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 Table of Contents  
ORIGINAL ARTICLE
Year : 2015  |  Volume : 52  |  Issue : 4  |  Page : 270-273

Quantitative electroencephalographic changes in attention deficit hyperactivity disorder children


1 Clinical Neurophysiology Unit, Faculty of Medicine, Cairo University, Cairo, Egypt
2 Department of Human Genetics, National Research Center, Cairo, Egypt
3 Department of Psychiatry, Faculty of Medicine, Cairo University, Cairo, Egypt

Date of Submission31-May-2015
Date of Acceptance18-Jul-2015
Date of Web Publication27-Nov-2015

Correspondence Address:
Basma B El Sayed
Fourth Mahmoud Samy El Baroudy Street, Haram, 12111 Giza
Egypt
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/1110-1083.170660

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  Abstract 

Background
The electroencephalogram (EEG) has long been used to pick up and analyze the electrical activity of the outermost layer of the brain. Attention deficit hyperactivity disorder (ADHD) patients revealed increased power in the lower frequency bands (δ and θ power) and a raised θ/β ratio.
Objective
The aim of this study was to detect the quantitative EEG changes in children with ADHD compared with normal children.
Patients and methods
The sampled group consisted of 45 children suffering from ADHD and represented the patient group, and 45 normal children represented the control group. EEG was recorded under resting conditions for all participants. Data from frontal areas were digitally processed and analyzed to calculate the four frequency bands' power (β, α, θ, and δ) and then θ/β ratio was computed. For the patient group, the Wechsler Intelligence Scale for Children was applied and parents of these patients filled out the Arabic version of Conners' Parent Rating Scale-revised-long version.
Results
The patient group showed significantly higher θ/β ratio in frontal areas compared with the control group (P < 0.05). There was a significant negative relation between age and θ/β ratios and a significant negative relation between age and Conners' hyperactivity subscale (P < 0.05). There was a significant positive relation between Conners' hyperactivity subscale and mean θ/β ratio (P < 0.05).
Conclusion
Quantitative EEG markers - namely, the θ/β ratio - could play a role in the understanding and identification of ADHD.

Keywords: attention deficit hyperactivity disorder, quantitative electroencephalography, θ/β ratio


How to cite this article:
Abdel Kader AA, Mohamed NA, Amin OR, El Sayed BB, Halawa IF. Quantitative electroencephalographic changes in attention deficit hyperactivity disorder children. Egypt J Neurol Psychiatry Neurosurg 2015;52:270-3

How to cite this URL:
Abdel Kader AA, Mohamed NA, Amin OR, El Sayed BB, Halawa IF. Quantitative electroencephalographic changes in attention deficit hyperactivity disorder children. Egypt J Neurol Psychiatry Neurosurg [serial online] 2015 [cited 2017 Jun 23];52:270-3. Available from: http://www.ejnpn.eg.net/text.asp?2015/52/4/270/170660


  Introduction Top


Attention deficit hyperactivity disorder (ADHD) is a long-standing condition, with symptoms continuing into adolescence and later life [1] . It involves a group of symptoms such as hyperactivity, impulsivity, and inattention. The existence of these symptoms considerably affects normal cognitive and behavioral functioning of the person. Children and teenagers with ADHD are at risk for later lawbreaking problems and some symptoms may persist throughout life. In the last 30 years, considerable changes have happened in the theories that tried to look into the development of ADHD [2] .

A more sophisticated form of electroencephalogram (EEG) has been established, called quantitative electroencephalogram (qEEG), in which the brain activity is transformed into a digital form to study the background activity. These signals are then processed with advanced arithmetical techniques to disclose patterns unnoticed by human eye. The findings are then showed in topographical diagrams demonstrating electrical activity of the brain known as 'brain maps' [3] .

The aim of this study was to detect the qEEG changes in children with ADHD.


  Patients and methods Top


This study included 45 male patients having clinical symptoms and signs of ADHD, according to the Diagnostic and Statistical Manual of Mental Disorders, 4th ed., text revision (DSM-IV-TR) criteria. Their ages ranged from 8 to 12 years, and they were referred from the Outpatient Clinic of Child Psychiatry in Center of Social and Preventive Medicine (Abo-El Reesh Hospital, Cairo University Hospitals, Cairo, Egypt) and Special Needs Clinic in National Research Centre (Cairo, Egypt). Forty-five normal sex-matched and age-matched children from other departments of pediatric hospital, suffering from gastrointestinal infections, were selected as controls.

Exclusion criteria

  1. Being ADHD on medication.
  2. Having any condition that may delay mental development.
  3. Being ADHD with intelligence quotient less than 80.


The study was approved by the research committee at Cairo University. The parents or caregivers of all patients and controls involved in the study signed written informed consent.

Evaluation of patients

  1. Detailed history taking and full general examination.
  2. Psychiatric assessment for the diagnosis of ADHD according to DSM-IV-TR and for exclusion of other psychiatric comorbidities in the patient group and for exclusion of psychiatric disorders in the control.
  3. Conners' Parent Rating Scale-revised-long version [4] to assess symptom severity. Parents were asked to respond to 80 questions about their child's behavior in the last month. The answers were then scored according to a preset scale as follows: 0 = not true or seldom true; 1 = just a little true, occasionally; 2 = often true, quite a bit; and 3 = very often true, very much true.


Items are clustered into subscales of symptoms:

  1. Hyperactivity;
  2. Opposition;
  3. Cognitive/inattention;
  4. Anxiety-shyness;
  5. Perfectionism;
  6. Psychosomatic;
  7. Social problems;
  8. ADHD index;
  9. Restless-impulsive index;
  10. Conners' Global Index;
  11. Emotional liability index,
  12. Total screening test for hyperactivity index;
  13. DSM-IV symptoms; and
  14. DSM-IV total score.


  1. The Wechsler Intelligence Scale for Children is a psychometric test utilized to assess cognitive ability degree (thinking and reasoning) and to evaluate innate intelligence. It is divided into two major areas to assess different types of intelligence, verbal skills and performance skills. A child's performance was evaluated on the basis of age, because as a child grows older their abilities increase as well [5] . Scoring depends on further sophisticated territories of cognitive performance: verbal comprehension, perceptual organization, working memory, and processing speed. The Arabic version translated by Meleka and Ismail [6] was used.
  2. Quantitative electroencephalography (recording technique): Studies were performed in the Special Needs Unit, National Research Center. EEG was recorded using a 32-channel EEG computer operated technique via E-series machine manufactured by Compumedics, Australia.


Twenty-one silver chloride electrodes were placed on the scalp following the international 10-20 system.

The signals inputted were referred to linked ears electrode. Filters used were 0.5 and 50 Hz, and sampling rate was 250 Hz. Impedance was 5 kΩ.

We processed the resulting data using WinEEG software, developed by Nova Tech EEG, Inc. Arizona, USA, after using common reference montage. Brain activities with large amplitude (>100 μV) and/or overly fast (20-35 Hz) and/or slow (0-1 Hz) were automatically denoted and omitted from further analysis. Every record was manually reviewed to confirm elimination of the artifacts. Data from frontal areas were digitally processed and analyzed to calculate four frequency bands' power (β, α, θ, and δ) and then θ/β ratio was computed [7] .

Statistical analysis

Continuous variables were summarized using mean and SD. Comparison of quantitative variables was tested using Student's 't' test. Correlation among different variables was tested using Pearson's equation. A P value greater than 0.05 was considered significant. All statistical computations were performed using statistical package for the social sciences (SPSS, version 18 for Microsoft Windows 7; SPSS Inc., Chicago, Illinois, USA).


  Results Top


The age of patients and controls ranged from 8 to 12 years. The mean age of patients was 9.67 ± 1.12 years and the mean age of controls was 9.9 ± 1.17 years, with no statistically significant difference (P > 0.05).

As regards the severity of symptoms in the sampled ADHD group measured using the Conners Parent Rating Scale, the mean values were as follows: 81.07 ± 6.26 for hyperactivity, 80.73 ± 11.84 for social problems, 78.6 ± 6.05 for opposition, 78.47 ± 6.84 for inattention, 71.53 ± 13.03 for psychosomatic, 67.4 ± 5.95 for perfectionism, and 66.93 ± 10.67 for anxiety-shyness.

Among the Conners indices, the restless-impulsive index was the highest index with a mean of 88.2 ± 2.56. The mean of emotional liability index was 81.8 ± 7.09. The mean of ADHD index was 73.27 ± 4.95 and the mean total score was 86.47 ± 4.55.

As regards the Wechsler Intelligence Scale, the mean of total intelligence quotient score in the patient group was 92.67 ± 3.65, whereas in the control group it was 103.13 ± 4.09, with a significant difference between the two groups (P < 0.001).

As for qEEG results, the control group showed significantly lower θ/β ratio in frontal areas with a mean of 3.39 ± 0.34 compared with a mean of 4.19 ± 0.58 in frontal areas in the patient group (P < 0.0001).

In the patient group, there was a significant negative correlation between age and mean θ/β ratio in frontal areas (r = −0.7205, P < 0.001).

Age was significantly correlated with emotional index (r = −0.3098, P = 0.0383), hyperactivity (r = −0.5446, P = 0.0001), total DSM-IV scores (r = −0.3604, P = 0.015), and ADHD index (r = 0.2999, P = 0.0453).

As regards frontal θ/β ratio, there was a significant negative correlation between it and Wechsler Intelligence Scale score (r = −0.3572, P = 0.016) and inattentive DSM-IV score (r = −0.3104, P = 0.038).

On correlating frontal θ/β ratio and Conners rating scale results, there was a significant positive correlation with hyperactivity subscale (r = 0.7026, P < 0.001).

There was a significant positive correlation between frontal θ/β ratio and anxiety, social problems, psychosomatic subscales, and emotional index (r = 0.3952, P = 0.0072; r = 0.3801, P = 0.01; r = 0.3043, P = 0.0421; and r = 0.3416, P = 0.0216, respectively).

There was a significant positive correlation between frontal θ/β ratio and hyperactivity (r = 0.4538, P = 0.0017) and total DSM-IV scores (r = 0.2983, P = 0.0465) (Tables 1 and 2).


  Discussion Top


We aimed at detecting θ/β ratio in frontal areas of the brain to improve the specificity and sensitivity of the EEG record in diagnosing ADHD.

Our study established that the θ/β ratio of ADHD patients was significantly greater than that in the control group. It was suggested that almost all ADHD patients show rather constant EEG changes in activity of the brain, particularly with respect to greater quantity of frontocentral θ activity [8] .

In addition, a meta-analysis, which examined nine studies with a total of 1498 individuals, noticed an increase of 32% in θ in ADHD patients compared with controls [9] .

Moreover, Clarke et al. [10] investigated the electrical power of the brain, disclosing that θ power is higher, whereas α and β powers are reduced considerably in ADHD patients than in controls.

Our study revealed a significant negative correlation between age and θ/β ratio; this is in accordance with that reported in previous literature, in which a correlation of excess θ band in ADHD was discovered throughout life, and it was reported that both teenagers and grownups with ADHD display excess frontocentral θ [11].

There have been many scientific theories that tried to understand the relationship between increased θ power and the presence of ADHD. Our results can be inferred to reveal tardy functional maturation of the brain in ADHD patients. As one theory suggested, increased θ activity might indicate delayed maturation. Slowing of the background activity and θ wave presence during wakefulness is accepted until the age of 3 years, after which α waves must appear in the background activity, and the persistence of θ waves in the background during wakefulness until the age of 8 years is considered abnormal. This is in accordance with maturational-lag model of ADHD, which clarified that it is associated with delayed development of the brain of the affected individuals [12] .

In addition, the explanation that elevated θ activity in ADHD patients represents reduced cortical activity and is related to hypoarousal of the brain has acquired significant support, as it clarified the apparently paradoxical effect of stimulants in the management of ADHD [13] .

Accordingly, the ADHD patients cannot uphold a proper level of attention, prompting conduct as inattention and hyperactivity [9] .


  Conclusion Top


qEEG markers - namely, the θ/β ratio - appears to be a trustworthy measure for differentiating between ADHD patients and controls. The θ/β ratio could have a part in the understanding or even diagnosis of ADHD. Aiming at identifying specific patterns of these findings can help develop a credible objective diagnostic test for ADHD.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.

 
  References Top

1.
Hechtman L. Long-term treatment of children and adolescents with attention-deficit/hyperactivity disorder (ADHD). Curr Psychiatry Rep 2006; 8 :398-408.  Back to cited text no. 1
    
2.
Weiss G, Hechtman LT. Hyperactive children grown up: empirical findings and theoretical considerations. New York: Guilford Press; 1986.  Back to cited text no. 2
    
3.
Hughes J, John E. Conventional and quantitative electroencephalography in psychiatry. J Neuropsychiatry Clin Neurosci 1999; 11 :190-208.  Back to cited text no. 3
    
4.
Conners K, Sitarenios G, Parker J, Epstein J. The revised Conners' Parent Rating Scale (CPRS-R): factor structure, reliability, and criterion validity. J Abnorm Child Psychol 1998; 26 :257-268.  Back to cited text no. 4
    
5.
Wechsler D. Wechsler Preschool and Primary Scale of Intelligence. New York: Psychological Corporation; 1990.  Back to cited text no. 5
    
6.
Meleka L, Ismail M. Translation of: Wechsler Intelligence Scale for Children. Cairo: El-Nahda Library; 1999.  Back to cited text no. 6
    
7.
Vigario R, Oja E. BSS and ICA in neuroinformatics: from current practices to open challenges. IEEE Rev Biomed Eng 2008; 1 :50-61.  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 :482-488.  Back to cited text no. 8
    
9.
Snyder S, Hall J. A meta-analysis of quantitative EEG power associated with attention-deficit hyperactivity disorder. J Clin Neurophysiol 2006; 23 :440-455.  Back to cited text no. 9
    
10.
Clarke A, Barry R, McCarthy R, Selikowitz M. EEG analysis in attention-deficit/hyperactivity disorder: a comparative study of two subtypes. Psychiatry Res 1998; 81 :19-29.  Back to cited text no. 10
    
11.
Bresnahan S, Barry R. Specificity of quantitative EEG analysis in adults with attention deficit hyperactivity disorder. Psychiatry Res 2002; 112 : 133-144.  Back to cited text no. 11
    
12.
Smartwood J, Swartwood M, Lubar J, Timmermann D. EEG differences in AD/HD-combined type during baseline and cognitive tasks. Pediatr Neurol 2003; 28 :199-204.  Back to cited text no. 12
    
13.
Clarke A, Barry R, McCarthy R, Selikowitz M. Excess beta activity in children with attention-deficit/hyperactivity disorder: an atypical electrophysiological group. Psychiatry Res 2001; 103:205-218.  Back to cited text no. 13
    




 

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Abstract
Introduction
Patients and methods
Results
Discussion
Conclusion
References

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