اقدامات همزمان EEG و EDA در اختلال بیش فعالی با نقص توجه نوجوانان
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|32692||1999||12 صفحه PDF||سفارش دهید||محاسبه نشده|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : International Journal of Psychophysiology, Volume 34, Issue 2, 1 November 1999, Pages 123–134
Adolescent unmedicated ADHD males and age- and sex-matched normal control subjects were examined simultaneously using EEG and EDA measures in a resting eyes-open condition. ADHD adolescents showed increased absolute and relative Theta and Alpha1 activity, reduced relative Beta activity, reduced skin conductance level (SCL) and a reduced number of non-specific skin conductance responses (NS.SCRs) compared with the control subjects. Our findings indicate the continuation of increased slow wave activity in ADHD adolescents and the presence of a state of autonomic hypoarousal in this clinical group.
Attention Deficit Hyperactivity Disorder (ADHD) is a behavioural syndrome of unknown aetiology, one of the most disruptive psychiatric disorders of childhood, with a prevalence that has been estimated to affect as much as 10% of school-age boys (Dulcan, 1997). The principal features of this disorder are lack of sustained attention, hyperactivity and impulsivity [American Psychiatric Association (APA, 1994)] associated with low self-esteem and poor academic performance. There are a number of features of this disorder that are age specific. Younger children tend to exhibit signs of gross hyperactivity and motor activity whereas in older children and adolescents, the hyperactivity has in most cases abated but may be experienced as inner feelings of restlessness (APA, 1994). The inattention and impulsivity, however, tend to endure. Non-invasive measures of brain activity, such as electroencephalography (EEG) have been utilised as a means of elucidating underlying neural substrates associated with this disorder. Previous EEG studies in ADHD have examined mostly pre-adolescent children and have found increased slow wave activity (mostly Theta) (Satterfield et al., 1972, Lubar, 1991, Mann et al., 1992, Matsuura et al., 1993, Janzen et al., 1995, Chabot and Serfontein, 1996, Defrance et al., 1996, Bresnahan et al., 1997 and Clarke et al., 1998) in ADHD children compared with normal control subjects. Mann et al. (1992) reported that ADHD pre-adolescents without hyperactivity or specific learning disabilities showed significantly increased Theta activity in the anterior-central regions compared with normal control subjects. Other studies employed a ratio of Theta to Beta that takes into account individual variability to examine regional activity in ADHD. Lubar (1991) found that this ratio was increased in the anterior region of their ADHD sample while Janzen et al. (1995) found an increase in the posterior region. Furthermore, Defrance et al. (1996) reported that children with ADHD showed significantly increased Theta activity over the entire scalp compared with control subjects under both resting and attend conditions. Other studies have also reported a consistently reduced Beta activity in ADHD children (Callaway et al., 1983, Satterfield et al., 1984, Mann et al., 1992, Bresnahan et al., 1997, Clarke et al., 1998 and Lazzaro et al., 1998). Satterfield et al. (1984) found an interaction between age and Beta activity. Younger ADHD children were found to show reduced Beta activity compared with control subjects. Electrodermal activity (EDA) in ADHD has been investigated by a number of studies (for reviews see Rosenthal and Allen, 1978 and Zahn, 1986). Most of these studies examined pre-adolescent ADHD children using electrodermal indices of arousal such as the skin conductance level (SCL), the skin conductance response (SCR) and the number of non-specific skin conductance responses (NS.SCRs) during resting, non-attend and attend conditions (Satterfield and Dawson, 1971, Satterfield et al., 1972, Satterfield et al., 1984, Cohen and Douglas, 1972, Spring et al., 1974, Montagu and Swarbrick, 1975, Montagu, 1975, Zahn et al., 1975, Zahn et al., 1978, Zahn et al., 1980, Rapoport et al., 1980, Pliszka et al., 1993, Shibagaki et al., 1993 and Zahn and Kruesi, 1993). Some of these studies have reported reduced SCL (Satterfield and Dawson, 1971 and Satterfield et al., 1972) and reduced task-related SCR amplitudes (Satterfield and Dawson, 1971, Cohen and Douglas, 1972, Spring et al., 1974, Zahn et al., 1975 and Shibagaki et al., 1993) in unmedicated ADHD children compared with control subjects. The number of NS.SCRs was also found to be significantly lowered in ADHD children compared with control subjects (Satterfield and Dawson, 1971). The behavioural disturbances characteristic of pre-adolescent ADHD children such as impulsivity and attentional deficits are known to continue into adolescence (Barkley, 1990). Only a paucity of studies have examined EEG and EDA measures in adolescent ADHD. Suffin and Hamlin Emory (1995) in an EEG study, employed an eyes-closed condition and neurometric EEG analysis to separate a subgroup of ADHD adolescents who showed both excessive frontal Theta activity and which were also responsive to stimulant medication, from a larger cohort of ADHD patients. Bresnahan et al. (1997) examined as part of a larger study, adolescents diagnosed with ADHD and found increased Theta activity in this group compared with control subjects. Our group (Lazzaro et al., 1998) examined EEG activity in 26 ADHD adolescents (11–17 years of age) during a 2-min resting eyes-open condition. Theta activity was significantly larger in the ADHD group compared with the control subjects in the anterior region and in the left and right hemispheres. With respect to EDA, Zahn and Kruesi (1993) examined a clinical sample of boys ranging in age from 6 to 17 years from the disruptive behaviour disorder spectrum consisting of ADHD, Conduct and Oppositional Defiant Disorders. There were no significant differences in SCL between the disruptive disorder sample and the normal control subjects. SCR frequency, however, was found to be significantly larger in the control subjects than in the disruptive behaviour group. EEG and EDA measures have generally been explored separately in ADHD. No study has examined interactions between these central and peripheral measures in this disorder, although it is known that there are central networks exerting inhibitory and excitatory effects on electrodermal activity (Roy et al., 1993 and Sequeira and Roy, 1993). Furthermore, our group in a previous study involving adult normal control subjects has shown that during a non-attend auditory task, Alpha, Beta and Theta power were each negatively correlated with SCL (Lim et al., 1996). This current study served to explore simultaneously acquired EEG activity and autonomic electrodermal measures of arousal in a group of adolescent males diagnosed with ADHD and in normal control subjects during an eyes-open resting condition. The main hypotheses of this study are that Theta activity in the ADHD adolescents would be increased anteriorly and that simultaneously acquired SCL and the number of NS.SCRs would be significantly reduced in this group compared with control subjects. Increased Theta activity would also be associated with decreased arousal in the ADHD group. Fifty-four adolescent males diagnosed with ADHD (mean age=13.7 years; S.D.=1.4; age range=11–17 years) and 54 age- and sex-matched normal control subjects (mean age=13.4 years; S.D.=1.5; age range=11–17 years) were examined in this study. ADHD patients were referred by paediatricians, clinical psychologists and psychiatrists who considered them to have a diagnosis of ADHD. All patients (accompanied by a parent) were subsequently interviewed by our team using a semi-structured interview based on DSM-IV criteria for ADHD (APA, 1994). For older children, symptom features present before the age of 7 years were established retrospectively with the aid of their parents. For children with a prior diagnosis of ADHD, records were available. Forty-seven patients fulfilled the criteria of ADHD of the Combined Type diagnosis while seven patients fulfilled the criteria for ADHD of the Predominantly Hyperactive–Impulsive Type. Thirty-four ADHD patients were drug naive at the time of electrophysiological testing while the remaining 20 were withdrawn from stimulant treatment for a period of 2 weeks or longer prior to testing. Each patient was then rated using the Conners’ Parent (48-item) and the Conners’ Teacher (28-item) Rating Scales (Conners, 1989) and the Achenbach Child Behaviour Check List for parents (Achenbach, 1991a) and Teacher’s Report Form (Achenbach, 1991b). Patients were accepted into this study if they showed raised scores on the Hyperactivity Index on both the Conners’ Parent and Teacher Rating Scales. For the Conners’ Parent Rating, entry cut-off was set at a T-score of 1.0 S.D. above the norm while for the Conners’ Teacher Rating, entry criteria was set at 1.5 S.D. above the norm. All patients were to have no history of neurological disorder or substance abuse. Age-matched normal control boys were recruited from local high schools. Each control participant was interviewed prior to acceptance to ensure no history of ADHD, neurological disorder or substance abuse. Only control subjects with a T-score of <1.0 S.D. above the norm on the Conners’ Parent and Teacher Rating Scales were accepted into the study. Boys in both groups were further assessed for intellectual ability and learning achievement using the Kaufman Brief Intelligence Test (K-BIT: Kaufman and Kaufman, 1991) and the Wechsler Individual Achievement Test (WIAT: Psychological Corporation, 1992). Criterion for sample entry was a K-BIT composite IQ estimate of 75 or greater. EEGs were acquired continuously for 2 min during a resting eyes-open condition. This formed the baseline of a larger study consisting of non-attend and attend conditions to be presented at a later stage. The EEGs were recorded using an electrocap (Blom and Anneveldt, 1982) from 19 electrode sites (Fp1, Fp2, Fz, F3, F4, F7, F8, Cz, C3, C4, T3, T4, T5, T6, Pz, P3, P4, O1,O2) of the International 10–20 system. Linked earlobes served as reference. EOG activity was monitored via two bipolar electrodes placed 1 cm at the outer canthus of each eye to measure horizontal EOG and a separate bipolar montage was placed above and below the centre of the left eye to record vertical eye movement. All electrode impedances were <5 kΩ. All subjects were seated in a reclining comfortable dental chair. During the recording, subjects were instructed to look at a small circular dot (to limit eye movement) placed 60 cm on a screen in front of them. All potentials were acquired on a Syn Amps (NEURO SCAN Inc.) 32-channel DC system with a gain of 200 and digitisation rate of 250 Hz. All signals were band-limited to 50 Hz. EOG correction was carried out post acquisition using the Gratton et al. (1983) procedure in which linear regressions were calculated between each of the EOG and the EEG channels. The regression coefficients were then determined from which correction factors were derived and applied to correct the EEG data. Skin conductance was recorded simultaneously and continuously with the EEG. A pair of silver–silver chloride electrodes, approximately 0.8 cm2 in contact area, filled with electrode paste (0.05 M NaCl in an inert ointment base) were placed on the volar surface of the distal phalanges of digits II and III of the non-dominant hand of each subject. The electrode pairs forming part of the input circuit were excited by a constant voltage of 0.5 V (Lykken and Venables, 1971 and Fowles et al., 1981) and the current change representing conductance was recorded using the Syn Amps DC amplifier and digitised at 250 Hz. A fast Fourier transform (FFT) analysis was applied to 60 1-s epochs of the EEG. An average power spectrum was then computed for each subject. This was then used to determine absolute and relative EEG activity (power) in the Delta (1.0–3.0 Hz), Theta (4.0–7.0 Hz), Alpha1 (8.0–9.0 Hz), Alpha2 (10.0–13.0 Hz), Alpha (8.0–13.0 Hz) and Beta (14.0–30.0 Hz) bands. Each frequency band was submitted separately to a repeated two-way analysis of variance, in which group (control subjects vs. ADHD) was a between subject factor and site was a repeated within subject factor. Between group regional analyses were then undertaken that examined the midline (Fz, Cz, Pz), anterior (Fp1, Fp2, Fz, F3, F4, F7, F8), posterior (Pz, P3, P4, T5, T6, O1, O2), left hemispheric (Fp1, F3, F7, C3, T3, P3, O1) and right hemispheric (Fp2, F4, F8, C4, T4, P4, O2) activity. Data was initially screened for normality of distribution and homogeneity of variance. To obtain normality of distribution, absolute power scores were log transformed. Relative power scores (x%) were transformed using ln [x/(100−x)] ( Gasser et al., 1982). With repeated measures design, Greenhouse–Geisser correction was used for adjusting univariate results for violations of compound symmetry assumptions. Bonferroni-type adjustments were applied to control for type 1 error where appropriate. For each 1-s epoch in which an FFT was calculated, the tonic SCL (μS) for that epoch was determined by calculating the average within that epoch. This resulted in 60 SCL values across the 2-min period. These 60 values were then averaged to form a mean SCL for each subject. SCL was then submitted to a two-sample t-test that compared the control subjects with the ADHD group. NS.SCRs were obtained for each subject using a curve fitting procedure (SCORES) based upon the sigmoid-exponential SCR model ( Lim et al., 1997). This method allowed the decomposition of skin conductance into tonic and phasic components from which the NS.SCRs were determined. The number of NS.SCRs across the 2-min period for each subject was then obtained by counting the number of responses which occurred during this period. The number of NS.SCRs were then submitted to a non-parametric Mann–Whitney test for group comparison. Associations between absolute and relative Theta power with the EDA measures in every region were explored using correlational analyses. All statistical analyses were carried out using the Statistical Package for the Social Sciences (SPSS 6.1.3). There were no significant differences in mean age (t=1.14; P>0.1) between ADHD patients and control subjects. Mean K-Bit composite IQ scores for the control subjects were (mean IQ=103; S.D.=9.7) and for the ADHD patients (mean IQ=96.3; S.D.=10.5). ADHD patients had significantly larger mean rating scores on the Hyperactivity Index, Impulsive–Hyperactive and Hyperactivity subscales for the Conners’ Teacher and Parent Rating Scales ( Table 1).