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 Table of Contents  
ORIGINAL ARTICLE
Year : 2022  |  Volume : 23  |  Issue : 2  |  Page : 129-132

Quantitative electroencephalography – A promising biomarker in children with attention deficit/hyperactivity disorder


1 Senior Resident, Department of Psychiatry, Drug De Addiction Centre, Lady Hardinge Medical College, New Delhi, India
2 Assistant Professor, Institute of Human Behaviour and Allied Sciences, New Delhi, India
3 Professor, Department of Neurology, Institute of Human Behaviour and Allied Sciences, New Delhi, India
4 Professor, Department of Psychiatry, Institute of Human Behaviour and Allied Sciences, New Delhi, India

Date of Submission26-Jan-2022
Date of Acceptance09-Aug-2022
Date of Web Publication14-Oct-2022

Correspondence Address:
Dr. Mini Sharma
Department of Psychiatry, Drug De-Addiction Centre, Lady Hardinge Medical College, New Delhi
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/amh.amh_24_22

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  Abstract 


Background: Attention-deficit/hyperactivity disorder (ADHD) is marked by inattention, hyperactivity, and impulsivity. Experimental studies have reported increased theta activity and reduced beta activity on electroencephalography (EEG), although theta wave tends to appear during meditative, drowsy, hypnotic, or sleeping states.
Aims: We aimed to study EEG changes in children with significant severity of ADHD.
Settings and Design: A cross-sectional study was designed for the children with ADHD presenting to the Child and Adolescent Psychiatry Outpatient Department (OPD) of IHBAS.
Methodology: A total of 33 ADHD children in the age group of 5–12 years attending OPD were included in the study after qualifying the inclusion and exclusion criteria for the study.
DSM-5 criteria were used to make the diagnosis of ADHD and severity was assessed using Conners' Rating Scale-Revised Parent short version. The children with more than 50% score on the Conners Scale were included in the study. The quantification of the recorded EEG was done using Fast Fourier Transformation by New Natus NeuroWorks computer software.
Statistical Analysis: The data were analyzed using SPSS version 23.0.
Results: Around 3/4th of participants in the study showed elevated theta: beta ratio results on qEEG.
Conclusions: Although ADHD is marked by inattention, hyperactivity, and impulsivity, children with ADHD showed marked elevated theta: beta ratio indicating raised slow-wave changes in cortical activity, thus concluding quantitative EEG as a promising biomarker in children with ADHD.

Keywords: ADHD, Biomarker, qEEG


How to cite this article:
Sharma M, Kumar M, Kushwaha S, Kumar D. Quantitative electroencephalography – A promising biomarker in children with attention deficit/hyperactivity disorder. Arch Ment Health 2022;23:129-32

How to cite this URL:
Sharma M, Kumar M, Kushwaha S, Kumar D. Quantitative electroencephalography – A promising biomarker in children with attention deficit/hyperactivity disorder. Arch Ment Health [serial online] 2022 [cited 2023 Jan 29];23:129-32. Available from: https://www.amhonline.org/text.asp?2022/23/2/129/358622




  Introduction Top


Attention-deficit/hyperactivity disorder (ADHD) is characterized by developmentally inappropriate, a persistent problem in attention and/or excessive motor restlessness and/or impulsivity that significantly interfere with functioning.[1] The clinical features of ADHD in the domain of cognition include short attention span, distractibility, and inability to foresee the consequences of one's action.[2] Whereas, the behavioral domain includes hyperactivity, motor restlessness and impulsivity in cases of ADHD.

Electroencephalography (EEG) research in the past 40 years has been attempted to characterize and quantify the neurophysiology of ADHD, most consistently associating it with increased frontocentral theta band activity and increased theta-to-beta (θ/β) power ratio during rest.

In the 1970s, Satterfield et al. conducted a series of EEG studies of children with ADHD and found EEG abnormalities, including excess slow-wave activity and increased epileptiform (spike and wave) activity.[3] Barry et al. concluded that elevated relative theta power and reduced relative alpha and beta, together with elevated theta/alpha and theta/beta power ratios, are most reliably associated with ADHD.[4] The presence of varied worldwide results and lacking Indian data on EEG changes in children with ADHD formed the basis of this study.


  Methodology Top


The children with ADHD presenting to the Child and Adolescent Psychiatry Outpatient Department (OPD) of our neuropsychiatric tertiary institute were approached after diagnosis was confirmed using DSM-5 criteria and informed consent from parents and assent from children. After application of inclusion criteria, i.e., children between the age group of 5 and 12 years and of either gender having more than 50% score on Conners' Rating Scale[5] were considered. Children with a history of epilepsy and institutionalized children were excluded from the study. Around 100 children with ADHD were screened and a total of 33 children with ADHD were recruited for the study after application of inclusion and exclusion criteria.

For each case, a spectral EEG was done in eyes-closed resting state using 21 channel leads for 45 min and analysis for quantitative EEG (qEEG) was done using Fast Fourier Transformation (FFT) software. The EEG recordings were quantified for calculation of theta: beta ratio using FFT algorithm-based New Natus NeuroWorks computer software.[6],[7] The theta-beta power ratio of >5.00:1 was taken as the cutoff for dysfunction in our study as there is a precedence of similar cutoff in a study done by Ogrim et al. in 2012.[8]

The collected data were further analyzed for the study outcome.

Statistical analysis

Data were entered in the data-based computer program and were analyzed using the Statistical Package for the SPSS Statistics for Windows, version 23. 0 (SPSS Inc., Chicago, Ill., USA). The clinical profile was analyzed by descriptive statistics. For correlation analysis, Pearson's correlation statistics were used.


  Results Top


In the study, the sample of 33 children which included the children in the age group of 5–12 years had a mean age of presentation which was 8.61 (standard deviation [S.D.] = 2.16).

The severity of ADHD was assessed using the Conners' Rating Scale Revised (CRS R) (Parent version) and a mean value of 54.52 (S.D. =6.00) was found [Table 1].
Table 1: The quantitative electroencephalography theta:beta ratio in children with attention-deficit/hyperactivity disorder

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The quantification of the EEG theta: beta ratio showed a mean value of 11.16:1 (S.D. =11.57) which was more than 5.00 and suggestive of increased theta: beta ratio as studied for ADHD children [Table 1], [Figure 1]. In around 60.60% of the cases, increased theta: beta power ratio was seen.
Figure 1: Theta: beta ratio on qEEG in children with ADHD. qEEG: Quantitative electroencephalography, ADHD: Attention-deficit/hyperactivity disorder

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This was contrary to the findings in female cases where a strong value of correlation was noted [Table 2]. Though the significance value was weak to moderate, this could be attributed to the small sample size.
Table 2: The correlation between quantitative electroencephalography theta:beta ratio and severity of attention-deficit/hyperactivity disorder in children with attention-deficit/hyperactivity disorder

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  Discussion Top


The present study was carried out at a tertiary neuropsychiatry hospital and an academic institute in Delhi. It was a cross-sectional study wherein children were taken from Child and Adolescent Psychiatric OPD over a period of 9 months. DSM-5 criteria were applied to objectively validate the diagnosis and assessment of the clients taken for the study. A period sample of 100 children was initially taken, and after the application of inclusion and exclusion criteria, 33 children were included in the study. Children who had other comorbidities such as epilepsy and other psychiatric illnesses that could confound the process of assessment and results were excluded from the study.

The tools used in the study for diagnosis and assessment were already validated and used in various internationally published articles. DSM-5 criteria were used to make the diagnosis of ADHD, and CRS-R Parent short version[5] was used to assess the severity of the ADHD. The Conners score range is from 0 to 81. In the present study, children with score ≥40 (50% score on Conners Scale) were recruited.

In around 60% of the cases, increased theta: beta power ratio (>5.00) was seen. These results align with findings objectified in various studies conducted worldwide.

Since the ages, it is seen that EEG abnormalities are consistently found in the children with ADHD which were initially reported by Satterfield et al.[3] in the 1970s. As the understanding and investigations had progressed, more and more findings are indicative of functional brain damage in children with ADHD.

A multi- centre study (1999) by Monastra et al., found that the theta/beta ratio could discriminate between ADHD patients and normal controls with a sensitivity of 86%–90% and specificity from 94% to 98%.[9]

In a study by Rabiner, the theta/beta ratios of 209 subjects with ADHD were compared with those of a mixed clinical group with oppositional defiant disorder, mood disorder, or anxiety disorder without comorbid ADHD. An increased theta/beta ratio was found in 78% of ADHD subjects and was not present in 97% of the other subjects.[10]

In 2002, Bresnahan and Barry reported that elevated theta persisted into adolescence and adulthood in patients with ADHD; also provided diagnostic power for discriminating adults with ADHD from a group of patients referred for possible ADHD who failed to meet diagnostic criteria.[11]

In 2003, Barry et al. concluded that elevated relative theta power and reduced relative alpha and beta, together with elevated theta/alpha and theta/beta power ratios, are most reliably associated with ADHD.[4]

Snyder and Hall conducted a meta-analysis that reflected that the theta/beta ratio has much higher predictive power than rating scales do, for separating ADHD and clinical controls.[12]

Loo and Makeig 2012 concludes that increase in both theta band activity and in the theta/beta power ratio are two of the most reliable EEG findings in ADHD.[13]

In 2014, Lenartowicz and Loo found that the relatively high (>90%) sensitivities and specificities reported using EEG far exceed the most advanced classification attempts using anatomical and functional MRI data.[14]

The difference in the frontal lobe functioning has been studied for males and females in the ADHD population. In girls with ADHD, the functional and psychosocial impairment is well established by studies done by Hinshaw SP et al, Staller et al, Biederman et al and Akins CR et al.[15],[16],[17],[18] This could be inferred from the changes in EEG over frontocentral areas as noted in our study as well.

Hence, a literature review of more than 50 years consistently reveals increased theta activity in children with ADHD and our study with advanced qEEG also shows a similar finding of raised theta: beta ratio. Even the present study shows elevated theta: beta ratio in children with significant clinical severity of ADHD, thus suggesting theta: beta ratio to be a clinically significant biomarker.


  Conclusion Top


ADHD is characterized by a developmentally inappropriate, persistent problem in attention and/or recessive motor restlessness and/or impulsivity that significantly interfere with functioning and presence of increased frontocentral theta band activity and increased theta-to-beta power ratio during rest compared to non-ADHD controls.

Even 50 years later to the worldwide available studies and with the application of stringent criteria and newer modality for qEEG in our study, the results were conclusive to state that ADHD is a slow-wave disease. Thus, qEEG could be considered a promising biological marker for the diagnosis of ADHD. Furthermore, there is a need to reconsider the screening and treatment for patients with ADHD.

Strengths and limitations

A homogenized sample of 5–12-year-old children was taken utilizing the tools for assessment of the severity of ADHD having a good psychometric property. The tools used in the study were all validated ones, both in Western and Indian context. Furthermore, stringent inclusion and exclusion criteria were applied. As the children with severity CRS-R score of more than 50% severity score (>40) was used, then less severe cases which could have confounded the results were excluded from the study. The study had a limitation that it did not include treatment naïve cases. Some children had prior exposure to atomoxetine and methylphenidate.

Future direction

In cases of ADHD, the qEEG can be considered as a possible biological marker for diagnostic utility. The use of theta: beta ratio for knowing the difference of appearance and functional significance in the EEG changes in ADHD population could be evaluated in future over a larger sample and in a multicenter study. It can also be considered for treatment as neurofeedback therapy for ADHD. Furthermore, newer treatment modalities can be tried in the treatment of ADHD.

Ethical consideration

An ethical clearance was taken before conducting the study, reference no.: REC/IHBAS/2017/01).

Acknowledgment

We are thankful to the participants and caregivers for their participation and support.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders. 5th ed. DSM-5. Washington: American Psychiatric Association; 2013.  Back to cited text no. 1
    
2.
World Health Organization. The ICD-10 classification of mental and behavioural disorders: clinical descriptions and diagnostic guidelines. World Health Organization; 1992.  Back to cited text no. 2
    
3.
Satterfield JH, Cantwell DP, Satterfield BT. Pathophysiology of the hyperactive child syndrome. Arch Gen Psychiatry 1974;31:839-44.  Back to cited text no. 3
    
4.
Barry RJ, Clarke AR, Johnstone SJ. A review of electrophysiology in attention-deficit/hyperactivity disorder: I. Qualitative and quantitative electroencephalography. Clin Neurophysiol 2003;114:171-83.  Back to cited text no. 4
    
5.
Conners CK. Rating scales in attention-deficit/hyperactivity disorder: use in assessment and treatment monitoring. Journal of Clinical Psychiatry. 1998;59:24-30.  Back to cited text no. 5
    
6.
Cooley JW, Tukey JW. An algorithm for the machine calculation of complex Fourier series. Math Comput 1965;19:297-301.  Back to cited text no. 6
    
7.
Dumermuth G, Flühler H. Some modern aspects in numerical spectrum analysis of multichannel electroencephalographic data. Med Biol Eng 1967;5:319-31.  Back to cited text no. 7
    
8.
Ogrim G, Kropotov J, Hestad K. The quantitative EEG theta/beta ratio in attention deficit/hyperactivity disorder and normal controls: Sensitivity, specificity, and behavioral correlates. Psychiatry Res 2012;198:482-8.  Back to cited text no. 8
    
9.
Monastra VJ, Lubar JF, Linden M, VanDeusen P, Green G, Wing W, et al. Assessing attention deficit hyperactivity disorder via quantitative electroencephalography: An initial validation study. Neuropsychology 1999;13:424-33.  Back to cited text no. 9
    
10.
Rabiner DD. QEEG scan results differentiate ADHD from other psychiatric disorders. Attention Research Update. 2001;42.  Back to cited text no. 10
    
11.
Bresnahan SM, Barry RJ. Specificity of quantitative EEG analysis in adults with attention deficit hyperactivity disorder. Psychiatry Res 2002;112:133-44.  Back to cited text no. 11
    
12.
Snyder SM, Hall JR. A meta-analysis of quantitative EEG power associated with attention-deficit hyperactivity disorder. J Clin Neurophysiol 2006;23:440-55.  Back to cited text no. 12
    
13.
Loo SK, Makeig S. Clinical utility of EEG in attention-deficit/hyperactivity disorder: A research update. Neurotherapeutics 2012;9:569-87.  Back to cited text no. 13
    
14.
Lenartowicz A, Loo SK. Use of EEG to diagnose ADHD. Curr Psychiatry Rep 2014;16:498.  Back to cited text no. 14
    
15.
Hinshaw SP, Carte ET, Fan C, Jassy JS, Owens EB. Neuropsychological functioning of girls with attention-deficit/hyperactivity disorder followed prospectively into adolescence: Evidence for continuing deficits? Neuropsychology 2007;21:263-73.  Back to cited text no. 15
    
16.
Greene RW, Biederman J, Faraone SV, Monuteaux MC, Mick E, Dupre EP, et al. Social impairment in girls with ADHD: patterns, gender comparisons, and correlates. Journal of the American Academy of Child & Adolescent Psychiatry. 2001;40:704-10.  Back to cited text no. 16
    
17.
Staller J, Faraone SV. Attention-deficit hyperactivity disorder in girls. CNS drugs. 2006;20:107-23.   Back to cited text no. 17
    
18.
Akins CR, Krakowiak P, Angkustsiri K, Hertz-Picciotto I, Hansen RL. Utilization patterns of conventional and complementary/alternative treatments in children with autism spectrum disorders and developmental disabilities in a population-based study. Journal of developmental and behavioral pediatrics: JDBP. 2014;35:1.  Back to cited text no. 18
    


    Figures

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    Tables

  [Table 1], [Table 2]



 

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