تجزیه و تحلیل EEG در اختلال نقص توجه/بیش فعالی: مطالعه مقایسه ای از دو زیرگروه
|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|32689||1998||11 صفحه PDF||سفارش دهید|
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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Psychiatry Research, Volume 81, Issue 1, 19 October 1998, Pages 19–29
This study investigated differences in the EEG between children with Attention-Deficit/Hyperactivity Disorder of the Combined Type, Attention-Deficit/Hyperactivity Disorder of the Predominantly Inattentive Type and control subjects. All subjects were between the ages of 8 and 12 years, and groups were matched on age and gender. The EEG was recorded during an eyes-closed resting condition from 21 monopolar derivations and these were clustered into nine regions prior to analysis. One minute of trace was analysed using Fourier transformation to obtain both absolute and relative power estimates in the delta, theta, alpha and beta frequency bands. The patient groups were found to have greater levels of theta and deficiencies of alpha and beta in comparison to the control group. Children with Attention-Deficit/Hyperactivity Disorder of the Predominantly Inattentive type were found to be significantly different from those of the Combined type in the same measures, appearing to be closer to the normal profiles. The general results support a maturational lag model of the central nervous system in Attention Deficit/Hyperactivity Disorder. The differences between the subtypes suggest a difference in the severity of the disorder rather than a different neurological dysfunction.
Over the course of this century the disorder that has become known as Attention Deficit/Hyperactivity Disorder (ADHD) has undergone clarification in its aetiology. Initially ADHD was believed to result from brain damage, but this explanation lost favour as children without brain damage were diagnosed with ADHD. Subsequently, researchers in the 1950s and 1960s changed the name of this disorder from `minimal brain damage' to `minimal brain dysfunction' (Green and Chee, 1994). In 1968 the DSM-II first listed diagnostic criteria for ADHD under the title `hyperkinetic reaction of childhood', characterised by overactivity, restlessness, distractibility and short attention span (APA, 1968). Much of the literature from the 1960s and 1970s used both `minimal brain disfunction' (MBD) and `hyperactive' to describe the same disorder. In DSM-III (APA, 1980), the title was changed to `Attention Deficit Disorder' and two groups were identified, children with and without hyperactivity. In the DSM-IV (APA, 1994), the diagnostic criteria have changed again, with three main groups being identified: ADHD of the Predominantly Hyperactive-Impulsive Type, ADHD of the Predominantly Inattentive Type (ADHDin) and ADHD of the Combined Type (ADHDcom). This disorder is primarily found in boys (James and Taylor, 1990), with the ratio of boys to girls being approx. 4:1 for all three DSM-IV groups (De Quiros et al., 1994). With normal maturation, EEG frequencies increase as a function of age, with slow wave activity apparently being replaced by faster waveforms (Matousek and Petersen, 1973Matthis and Scheffner, 1980). John et al. (1980)developed 32 linear regression equations predicting the frequency composition of the EEG as a function of age. The results indicated that development of the normal EEG was linear in nature. Benninger et al. (1984), in a longitudinal study of 96 boys and girls, found that theta activity decreased as alpha increased and that the speed of change in occipital areas was almost twice that of central areas. Gasser et al. (1988a)found that certain regions of the brain matured before other regions. Absolute power in delta, theta and alpha 1 frequency bands was found to decrease and amplitudes to become similar with age. The decline was found to be greatest in posterior regions. Frontally, delta and theta were found to develop in parallel, whereas theta dominated delta in all other areas. Alpha activity showed a strong posterior increase. At frontal and central regions, the increase started later and remained small. All beta activity showed a decline with age. Except for alpha 2 activity, all frequency bands and total power showed a continuous decrease in power with age. For relative power, a strong complementary replacement of theta by alpha 2 activity was found up to the age of 14. Delta, theta and alpha 1 frequencies decreased with age and higher frequencies increased. All of these studies found a decrease in slow wave activity and an increase in faster frequency bands with age, with this change being linear in nature. Topographic studies of maturation have found changes to take place from posterior to anterior regions. Gasser et al. (1988b)found that delta, theta and alpha waves were developed earliest occipitally followed by parietal, central and frontal regions. Beta waves developed earliest in central regions followed by parietal, occipital and then frontal regions. In the central area, the midline was found to have a lower frequency power than the two hemispheres, whereas high frequency power was found more evenly distributed between the three regions. Electrophysiological studies of children with learning and behavioural problems have found that these children have differences in the EEG when compared to normal control subjects (John et al., 1988). Studies of mentally retarded children (Gasser et al., 1983a), learning disabled children (Lubar et al., 1985) and hyperactive children (Capute et al., 1968Wikler et al., 1970) have found an increase in slow wave activity in the EEG. Satterfield et al. (1973a), with a group of good responders to stimulant medication, found an increase in slow wave activity and greater power in the lower frequency bands between 0 and 8 Hz, prior to medication being prescribed. Matousek et al. (1984)found the highest correlates of MBD in the relative delta band for parieto–occipital derivations. Mann et al. (1992), in a study of children with ADHD, found an increase in absolute amplitude in the theta band during a resting condition, predominantly in the frontal regions. During cognitive tasks, ADHD children showed a greater increase in theta activity in frontal and central regions, and a decrease in beta activity in posterior and temporal regions, with tasks requiring sustained attention. The ADHD children were found to have EEG frequency distributions that resembled profiles typical of younger children. Mann et al. (1992)concluded that this finding supported the view that ADHD reflects maturational delays in the systems that subserve attention. The studies outlined above have led researchers to propose two models of ADHD with a neurophysiological basis. The first model proposes that ADHD is the result of a low level of central nervous system (CNS) arousal (Satterfield and Cantwell, 1974). To investigate this, Satterfield and Dawson (1971)conducted a study of skin conductance levels (SCLs). This study found that 50% of the hyperactive children had abnormally low SCLs, supporting a model of low CNS arousal. Hyperactive children have been found to respond well to the use of stimulant medication and are often prescribed stimulants as part of their clinical management (Spencer et al., 1996). Two of the drugs most commonly used in the treatment of ADHD in Australia are dexamphetamine and Ritalin (Serfontein, 1991). Both of these drugs act as CNS stimulants and have the effect of increasing concentration and reducing excessive motor activity. These findings further support a model of low CNS arousal. A second model of ADHD, although not incompatible with a low CNS arousal model, is the maturational lag model. Studies of the auditory evoked potential have found that hyperactive children have significantly lower amplitudes and longer latencies than age-matched control subjects (Satterfield et al., 1973aSatterfield et al., 1973b). These findings are typical of younger children. Most studies of ADHD have used populations of children exhibiting hyperactive behaviours with few studies investigating subtypes of ADHD. Kuperman et al. (1996), using the DSM-III-R criteria, studied quantitative EEG differences between children with ADHD, Undifferentiated Attention Deficit Disorder (UADD) and normal children. For relative power, main effects of band were found, with the control group having more delta than the UADD subjects and less beta than both groups of children with ADD. Only the UADD group had hemispheric differences, with decreased delta and increased beta in the left hemisphere. This study investigated topographic effects only where a significant main effect was found for the band and this may have resulted in significant regional differences being overlooked. An eyes-open condition was also used, making comparison with most other EEG studies of ADHD difficult. Chabot and Serfontein (1996)studied EEG differences in children with ADD with or without hyperactivity, using the DSM-III criteria. The children with ADD were found to have an increase in absolute and relative theta, with the greatest increase being found in frontal regions and at the midline. A slight elevation in relative alpha was also noted, and in a small group of subjects (13%), an increase in beta was found. The differences between the two ADD groups mainly involved degree of abnormality, not type. From these results, Chabot and Serfontein (1996)concluded that the EEG patterns represented a deviation from normal development, not a maturational lag. DSM-IV (APA, 1994) outlined diagnostic criteria for three subgroups of children with ADHD. This study investigated two of these subgroups of children with ADHD: children with ADHDcom and ADHDin, to determine whether the two subgroups differ from normal control subjects in their EEG. A further aim of this study was to investigate EEG differences between the ADHDcom and the ADHDin subgroups to determine if the subgroups were neurologically independent. It is anticipated from the literature cited that differences between the control group and the two ADHD groups will be found in the theta band frontally and the delta and beta bands in posterior regions.