1 643824EEGXXX / Clinical EEG and NeuroscienceMarkovska-Simoska and Pop-Jordanova research-article2016 Original Article Quantitative EEG in Children and Adults With Attention Deficit Hyperactivity Disorder: Comparison of Absolute and Relative Power Spectra and Theta/Beta Ratio Clinical EEG and Neuroscience 1 13 EEG and Clinical Neuroscience Society (ECNS) 2016 Reprints and permissions: sagepub.com/journalspermissions.nav DOI: / eeg.sagepub.com Silvana Markovska-Simoska 1 and Nada Pop-Jordanova 1 Abstract In recent decades, resting state electroencephalographic (EEG) measures have been widely used to document underlying neurophysiological dysfunction in attention deficit hyperactivity disorder (ADHD). Although most EEG studies focus on children, there is a growing interest in adults with ADHD too. The aim of this study was to objectively assess and compare the absolute and relative EEG power as well as the theta/beta ratio in children and adults with ADHD. The evaluated sample comprised 30 male children and 30 male adults with ADHD diagnosed according to DSM-IV criteria. They were compared with 30 boys and 30 male adults matched by age. The mean age (±SD) of the children s group was 9 (±2.44) years and the adult group 35.8 (±8.65) years. EEG was recorded during an eyes-open condition. Spectral analysis of absolute (μv 2 ) and relative power (%) was carried out for 4 frequency bands: delta (2-4 Hz), theta (4-8 Hz), alpha (8-13 Hz), and beta (13-21 Hz). The findings obtained for ADHD children are increased absolute power of slow waves (theta and delta), whereas adults exhibited no differences compared with normal subjects. For the relative power spectra there were no differences between the ADHD and control groups. Across groups, the children showed greater relative power than the adults in the delta and theta bands, but for the higher frequency bands (alpha and beta) the adults showed more relative power than children. Only ADHD children showed greater theta/ beta ratio compared to the normal group. Classification analysis showed that ADHD children could be differentiated from the control group by the absolute theta values and theta/beta ratio at Cz, but this was not the case with ADHD adults. The question that should be further explored is if these differences are mainly due to maturation processes or if there is a core difference in cortical arousal between ADHD children and adults. Keywords attention deficit hyperactivity disorder, children, adults, QEEG, absolute power, relative power, theta/beta ratio Received January 9, 2015; revised March 1, 2016; accepted March 2, Introduction Attention deficit hyperactivity disorder (ADHD) is a common disorder in children and adults. The essential diagnostic criteria for the disorder include developmentally inappropriate levels of impulsive, hyperactive, and inattentive behaviors. These behaviors affect almost every area of daily functioning. ADHD is now recognized as a common childhood disorder and DSM-IV 1 estimates that 3% to 5% of school-age children are affected. Currently, the worldwide prevalence of ADHD is estimated by Willcutt 2 to be between 5% and 7%. It has been reported 3,4 that adults with ADHD continue to present attention problems. In fact, 15% of children with ADHD continue to meet full diagnostic criteria at age 25 years and another 50% are in partial remission. 5 According to Wender, 6 adults with ADHD continue to present attention difficulties that tend to manifest themselves in personal relationships and academic pursuits, and they often report problems with short-term memory, distractibility, and impulsivity. ADHD is diagnosed clinically by assessing behavioral symptoms and impairment via interviews and standard questionnaires. Diagnosis can be challenging as the core symptoms are nonspecific. At present, no reliable objective measures of ADHD exist. In the past decade, many studies have tried to define the neural correlates of ADHD, particularly changes in quantitative EEG (QEEG). The pattern of neuronal oscillations plays an important role in the evaluation and treatment of 1 Macedonian Academy of Sciences and Arts, Skopje, Republic of Macedonia Corresponding Author: Silvana Markovska-Simoska, Macedonian Academy of Sciences and Arts, Bul Krste Misirkov br.2, P.O. Box 428, 1000 Skopje, Republic of Macedonia.
2 2 Clinical EEG and Neuroscience children and adults with ADHD although more objective diagnostic procedures would provide a valuable supplement in postulating the diagnosis of ADHD. The most commonly used form of EEG analysis in studies of ADHD has been the estimation of absolute and relative power. The number of studies in this field is numerous. At the moment of writing of this article, a search for the key words ADHD and EEG on PubMed database provided 3439 articles. In this article, we refer to the most related ones. Most of these studies concerning ADHD in children summarize that they have a reduced power in alpha and beta bands and an increased power in delta and theta bands in comparison with healthy control groups One of these studies 7 supports a maturational lag model of the central nervous system in ADHD, while another study 9 from the same author three years later reports that an ADHD model is a result of developmental deviation, rather than a maturational lag of central nervous system. Chabot and Serfontein 11 reported EEG differences in 407 ADHD children compared to a normative database. According to them, children with ADHD had an increase in absolute and relative theta, primarily in the frontal regions and at the frontal midline. In adolescence, as a transitive age, the population with ADHD showed similar results as children. In particular, Hobbs et al 12 investigated EEG abnormalities in male adolescents with ADHD during an eyes-closed resting condition and found absolute dominance of delta and theta activity and a higher theta/beta ratio (TBR) compared with control subjects. Similar results with increased theta activity, along with decreased beta power in eyes-open resting condition in adolescents with ADHD have been described by Lazzaro et al. 13 Despite the great interest in EEG studies in children, in recent years there has been a growing interest in adults with ADHD too. Bresnahan et al 14 published the first study that investigated the EEG profiles of adult ADHD subjects, using 3 age groups: children, adolescents, and adults, with age and sex matched controls. Their results indicated that absolute and relative theta activity remained elevated through adolescence into adulthood. Other studies have also reported reduced alpha 15 and beta activity, 16 though other authors have failed to observe group differences for at least one of the bands suggesting a degree of normalization with maturation. Because the absolute values of EEG spectra depend on some features unrelated to the brain, such as thickness of the skull, a relative parameter defined as the TBR is introduced. 21 Multicentric studies in the United States have used the TBR as an index of inattention. This so-called inattention index is defined as the ratio of theta EEG power (measured within the 4-8 Hz frequency band) and beta EEG power (measured within Hz frequency band). Usually, this index is calculated by EEG recording at Cz electrode in reference to linked ears. It was found that this index is 3 times higher in inattentive (according to DSM-IV inattentive type of ADHD is characterized with predominantly symptoms of inattention) and combined types (according to DSM-IV combined type of ADHD is characterized with both symptoms of inattention and hyperactivity/impulsivity) of ADHD children aged 6 to 10 years compared with normal group. Monastra et al 23,24 found that the sensitivity of this index (the percentage of ADHD children testing positive regarding TBR) was 86% to 90% and its specificity (the percentage of non-adhd testing negative regarding this index) was found to be 94% to 98%. Contrary to these findings scientists from the Human Brain Institute in St Petersburg 25 showed that this index is a good measure only for a part of the ADHD population. Mapping this index in a normal population showed that the location of the maximum of this index changes significantly with age. For example the maximum TBR moves from the central-parietal location in 7- to 8-year-old children to fronto-central location in adults. The conclusion was that for better results in discriminating the ADHD population from healthy subjects, this index must be measured in different electrode position depending on age. Elevated TBRs have been reported for both children and adults with ADHD, 10,14,17,26 but in recent years, there have been studies which did not find any significant TBR difference between ADHD and control groups. 19,20,27 Certainly, in the assessment of EEG spectral power in children and adults with ADHD, maturational processes of brain activity should be taken into consideration. There are several former and recent studies of age-related changes in EEG activity. The characteristic signature of brain maturation is shifting from low to high EEG frequencies. In a study by Matousek and Petersen 28 there was a linear decrease of absolute and relative power in delta and theta bands and an increase in the alpha and beta bands with increased age. In a study by John et al 29 examining EEG as a function of age, it was concluded that the frequency composition of the EEG reflects the age and functional status of the brain. Similarly, a longitudinal study by Benninger et al 30 demonstrated that as theta activity decreased, alpha activity increased. Gasser et al 31 showed that all bands except for alpha 2 decreased in absolute power, whereas the fast bands increased and the slow bands decreased in relative power. In summary, these studies have provided evidence that EEG activity changes systematically as a function of age. There are few scientific articles that directly estimate the differences in EEG power between children and adults with ADHD. 14,19 Bresnahan et al 14 found that theta activity was elevated in the ADHD groups across all age groups compared with normal controls, while the extent of the reduction in relative beta activity in the ADHD groups decreased with increasing age. In contrast, a study by Liechti et al 19 found no consistent theta or theta/beta increases in ADHD. The aim of this study was to assess resting electrocortical profiles in children and adults with ADHD and compare them with control groups matched by age and sex. It was hypothesized that ADHD children and adults would be characterized by more slow than fast waves and higher TBR, compared with control groups. Subjects and Methods A total of 30 boys and 30 male adults with ADHD were examined in this study. They were compared with 30 boys and 30 adults from the Human Brain Index (HBI) database, matched
3 Markovska-Simoska and Pop-Jordanova 3 Table 1. Demographics of the Sample. by age. Having in mind the male prevalence of ADHD and because only 2 girls were referred to us as ADHD, we decided to include only male subjects. Table 1 shows demographic information for patients and controls. Diagnosis for children was made by a team consisting of a senior neuropsychologist, a pediatrician, and a clinical psychologist. In addition to the clinical assessment, Conners Rating Scales for teachers and parents were also used. 32,33 Diagnosis of adults with ADHD was based on a clinical interview by a psychiatrist in conjunction with Barkley s Semistructured Interview. 34 Some adults with ADHD were identified among the parents of these children. Only those who presented with a childhood history consistent with ADHD and who experienced sufficient current symptoms to satisfy the adult diagnostic criteria were included in the study. Adults diagnosed with ADHD and comorbid diagnoses were excluded from the analysis. None of the subjects had any serious medical or neurological problems (including seizures) or recent (<6 months) head trauma. No one from the examined individuals was taking psychostimulants, since these kind of medicines are not registered for use in the Republic of Macedonia. Therefore there was no need for a washout period. Only right-handed children and adults were included in the study. All participants and children s parents gave informed, written consent and the study was approved by the local ethics committee. The subjects did not receive any compensation for their participation in this study. Quantitative EEG ADHD Children Control Children ADHD Adults Control Adults Male gender, n Age, years, 9 (2.44) (2.27) 35.8 (8.65) 35.3 (8.53) mean (SD) Age, years, range The same equipment and procedures were used for patients and controls when QEEG was recorded. Subjects were tested in a quiet air conditioned room with the experimenter and recording equipment present. All recordings were made during working office hours (8:00 am to 3:00 pm). The participants did not abstain from eating, but did refrain from tobacco/caffeine on the morning of the day of testing. EEG was recorded using a Mitsar 201 ( a PC-controlled 19-channel electroencephalographic system. During fitting of the electrodes, subjects were familiarized with the testing equipment and the procedure. While seated in a comfortable chair, subjects were required to fixate on a computer monitor for a 5 minute period while EEG was recorded with eyes-open condition. All participants were instructed to avoid excessive blinking. EEG recordings were obtained using an electrode cap (Electro-Cap International) with 19 electrodes placed according to the international system, linked ear lobe (A1-A2) referenced and electrode impedance maintained below 5 kohm for all electrodes. The input signals were filtered between 0.5 and 50 Hz, and digitized at a sampling rate of 250 Hz. Vertical electro-oculogram (VEOG) was recorded with 2 tin electrodes placed 1 cm above and 1 cm below the right eye. The cap ground electrode was midway between Fpz and Fz. Quantitative data were obtained using WinEEG software ( com). The linked ears reference montage was changed to average reference montage prior to data processing. The average montage was used because it allowed comparisons with the HBI database in WinEEG software, which also consisted of an average montage. Eye-blink artifacts were corrected by zeroing the activation curves of individual ICA component score responding to eye blinks. 35 In addition, epochs of the filtered electroencephalogram with excessive amplitude (>100 μv) and/or excessively fast (>35 μv in Hz band) and slow (>50 μv in 0-1 Hz band) frequency activities were automatically marked and excluded from further analysis. Finally, EEG was manually inspected to verify artifact removal. The continuous EEG data were segmented into 4 second epochs with 50% overlap. Minimum of 60 artifact-free epochs for each individual were included in the analysis. The average number of EEG epochs used for the FFT analyses was 93 (SD = 8.6) for ADHD and 92 (SD = 9.4) for NORM (control groups will be referred as NORM further in the text) children groups. In the ADHD/NORM adults groups the average number of EEG epochs were 98 (SD = 7.9)/94 (SD = 8.2) respectively. Spectral analysis of absolute and relative power using fast Fourier transform was carried out for the four frequency bands: delta (2-4 Hz), theta (4-8 Hz), alpha (8-13 Hz), and beta (13-21 Hz). Relative power is represented by the percentage of the amplitude in a given frequency band compared with the total amplitude across all frequency bands. Also, we calculated the ratio between theta and beta absolute power in order to obtain the TBR at Fz, Cz, and Pz. We used this band range classification in accordance with the literature 23,24,27,36 and in order to have the possibility of comparison, especially for TBR. The HBI database 25 ( was developed to help researchers to perform both conventional and quantitative EEG and event-related potentials (ERPs) studies. It is software for comparing the EEG spectra, coherence and ERP components computed for a given patient relative to a normative database. Inclusion/exclusion criteria presume an uneventful perinatal period, with no head injury with cerebral symptoms, with no history of neurological or psychiatric diseases, with no convulsions, normal mental and physical development, average or better grades in school. The HBI database includes the results of processing more than 3000 EEG recordings collected from more than 1000 healthy subjects at the age from 7 to 89 years. The EEGs were recorded at 7 different conditions. For better representation of the data, we had the access to healthy controls in the HBI database and compared the raw data between the subjects.
4 4 Clinical EEG and Neuroscience Figure 1. Absolute power for delta, theta, alpha, and beta in eyes opened condition (ch, children; ad, adults; *P <.05). Data Analysis The Statistica StatSoft and XLSTAT softwares were used to assess group differences. One-way analysis of variance (ANOVA) was carried out on absolute and relative EEG power for each band (delta, theta, alpha beta) in eyes-open condition in 3 sagittal regions (frontal [F]: (Fp1, Fp2, F3, Fz, F4, F8, F7); central [C]: (T3, T4, C3, Cz, C4); and parietal [P]: (T5, T6, P3, Pz, P4, O1, O2), regions. Group (ADHD children, NORM children, ADHD adults, NORM adults) was the between-subject factor. The matrix for data analysis comprised 12 columns (4 bands, 3 regions) and 120 rows (subjects). If the ANOVAs revealed significant interaction effects with group, Bonferroni post hoc analyses were conducted to examine the group effect.
5 Markovska-Simoska and Pop-Jordanova 5 Table 2. Summary of Significant Post Hoc Bonferroni P Values for Absolute Power Between Groups. Delta Theta Alpha Beta Absolute Power F C P F C P F C P F C P ADHD ch vs NORM ch <.01 <.01 <.05 <.01 <.05 <.01 ADHD ad vs.norm ad ADHD ch vs ADHD ad <.001 <.001 <.001 <.001 <.001 <.001 <.001 <.001 <.001 <.001 <.001 NORM ch vs NORM ad <.001 <.001 <.001 <.001 <.001 <.01 <.001 <.001 <.001 <.01 <.01 <.001 Abbreviations: ADHD, attention deficit hyperactivity disorder; ch, children; ad, adults; NORM, normal; F, frontal; C, central; P, posterior. The level of significance was set at P <.05. Because of space reasons, only significant effects and interactions between groups are reported. In order to evaluate the correlation between age and electrophysiological data, we performed Pearson correlation analysis for each frequency band and TBR. Since, we have carried out correlations per 12 regions for absolute and per 12 regions for relative power, the statistical correction of P values was done with Bonferroni s adjustment. As a newer recent tool, the receiver operating characteristic (ROC) curve analysis was performed to determine usefulness of evaluation of absolute and relative theta central, absolute and relative beta central and TBR at Cz as EEG parameters in distinguishing individuals (children or adults) with ADHD from normal developing subjects. Central position was examined to warrant compatibility with other publications. 19,23,24,27 Accuracy was indicated by the area under the ROC curve. A truly useless test (one no better at identifying true positives) has an area of 0.5. A perfect test (one that has zero false positives and zero false negatives) has an area of Usually, test will have an area between those 2 values. Sensitivity corresponds to the rate of positive cases that are well diagnosed by test. Specificity corresponds to the rate of negative cases that are well diagnosed by test. Results Absolute Power In the comparison within all 4 groups for the absolute delta power, the delta band was significantly higher among children s groups for F(9, 278) = 17.37, P <.001 compared with adults. The ADHD children showed significantly more delta power (frontal, central and posterior) than NORM children (Figure 1, Table 2). For the theta band, there were also statistically significant differences between the ADHD children and NORM children groups, F(9, 278) = 7.43, P <.001. More specifically, the ADHD children showed more spectral power in the theta band than NORM children group in the frontal, central, and posterior areas (Table 2). In comparison of adult groups there was no significant difference between ADHD adults and corresponding NORM adults group for delta and theta power. For alpha and beta bands neither ADHD children nor ADHD adults showed Figure 2. Summary of absolute power for brain waves for children and adults with attention deficit hyperactivity disorder (ADHD). ch, children; ad, adults. any significance compared with corresponding NORM groups. The children (ADHD and NORM) showed more spectral power than adults (ADHD and NORM) in alpha band, F(9, 278) = 6.97, P <.001, and in beta band, F(9, 278) = 6.07, P <.001. Notice that for absolute power the children always have a higher power than adults (Figures 1 and 2). The significant differences (obtained by post hoc Bonferroni tests) between ADHD children and ADHD adults, with higher absolute power for children are presented on Table 2. Relative Power For the relative power, there were no statistically significant effect between the ADHD children and NORM children (except for higher central beta in NORM subjects for P <.05) and between ADHD adults and NORM adults groups in all bands (Figure 3). Children (ADHD and NORM) showed more relative spectral power for delta band, F(9, 278) = 7.49, P <.001, and theta band, F(9, 278) = 4.34, P <.001, than adults (ADHD and NORM). There was a significantly higher spectral power in adults than in children for the alpha F(9, 278) = 3.50, P <.001, and beta, F(9, 278) = 10.77, P <.001, bands (Figure 4). The significant results for the relative power differences between the groups obtained with the post hoc tests are presented in Table 3.
6 6 Clinical EEG and Neuroscience Figure 3. Relative power for delta, theta, alpha and beta in eyes opened condition (ch, children; ad, adults; *P <.05). Theta/Beta Ratio When the ADHD children group was compared with the NORM children group in eyes-open condition, a higher TBR was obtained for ADHD children, F(3, 56) = 2.97, P <.05 (Figure 5). For the adult ADHD group, we did not find any significant difference when compared to NORM adult group. Centro-parietal localization of the TBRs was characteristic for our children s sample, while localization for adults was more fronto-central (Figure 6). Correlations Significant negative correlations with age were found for all EEG absolute power measures with P <.05. Strong
7 Markovska-Simoska and Pop-Jordanova 7 Figure 4. Summary of relative power for brain waves for children and adults with attention deficit hyperactivity disorder (ADHD). ch, children; ad, adults. maturational power reductions were found, especially for delta and theta (Table 4). Negative correlations with age were also found for delta and theta relative power, and positive correlations for alpha and beta (Figure 7 and Table 4). Age vs. TBR correlation coefficient was moderately negative r = ROC curve ROC analysis indicated that assessed EEG parameters, in particular TBR at Cz and absolute theta central were successful in differentiating children with ADHD from control group (accuracy rates of 81% and 87.6% respectively). For ADHD adults moderate accuracy rate of 68.3% was estimated only for relative theta central parameter. For the obtained values of ROC curve see Figure 8 and Table 5. In distinguishing children from adults based on EEG parameters, we can only rely on TBR at Cz (with 87.9% accuracy), absolute theta (99.2%), and beta central (74.4%) (Table 5). Discussion Being the most accessible, informative, and inexpensive method, EEG is widely used for examination and objective diagnosis of ADHD. A number of approaches have been used to assess changes in the EEG of ADHD children and adults. The present study primarily investigated changes in absolute and relative power, which have been found to be reliable EEG measures and are easily interpreted. In the current study, we evaluated 30 children and 30 adults (all male) with ADHD diagnosed according to DSM-IV criteria. They were compared with 30 boys and 30 male adults from the HBI database, matched by age. We subsequently analyzed the absolute and relative power for delta, theta, alpha and beta brain waves recorded in eyes-open condition. Estimation of TBR was added in the analysis as a very common parameter for ADHD diagnosis. Also, classification analysis as a newer recent tool was performed to determine usefulness of used parameters. In line with our hypothesis, we found that absolute power for delta and theta were higher in the ADHD children group, compared with NORM controls, but this was not the case with the adults. Inconsistent with the hypothesis, we found no evidence of increased delta and theta power as well as TBR in the ADHD adults. In comparison between ADHD adults and corresponding controls we did not find any significant difference between these two groups for any band in absolute or relative power. As far as theta/beta ratio is concerned we obtained a significant difference only in the comparison of children s groups (ADHD and NORM), whereas there are no differences in adults. We also found that children and adults (regardless of whether they belong to ADHD or control group) differed with respect to magnitude in absolute and relative power. The children showed higher absolute power for all bands. For relative power we found that the children expressed increased slow waves while the adults expressed increased fast waves. These results contribute to the understanding of specific age-related differences and changes in EEG of the individuals throughout the life span. Our results obtained in children with ADHD compared to the age-matched NORM controls, are very similar to the results from other previous studies that found elevated absolute slow frequency activity (predominantly theta) 7-11,22,37-40 and a decrease in beta activity in ADHD children. In our children s sample, theta was more prevalent in posterior than frontal and central regions, a result that is already noted 41 in children between 7 and 10 years old. Puligheddu et al 42 suggested that this phenomenon may be a precursor of the adult alpha rhythm and could be related to maturation, overlapping the areas implicated in the generation of the lower frequency alpha rhythm. However, theta is also increased in fronto-central region in ADHD children, pointing to slower activity in these areas of the brain responsible for executive functions. Our findings of no difference for the relative power frequency regardless of children s groups is inconsistent with the reports of the studies 10 with significant higher relative slow activity in ADHD children. For relative power we have obtained only one significant difference: central beta, which was higher in NORM children compared with ADHD children. This is contrary to the findings of Chabot and Serfontein 11 and Clarke et al, 43 who found increased beta in ADHD children and claimed that the excess beta profile may represent a separate subtype of ADHD related to comorbid factors in these children. Also, increased beta activity tends to be interpreted as reflecting enhanced cortical activity. 20 In the ADHD adult group, we did not obtain any group interactions for absolute or relative power compared with NORM subjects. This is in line with the report of Liechti et al, 19 with no found EEG abnormalities in ADHD adults, but contrary to the findings of Bresnahan and Barry, 17 which found increased slow wave activity in the adults too. The results of the current study are also in agreement with the research in a more recent study, 44 with no reported EEG differences between the total ADHD
8 8 Clinical EEG and Neuroscience Table 3. Summary of Significant Post Hoc Bonferroni P Values for Relative Power Between Groups. Delta Theta Alpha Beta Relative Power F C P F C P F C P F C P ADHD ch vs NORM ch <.05 ADHD ad vs NORM ad ADHD ch vs ADHD ad <.001 <.001 <.001 <.05 <.01 <.01 <.05 <.001 <.001 <.001 <.001 NORM ch vs NORM ad <.001 <.001 <.001 <.01 <.01 <.05 <.01 <.001 <.001 Abbreviations: ADHD, attention deficit hyperactivity disorder; ch, children; ad, adults; NORM, normal; F, frontal; C, central; P, posterior. Figure 5. Theta/beta ratio. group (ie, comprising both ADHD-I and ADHD-C) and the healthy control group. Also no divergence in the developmental course of EEG activity was found between those groups. Part of our obtained results referring to no group interactions for theta relative power in ADHD adults are in line with the research of Jaworska et al, 20 who also reported no group interactions between ADHD + anger (comorbid dysfunctional anger) and control groups. The results of our study may also indicate the same conclusion as the normalization of brain activity in the frontal and central regions in adults with ADHD may be representative of the changes in clinical presentation evident with increasing age. Liechti et al 19 could not replicate the commonly reported EEG abnormalities in ADHD like theta increase and beta decrease but observed highly consistent maturational changes which is supported by the present study. Our findings are also consistent with some of the reported EEG results of the study of Bresnahan et al 14 who found a decrease in slow wave relative activity and an increase in fast wave activity with increasing age. TBR has been introduced as an indicator of ADHD and is broadly used as indicator for this disorder. Two years ago, the US Food and Drug Administration approved a medical device using the EEG TBR to help assess pediatric ADHD. 45 Our results for TBR of the present study are in line with the findings of Monastra et al. 23 They reported that TBR index can be used for determination of the characteristics of ADHD children, but they are not as accurate for ADHD adults. In this case, we have shown that for ADHD adults it cannot be used with assurance because with maturation it is not a good index. So our obtained TBR results for ADHD adults are consistent with previous work in the recent years documenting an insignificant TBR difference between ADHD and control groups. 19,20,27 That was also confirmed with the ROC curve analysis and obtained accuracy of 81% for using TBR at Cz in discriminating ADHD children from control group, but not for ADHD adults. It can be concluded that TBR can be additional marker of ADHD diagnosis only in children but not in adult population. The evaluated children with ADHD in this article are characterized by excess of the theta beta ratio in parietal-central locations. This can be explained by the fact that for the theta and alpha rhythms, and to a lesser extent delta, maturation begins in posterior regions and ends in anterior regions. This is further explained with the movement of peak point of TBR from parieto-central in children to fronto-central location in adults. Classification analysis showed that ADHD children could be differentiated from the control group by the absolute theta values and TBR at Cz, but this was not the case with ADHD adults. Our results showed higher accuracy rate for theta and TBR at Cz than study of Ogrim et al 27 and Buyck and Wiersema, 44 who obtained moderate accuracy for theta of 63% and 52% and TBR of 58% and 55% in classification of ADHD groups. Regarding age as a test data variable, we have observed results that are similar to those of Buyck and Wiersema 44 in discriminating children versus adults with TBR and absolute theta and beta accuracy, but our results were not in line with their data in terms of relative theta and beta power accuracy values. Our results produced AUC values less than 0.5 for relative power. When we compared the children and adults (ADHD and norms), we found that the EEG patterns are following brain maturational processes as described in several previous studies. Generally with increasing age lower frequencies decrease and higher frequencies increase. 31,46 In this context, Matousek and Petersen 28 confirmed a decrease of absolute and relative power in the delta and theta bands and an increase in the alpha and beta bands during brain maturation. This shift from low to high EEG frequencies is a characteristic signature of brain maturation. Whitford et al 47 suggested that the decrease of lower EEG frequencies in adolescents might be caused by synaptic pruning which is typical of this developmental period. Our findings are
9 Markovska-Simoska and Pop-Jordanova 9 Figure 6. Maps of theta/beta ratio in all groups. Table 4. Summary of Correlation Coefficients and Obtained Significant P Levels After Bonferroni s Adjustment Between Absolute/Relative Power and Age. Delta Theta Alpha Beta F C P F C P F C P F C P Absolute power vs age 0.66*** 0.66*** 0.54*** 0.56*** 0.55*** 0.53*** 0.5*** 0.53*** 0.49*** 0.36** 0.3** 0.5*** Relative power vs age 0.62*** 0.63*** 0.6*** 0.32** 0.51*** 0.36** 0.31** 0.21** 0.34** 0.56** 0.7*** 0.7*** Abbreviations: F, frontal; C, central; P, posterior. **P <.01. ***P <.001. also in accordance to the findings of Barriga-Paulino et al. 46 Their results also indicate that changes in the QEEG of ADHD subjects are age dependent, but still differ significantly from the control group in childhood. Generally ADHD is considered a heterogeneous disorder involving multiple pathways and neurophysiological subtypes. Durston et al 48 suggest a model for differentiating 3 neurobiological subtypes of ADHD: dorsal fronto-striatal, orbitofronto-striatal, or fronto-cerebellar. This could be useful in explaining the neurobiological basis of different clinical pictures of ADHD. The brain deficits in ADHD therefore appear to be multisystemic. 49 This study has several limitations. First, given the difference in ethnicity between the groups (ADHD vs controls), we cannot exclude that this may have influenced the reported EEG findings, though the ethnicity and culture as a covariate did not alter
10 10 Clinical EEG and Neuroscience Figure 7. Correlations between relative power and age. the EEG results according to John et al. 29 Furthermore, methodological choices are a frequent source of variability between studies, hampering direct comparisons of results. As an example the beta frequency range that we used in calculating the TBR may differ from other studies, though there is limited consistency on this matter. 26 In line with this, we tried to be as close to other studies as possible concerning the definition of frequency ranges. Different software options for analysis of the results are another question. Such methodological considerations should be kept in mind when designing future comparable studies. Maybe, one of the options is acceptance of standardized protocol. Also it should be borne in mind that we processed only male children and adults, so there is always a chance that gender may have influenced the results. Using ethnicity, ADHD subtypes, and gender as covariates could be another future direction for conducting research in this area. Finally, ADHD is a heterogeneous disorder where the resting state is not consistently characterized by maturational lag (because of that, recording of another condition should be included in the analysis, primarily the one which will require cognitive effort). 50
11 Markovska-Simoska and Pop-Jordanova 11 Figure 8. Receiver operating characteristic (ROC) curves indicating accuracy of absolute and relative theta central, absolute beta central and theta/beta ratio (TBR) Cz in distinguishing attention deficit hyperactivity disorder (ADHD) children (left) and age classification (right). Table 5. Parameters of ROC Curves for Corresponding Test Variables. EEG Parameter AUC Sensitivity Specificity P ADHD children TBR Cz Absolute theta Cz Absolute beta Cz Relative theta Cz Relative beta Cz ADHD adults TBR Cz Absolute theta Cz Absolute beta Cz Relative theta Cz Relative beta Cz Age/children TBR Cz Absolute theta Cz Absolute beta Cz Relative theta Cz Relative beta Cz Age/adults TBR Cz Absolute theta Cz Absolute beta Cz Relative theta Cz Relative beta Cz Abbreviations: ROC, receiver operating characteristic; ADHD, attention deficit hyperactivity disorder; AUC, area under the curve; TBR, theta/beta ratio. Boldface values represent significant obtained values for AUC. Conclusions Finding objective and reliable biological markers of ADHD would provide a valuable addition to the diagnosis, but until now except for TBR this statement fails. The typical findings in ADHD children are increased slow waves (theta and delta). That was confirmed by present study for children, but not for adults. Between ADHD and control groups more pronounced changes for absolute than for relative power were obtained for children only. Our findings are similar with some other studies concerning age related specifics in ADHD. The main differences between children and adults are the magnitude in relative power, with higher magnitude of delta and theta in children, and higher relative power for alpha and beta for adults. The question that should be further explored is if these differences are mainly due to maturation processes or if there is a core difference in cortical arousal between ADHD children and adults. Our EEG findings suggest that it is unlikely that ADHD is characterized by generalized EEG abnormalities, especially in adults. But, EEG measures used as a diagnostic add-on in ADHD may be of interest in guiding a personalized medicine approach in particular regarding treatment outcomes. Acknowledgments Access to healthy controls in the HBI database was given by director of the Research Clinic, Chur, Switzerland, and CEO Brain and Trauma Foundation, Switzerland Dr Andreas Müller and the data were sent by his assistant Clin Psych Gian Candrian. We would like to thank them and also Mr Martin Wood-Mitrovski for his English language editorial assistance and comments.
12 12 Clinical EEG and Neuroscience Author Contributions SMS contributed to conception and design; contributed to acquisition, analysis, and interpretation; drafted manuscript; critically revised manuscript; gave final approval; agrees to be accountable for all aspects of work ensuring integrity and accuracy. NPJ contributed to design; contributed to interpretation; drafted manuscript; critically revised manuscript; gave final approval; agrees to be accountable for all aspects of work ensuring integrity and accuracy. Declaration of Conflicting Interests The author(s) declared no conflicts of interest with respect to the research, authorship, and/or publication of this article. Funding The author(s) received no financial support for the research, authorship, and/or publication of this article. References 1. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders. 4th ed. Washington, DC: American Psychiatric Press; Willcutt EG. The prevalence of DSM-IV attention-deficit/hyperactivity disorder: a meta-analytic review. Neurotherapeutics. 2012:9; Serfontein G. ADD in Adults: Help for Adults Who Suffer from Attention Deficit Disorder. Sydney, Australia: Simon & Schuster; Weiss G, Hechtman L. Hyperactive Children Grown Up: ADHD in Children, Adolescents, and Adults. 2nd ed. New York, NY: Guilford Press; Faraone SV., Biederman J, Mick E. The age dependent decline of attention deficit hyperactivity disorder: a meta analysis of followup studies. Psychol. Med. 2006;36: Wender P. Attention-Deficit Hyperactivity Disorder in Adults. New York, NY: Oxford University Press; Clarke AR, Barry RJ, McCarthy R, Selikowitz M. EEG analysis in attention-deficit hyperactivity disorder: a comparative study of two subtypes. Psychiatry Res. 1998;81: Clarke AR, Barry RJ, McCarthy R, Selikowitz M. Age and sex effects in the EEG: differences in two subtypes of attention deficit hyperactivity disorder. Clin Neurophysiol. 2001;112: Clarke AR, Barry RJ, McCarthy R, Selikowitz M. Electrophysiological differences in two subtypes of attention deficit hyperactivity disorder. Psychophysiology. 2001;38: Barry R, Clarke A, Johnstone S. A review of electrophysiology in attention deficit/hyperactivity disorder: I. Qualitative and quantitative electroencephalography. Clin Neurophysiol. 2003;114: Chabot RJ., Serfontein G. Quantitative electroencephalographic profiles of children with attention deficit disorder. Biol Psychiatry. 1996;15;40: Hobbs MJ, Clarke AR, Barry RJ, McCarthy R, Selikowitz M. EEG abnormalities in adolescent males with AD/HD. Clin Neurophysiol. 2007;118: Lazzaro I, Gordon E, Li W, et al. Simultaneous EEG and EDA measures in adolescent attention deficit hyperactivity disorder. Int J Psychophysiol. 1999;34: Bresnahan SM, Anderson JW, Barry RJ. Age-related changes in quantitative EEG in attention-deficit/hyperactivity disorder. Biol Psychiatry. 1999;46: Loo SK, Hale TS, Macion J, et al. Cortical activity patterns in ADHD during arousal, activation and sustained attention. Neuropsychologia. 2009;47: Hermens DF, Williams LM, Lazzaro I, Whitmont S, Melkonian D, Gordon E. Sex differences in adult ADHD: a double dissociation in brain activity and autonomic arousal. Biol Psychol. 2004;66: Bresnahan S, Barry R. Specificity of quantitative EEG analysis in adults with attention deficit hyperactivity disorder. Psychiatry Res. 2002;112: Clarke AR, Barry RJ, Heaven PC, McCarthy R, Selikowitz M, Byrne MK. EEG in adults with attention-deficit/hyperactivity disorder. Int J Psychophysiol. 2008;70: Liechti MD, Valko L, Müller UC, Döhnert M, Drechsler R, Brandeis D. Diagnostic value of resting electroencephalogram in attention-deficit/hyperactivity disorder across the lifespan. Brain Topogr. 2013;26: Jaworska N, Berrigan L, Ahmed AG, et al. The resting electrophysiological profile in adults with ADHD and comorbid dysfunctional anger: a pilot study. Clin EEG Neurosci. 2013;44: Lubar JF. Discourse on the development of EEG diagnostics and biofeedback for attention-deficit/hyperactivity disorders. Biofeedback Self Regul. 1991;16: Mann CA, Lubar JF, Zimmerman AW, Miller CA, Muenchen RA. Quantitative analysis of EEG in boys with attention-deficithyperactivity disorder: controlled study with clinical implications. Pediatr Neurol. 1992;8: Monastra VJ, Lubar JF, Linden M, et al. Assessing attention deficit hyperactivity disorder via quantitativeelectroencephalography: an initial validation study. Neuropsychology. 1999;13: Monastra VJ, Lubar JF, Linden M. The development of a quantitative electroencephalographic scanning process for attention deficit-hyperactivity disorder: reliability and validity studies. Neuropsychology. 2001;15: Kropotov JD. Quantitative EEG Event-Related Potentials and Neurotherapy. Amsterdam, Netherlands: Elsevier; Snyder SM, Hall JR. A meta-analysis of quantitative EEG power associated with attention-deficit hyperactivity disorder. J Clin Neurophysiol. 2006;23: Ogrim G, Kropotov J, Hestad K. The QEEG theta/beta ratio in ADHD and normal controls: Sensitivity, specificity, and behavioral correlates. Psychiatry Res. 2012;198: Matousek M, Petersen I. Frequency analysis of the EEG in normal children and normal adolescents. In: Kellaway P, Petersen I, eds. Automation of Clinical Electroencephalography. New York, NY: Raven Press; 1973: John E, Ahn H, Trepetin M, Brown D, Kaye H. Developmental equations of the electroencephalogram. Science. 1980;210: Benninger C, Matthis P, Scheffner D. EEG development of healthy boys and girls: results of a longitudinal study. Electroencephalogr Clin Neurophysiol. 1984;57: Gasser T, Verleger R, Bacher P, Sroka L. Development of the EEG of school children and adolescents. I. Analysis of band power. Electroencephalogr Clin Neurophysiol. 1988;69:
13 Markovska-Simoska and Pop-Jordanova Conners CK. Rating scales in attention-deficit/hyperactivity disorder: use in assessment and treatment monitoring. J Clin Psychiatry. 1998;59 (suppl 7): Conners CK. Clinical use of rating scales in diagnosis and treatment of attention-deficit/hyperactivity disorder. Pediatr Clin North Am. 1999;46: Barkley RA, Murphy KR. Attention-Deficit Hyperactivity Disorder A Clinical Workbook. 3rd ed. New York, NY: Guilford Press; Vigário RN. Extraction of ocular artefacts from EEG using independent component analysis. Electroencephalogr Clin Neurophysiol. 1997;103: Loo SK, Cho A, Hale TS, McGough JJ, McCracken JT, Smalley SL. Characterization of the theta to beta ratio in ADHD: identifying potential sources of heterogeneity. J Atten Disord. 2013;17: Janzen T, Graap K, Stephanson S, Marshall W, Fitzsimmons G. Differences in baseline EEG measures for ADD and normally achieving preadolescent males. Biofeedback Self Regul. 1995;20: Chabot RJ, Merkin H, Wood LM, Davenport TL, Serfontein G. Sensitivity and specificity of QEEG in children with attention deficit or specific developmental learning disorders. Clin Electroencephalogr. 1996;27: Clarke AR, Barry RJ, McCarthy R, Selikowitz M. EEG-defined subtypes of children with attention-deficit/hyperactivity disorder. Clin Neurophysiol. 2001;112: Barry RJ, Clarke AR. Spontaneous EEG oscillations in children, adolescents, and adults typical development, and pathological aspects in relation to AD/HD. J Psychophysiol. 2009;23: Niedermeyer E, Lopes da Silva F, eds. Electroencephalography: Basic Principles, Clinical Applications, and Related Fields. 4th ed. Baltimore, MD: Williams & Wilkins; Puligheddu M, Munck JC, Stam CJ, et al. Age distribution of MEG spontaneous theta activity in healthy subjects. Brain Topogr. 2005;17: Clarke AR, Barry RJ, McCarthy R, Selikowitz M. Excess beta activity in children with attention-deficit/hyperactivity disorder: an atypical electrophysiological group. Psychiatry Res. 2001;103: Buyck I, Wiersema JR. Resting electroencephalogram in attention deficit hyperactivity disorder: developmental course and diagnostic value. Psychiatry Res. 2014;216: US Food and Drug Administration. FDA permits marketing of first brain wave test to help assess children and teens for ADHD. July 14, PressAnnouncements/ucm htm. Accessed September 4, Barriga-Paulino CI, Flores AB, Gómez CM. Developmental changes in the EEG rhythms of children and young adults: analyzed by means of correlational, brain topography and principal component analysis. J Psychophysiol. 2011;25: Whitford T, Rennie C, Grieve S, Clark C, Gordon E, Williams L. Brain maturation in adolescence. Concurrent changes in neuroanatomy and neurophysiology. Hum Brain Mapp. 2007;28: Durston S, van Belle J, de Zeeuw P. Differentiating frontostriatal and fronto-cerebellar circuits in attention-deficit/hyperactivity disorder. Biol Psychiatry. 2011;69: Cubillo A, Halari R, Smith A, Taylor E, Rubia K. A review of fronto-striatal and fronto-cortical brain abnormalities in children and adults with attention deficit hyperactivity disorder (ADHD) and new evidence for dysfunction in adults with ADHD during motivation and attention. Cortex. 2012;48: Sangal RB, Sangal JM. Use of EEG beta-1 power and theta/ beta ratio over Broca s area to confirm diagnosis of attention deficit/hyperactivity disorder in children. Clin EEG Neurosci. 2015;46: