: A theoretical review and critique of conflict-related ERPs. International Journal of Psychophysiology, 93(3), 283–297. https://doi.org/10.1016/j.ijpsycho.2014.06.007
57.
LarssonH.AnckarsaterH.RåstamM.ChangZ.LichtensteinP. (2012). Childhood attention-deficit hyperactivity disorder as an extreme of a continuous trait: A quantitative genetic study of 8,500 twin pairs. Journal of Child Psychology and Psychiatry, and Allied Disciplines, 53(1), 73–80. https://doi.org/10.1111/j.1469-7610.2011.02467.x
LenartowiczA.MazaheriA.JensenO.LooS. K. (2018). Aberrant modulation of brain oscillatory activity and attentional impairment in Attention-Deficit/Hyperactivity Disorder. Biological Psychiatry. Cognitive Neuroscience and Neuroimaging, 3(1), 19–29. https://doi.org/10.1016/j.bpsc.2017.09.009
60.
LeroyA.PetitG.ZarkaD.CebollaA. M.Palmero-SolerE.StrulJ.DanB.VerbanckP.CheronG. (2018). EEG dynamics and neural generators in implicit navigational image processing in adults with ADHD. Neuroscience, 373, 92–105. https://doi.org/10.1016/j.neuroscience.2018.01.022
61.
LiR. (2024). From medical labels to “disorder” reality: The clinical ethnography of childhood attention deficit hyperactivity disorder. She Hui = Society, 44(1), 1–31. https://doi.org/10.15992/j.cnki.31-1123/c.2024.01.001.
62.
MarcusD. K.BarryT. D. (2011). Does attention-deficit/hyperactivity disorder have a dimensional latent structure? A taxometric analysis. Journal of Abnormal Psychology, 120(2), 427–442. https://doi.org/10.1037/a0021405
63.
MartinC. A.PapadopoulosN.ChellewT.RinehartN. J.SciberrasE. (2019). Associations between parenting stress, parent mental health and child sleep problems for children with ADHD and ASD: Systematic review. Research in Developmental Disabilities, 93, Article 103463. https://doi.org/10.1016/j.ridd.2019.103463
64.
McPhersonD. L.SalamatM. T. (2004). Interactions among variables in the P300 response to a continuous performance task in normal and ADHD adults. Journal of the American Academy of Audiology, 15(10), 666–677. https://doi.org/10.3766/jaaa.15.10.2
65.
Moreno-GarcíaI.Delgado-PardoG.Roldán-BlascoC. (2015). Attention and response control in ADHD. Evaluation through integrated visual and auditory continuous performance test. The Spanish Journal of Psychology, 18, E1. https://doi.org/10.1017/sjp.2015.2
66.
NaradM. E.GarnerA. A.PeughJ. L.TammL.AntoniniT. N.KingeryK. M.SimonJ. O.EpsteinJ. N. (2015). Parent-teacher agreement on ADHD symptoms across development. Psychological Assessment, 27(1), 239–248. https://doi.org/10.1037/a0037864
67.
NissimN. R.PhamD. V. H.PoddarT.BluttE.HamiltonR. H. (2023). The impact of gamma transcranial alternating current stimulation (tACS) on cognitive and memory processes in patients with mild cognitive impairment or Alzheimer’s disease: A literature review. Brain Stimulation, 16(3), 748–755. https://doi.org/10.1016/j.brs.2023.04.001
68.
PanX. X.MaH. W.DaiX. M. (2007). Value of integrated visual and auditory continuous performance test in the diagnosis of childhood attention deficit hyperactivity disorder. Chinese Journal of Contemporary Pediatrics, 9(3), 210–212.
69.
RavenJ. (1989). The Raven progressive matrices: A review of national norming studies and ethnic and socioeconomic variation within the United States. Journal of Educational Measurement, 26(1), 1–16. 10.1111/j.1745-3984.1989.tb00314.x
70.
RavenJ. (2000). The Raven’s progressive matrices: Change and stability over culture and time. Cognitive Psychology, 41(1), 1–48. 10.1006/cogp.1999.0735
71.
RubiaK.WestwoodS.AggensteinerP. M.BrandeisD. (2021). Neurotherapeutics for attention deficit/hyperactivity disorder (ADHD): A review. Cells, 10(8), 2156. https://doi.org/10.3390/cells10082156
72.
SamahaJ.BauerP.CimaroliS.PostleB. R. (2015). Top-down control of the phase of alpha-band oscillations as a mechanism for temporal prediction. Proceedings of the National Academy of Sciences of the USA, 112(27), 8439–8444. https://doi.org/10.1073/pnas.1503686112
73.
SandfordJ. A.TurnerA. (2000). Integrated visual and auditory continuous performance test manual. Brain Train.
SayalK.PrasadV.DaleyD.FordT.CoghillD. (2018). ADHD in children and young people: Prevalence, care pathways, and service provision. The Lancet. Psychiatry, 5(2), 175–186. https://doi.org/10.1016/S2215-0366(17)30167-0
76.
Seçen YazıcıM.SerdengeçtiN.DikmenM.KoyuncuZ.SandıkçıB.ArslanB.AcarM.KaraE.TarakçıoğluM. C.KadakM. T. (2023). Evaluation of P300 and spectral resolution in children with attention deficit hyperactivity disorder and specific learning disorder. Psychiatry Research. Neuroimaging, 334, Article 111688. https://doi.org/10.1016/j.pscychresns.2023.111688
77.
ShawP.EckstrandK.SharpW.BlumenthalJ.LerchJ. P.GreensteinD.ClasenL.EvansA.GieddJ.RapoportJ. L. (2007). Attention-deficit/hyperactivity disorder is characterized by a delay in cortical maturation. Proceedings of the National Academy of Sciences of the USA, 104(49), 19649–19654. https://doi.org/10.1073/pnas.0707741104
78.
SlaterJ.JooberR.KoborsyB. L.MitchellS.SahlasE.PalmerC. (2022). Can electroencephalography (EEG) identify ADHD subtypes? A systematic review. Neuroscience and Biobehavioral Reviews, 139, Article 104752. https://doi.org/10.1016/j.neubiorev.2022.104752
79.
Sonuga-BarkeE. J. (2005). Causal models of attention-deficit/hyperactivity disorder: From common simple deficits to multiple developmental pathways. Biological Psychiatry, 57(11), 1231–1238. https://doi.org/10.1016/j.biopsych.2004.09.008
80.
SuY. E.WangH.GengY. G.SunL.DuY. S.FanF.SuL. Y. (2015). Parent ratings of ADHD symptoms in Chinese urban schoolchildren: Assessment with the Chinese ADHD Rating Scale-IV: Home Version. Journal of Attention Disorders, 19(12), 1022–1033. https://doi.org/10.1177/1087054712461177
81.
TahıllıoğluA.BilaçÖ.UysalT.ErcanE. S. (2021). Who predict ADHD with better diagnostic accuracy? Parents or teachers?Nordic Journal of Psychiatry, 75(3), 214–223. https://doi.org/10.1080/08039488.2020.1867634
82.
ÜnsalE.DuygunR.Yemenicilerİ.BingölE.CeranÖ.GüntekinB. (2024). From infancy to childhood: A comprehensive review of event- and task-related brain oscillations. Brain Sciences, 14(8), 837. https://doi.org/10.3390/brainsci14080837
83.
WangC.RajagovindanR.HanS. M.DingM. (2016). Top-down control of visual alpha oscillations: Sources of control signals and their mechanisms of action. Frontiers in Human Neuroscience, 10, 15. https://doi.org/10.3389/fnhum.2016.00015
84.
WangS.LiQ.LuJ.RanH.CheY.FangD.LiangX.SunH.ChenL.PengJ.ShiY.XiaoY. (2023). Treatment rates for mental disorders among children and adolescents: A systematic review and meta-analysis. JAMA Network Open, 6(10), e2338174. https://doi.org/10.1001/jamanetworkopen.2023.38174
85.
WonG. H.ChoiT. Y.KimJ. W. (2020). Application of Attention-Deficit/Hyperactivity disorder diagnostic tools: Strengths and weaknesses of the Korean ADHD Rating Scale and Continuous Performance Test. Neuropsychiatric Disease and Treatment, 16, 2397–2406. https://doi.org/10.2147/NDT.S275796
86.
WuX.TaoM.QiuY. (2024). The diagnostic effect of integrated visual and auditory continuous performance and event-related potentials in ADHD. American Journal of Translational Research, 16(10), 5248–5267. https://doi.org/10.62347/RPJU2655
87.
YordanovaJ.KolevV. (1998). Single-sweep analysis of the theta frequency band during an auditory oddball task. Psychophysiology, 35(1), 116–126.
88.
ZhangZ. (Ed.). (2005). Hand book of behavioral medical scales. Chinese Medical Multimedia Press.
89.
ZhangD. W.JohnstoneS. J.RoodenrysS.LuoX.LiH.WangE.ZhaoQ.SongY.LiuL.QianQ.WangY.SunL. (2018). The role of resting-state EEG localized activation and central nervous system arousal in executive function performance in children with Attention-Deficit/Hyperactivity Disorder. Clinical Neurophysiology, 129(6), 1192–1200. https://doi.org/10.1016/j.clinph.2018.03.009
Supplementary Material
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
