INTRODUCTION

Attention – Deficit / Hyperactivity Disorder (ADHD) is an enduring mental disorder, characterized by persistent symptoms of inattention alone or in combination with hyperactivity and impulsivity.¹ ADHD has become one of the most commonly diagnosed disorders of childhood, with prevalence rates ranging from 2 to 29%.² Children with ADHD have a central nervous system dysfunction, characterized primarily as either a maturational lag or cortical under-arousal.³

Quantitative Electroencephalography (QEEG) is a much advanced form of electroencephalography (EEG). In this type of EEG, multichannels recording of eyes-closed (resting or "background" EEG) are visually edited and a sample of artifact-free data (usually 1 to 2 minutes) is analyzed to quantify the power at each frequency band of the EEG averaged across the entire sample, known as the power spectrum.⁴

This study investigated the QEEG changes that accompany children with ADHD compared to control subjects in order to provide an easy and applicable alternative diagnostic tool when compared to other available functional brain imaging modalities.

SUBJECTS AND METHODS

Twenty two (22) ADHD Children, attended the outpatient clinic of Neuropsychiatry department, Suez Canal University Hospital between June 2008 and June 2009 were included in the study. Their age ranged from 6-10 years (Mean: 8.6±1.3). They were 14 male and 8 female. Those children fulfilled the criteria for diagnosis of ADHD based on Diagnostic and Statistical Manual of mental disorders (DSM IV).¹ Exclusion criteria were; Children with history of a problematic prenatal, perinatal or neonatal period, Wechsler Intelligence Scale for Children⁵ score less than 85, history of head injury with cerebral symptoms, CNS infection or convulsions. A case-control study was designed with 22 control healthy children matched the patients group according to the age (Range: 6-11, Mean: 9.2±1.6 years) and sex (12 male and 10 female).

All children went through complete medical evaluation and CT brain was done for all ADHD children.

QEEG was done for all ADHD and control children. Electrical signals were recorded with SCAN LT^TM medical system device (Neuro Scan Medical System, Neurosoft, Inc., 2001). The traces were kept on the computer set for later off-line analysis. The recording was done in a sound- attenuated chamber. During recording sessions, subjects sat, semi-reclined with eyes closed and neck and arms supported for at least 15 minutes EEG acquisition period. To keep vigilance state at a constant level, subjects were verbally alerted at 2 minute intervals and any time when there were signs of drowsiness. Nineteen electrodes were positioned according to the 10/20 international system. Unipolar montage was used.⁶

The power spectrum was analyzed for every child from an artifact-free data using the fast Fourier transform (1 to 2 minutes of EEG recording during rest with eyes closed).⁴ The spectrum was divided into the following frequency bands: Delta (δ):  0.5 - > 4Hz, Theta (θ):  4 - > 8 Hz, Alpha 1 (α1):  8 - > 11Hz, Alpha 2 (α2):  11- > 13 Hz, Beta 1(β1):  13 - > 25 Hz, Beta 2 (β2):  25 - 35Hz. ⁷

The power spectrum for each band was calculated and the following approaches⁸ were used for quantitative analysis of the EEG results for each patient and control:

The peak power frequency (PPF): The frequency in spectrum that displays the highest power in particular epoch in particular site (e.g. PPF at FP2 Electrode is theta).

Relative power (RP): is the ratio of power in band divided by the total power in all bands combined in particular epoch (e.g. RP of theta band is 40.44%) (Figure 1).

Figure 1. Analysis of Quantitative EEG data: At the top: A window used for analyzing the relative power for each frequency band (Relative power for theta band is 40.44%). At the bottom: A window used for analyzing the peak power frequency in an electrode (Peak power frequency at FP2 electrode is theta frequency band).

Statistical Analysis

Data was collected, coded, entered and analyzed using Statistical Package of Social Sciences (SPSS version 10). Patients and controls were distributed according to their peak power frequency at each electrode and their percentage was determined. Relative power of each frequency band was determined for each patient and control. The mean and Standard deviation of relative power were determined for each group. P value was used to test difference of significance. It was set at <0.05 for significant value and <0.01 for highly significant value.⁹

RESULTS

In the control children, the peak power frequency bands predominantly were alpha₁ band (Range 36.4-91%), followed by theta (Range 4.5-45.5%) and alpha₂ bands (Range 0-27.3%) in all electrodes. In contrast; in the ADHD group, theta band predominates (Range 50%-95.5%), followed by alpha₁ (Range 4.5-50%) and delta bands (Range 4.5-9.5%) in all electrodes.

Theta band frequency is significantly more frequent and alpha₁ band is significantly less frequent among ADHD group in comparison to control group in: Frontal (Table 1), Frontopolar (Table 2), Central (Table 3), Parietal (Table 4), Temporal (Table 5), and Occipital (Table 6) electrodes (P<0.05), except T₃ electrode (P>0.05).

The means of relative power of theta and delta bands are significantly higher in ADHD patients (P<0.01), while the means of relative power of alpha₁, alpha₂ and beta₁ are significantly lower in ADHD patients (P<0.01) in comparison to control children (Table 7).

Table 1. Distribution of Attention Deficit-Hyperactivity/Disorder (ADHD) patients according to their peak power frequency bands in frontal electrodes in comparison to control group.

Chi square test

*statistically significant at p-value < 0.01                               

Table 2. Distribution of Attention Deficit-Hyperactivity/Disorder (ADHD) patients according to their peak power frequency bands in frontopolar electrodes in comparison to control group.

*significant at p <0.01

Table 3. Distribution of Attention Deficit-Hyperactivity/Disorder (ADHD) patients according to their peak power frequency bands in central electrodes in comparison to control group.

Chi square test

* Significant at p< 0.05 ** Significant at p-value p< 0.01                       

Table 4. Distribution of Attention Deficit-Hyperactivity/Disorder patients according to their peak power frequency bands in parietal electrodes in comparison to control group.

Chi square test

* Significant at p< 0.05 ** Significant at p-value p< 0.01                       

Table 5. Distribution of Attention Deficit-Hyperactivity/Disorder (ADHD) patients according to their peak power frequency bands in temporal electrodes in comparison to control group.

Chi square test

* Significant at p< 0.05 ** Significant at p-value p< 0.01                       

Table 6. Distribution of Attention Deficit-Hyperactivity/Disorder (ADHD) patients according to their peak power frequency bands in Occipital electrodes in comparison to control group.

Chi square test

* Significant at p< 0.05 ** Significant at p-value p< 0.01                       

Table 7. Means and Standard Deviations of the relative power of all frequency bands in the control and Attention Deficit-Hyperactivity/ Disorder (ADHD) Groups.

Student’s t- test

* Significant at p< 0.05   NS non-significant

DISCUSSION

Electroencephalographic studies are unique in providing an electrophysiological data about the brain’s activity. EEG could be considered as the only clinical diagnostic instrument directly reflecting cortical neuronal function.¹⁰ Quantitative electroencephalogram remains a valuable research tool but, as yet, an unproven diagnostic tool for ADHD. Thus, this study focused on identifying the quantitative electroencephalographic changes in children with attention-deficit/hyperactivity disorder compared with normal subjects. The strongest evidence in this study was finding a significant difference of QEEG among the ADHD patients in relation to the control group, even after the exclusion of low IQ and the suspected epileptic patients out of the study. These recordable differences may indicate organicity of the disorder. This organicity was implied by Levy¹¹ who viewed ADHD as a “problem of polysynaptic dopaminergic circuits between the prefrontal and striate centers”. Later, Swanson et al.¹² reported that the frontal lobe and basal ganglia are nearly 10% smaller in children with ADHD versus controls from magnetic resonance imaging (MRI) data and also that this syndrome is associated with polymorphism in the dopamine D₄ receptor and transporter genes.

The most evident frequency band among ADHD children was theta (θ), followed by alpha1 band (α1) and lastly delta band (δ). Most of the control group showed QEEG activities of alpha 1 (α1) band followed by theta band (θ), and lastly alpha 2 (α2) band. These findings were consistent with what was reported by Chabot and Serfontein (1996).¹³ They stated that children with ADHD displayed increased theta power, slight elevations in frontal alpha power, and diffuse decreases in beta mean frequency. They also denoted that the strong evidence of theta power increased among the ADHD children indicating that cortical hypoarousal is a common neuropathological mechanism in ADHD.  In our study this cortical hypoarousal was strongly observed with the increase of theta activities among the ADHD children (50 – 95.5%) in contrast to the control children (≤ 45.5%). This cortical slowing only in the ADHD group is consistent with SPECT research, in which evidence of hypoarousal was noted in patients with ADHD¹⁴ but not in patients diagnosed with an Affective Disorder¹⁵ or Oppositional Defiant Disorder.¹⁴ It is also consistent with prior single channel and multichannel QEEG studies in that hypoarousal was noted only in ADHD groups. The results which encourages the researchers to recommend QEEG as an assistant diagnostic tool for the diagnosis of ADHD.⁴

Calculation of theta /beta power ratios was a focus of interest of researchers to find a specific quantitative statistics measuring the hypoarousal state in ADHD children, even among those children with ADHD who showed an excess of beta activity in some leads recording.¹⁶ Most of studies found an increase in theta/beta ratios among ADHD children in comparison to control groups regardless the mental state of activity or resting during the recording.^3,4,17,18 Most of these subjects who had beta activity among the ADHD groups were recorded during specific mental tasks.^3,17 In our study, EEG was recorded during a resting state, and  neither control nor ADHD groups showed any beta activity in any of electrodes. So, the measurement of theta power quantity was the absolute indicator of the hypoarousal state among ADHD children. 

On the other hand, analyzing QEEG using the relative power of each frequency had less attention in researches. The current study showed statistically significant difference between control and ADHD groups regarding the relative power of all frequencies except the β2 frequency band relative power, showed no statistically significant difference. The relative power was found to be higher among ADHD group in case of δ and θ frequency bands while it was higher in control group as regarding α1, α2 and β1 frequency bands. Theta band relative power increase among ADHD children still had the most constant finding in those earlier studies.^18,19,20 in contrary for the delta bands relative power which was found to be decreased in one of those studies.¹⁴

Conclusion and Recommendation

Biological background for ADHD was highly suggested by the observed cortical hypoarousal using QEEG. This could be measured by QEEG using PPF or RP of theta band. Still a prospective study covering differential diagnosis would be required to determine validity of clinical applications. Standardization of the QEEG technique would be also needed, specifically with control of mental state, drowsiness, and medication.

[Disclosure: Authors report no conflict of interest]

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