584056
research-article2015
JADXXX10.1177/1087054715584056Journal of Attention DisordersMaoz et al.
Article
Association Between Continuous Performance and Response Inhibition Tests in Adults With ADHD
Journal of Attention Disorders 1–7 © 2015 SAGE Publications Reprints and permissions: sagepub.com/journalsPermissions.nav DOI: 10.1177/1087054715584056 jad.sagepub.com
Hagai Maoz1,2, Shai Aviram1,3, Uri Nitzan1,2, Aviv Segev1,2, and Yuval Bloch1,2
Abstract Objective: The study of ADHD uses various computerized tests to assess cognitive functions. Uncertainty exists regarding the association between deficits found by different tools testing similar or different cognitive functions (e.g., continuous performance tests [CPT] and response inhibition [RI] tests).We hypothesized that different tools that measure continuous performance will be better correlated between themselves than with a tool that examines RI. Method: Thirty-six adults with ADHD performed two different CPTs and a RI task. We analyzed correlations between different measures examined by the tasks. Results: There were strong correlations between corresponding measures in the CPTs. Correlations between the results in CPT and the RI task were only minimal. Conclusion: These findings support the specificity of impairments in different cognitive domains (continuous attention vs. RI) beyond the specific test used in the study of ADHD. Also, these findings strengthen the importance of specific discriminative cognitive domains in ADHD. (J. of Att. Dis. XXXX; XX(X) XX-XX) Keywords continuous performance, response inhibition, executive functions
Introduction ADHD is a prevalent neurodevelopmental disorder usually first diagnosed in childhood but with symptoms that tend to persist into adolescence and adulthood. The diagnosis of ADHD is based on behavioral symptoms clustered into inattention, hyperactivity, and impulsivity. Conceptually, these behaviors are caused by cognitive deficits that reflect malfunction of different neuronal networks (Cortese et al., 2012). Several neurocognitive tests have been developed for research in ADHD, as well as auxiliary instruments for diagnosis and assessment of treatment efficacy in children and adults with ADHD (Bloch et al., 2012; Gallagher & Blader, 2001; McGough & Barkley, 2004). When developing computerized cognitive tasks, researchers base their tools on the hypothesized impaired cognitive function that they demand. ADHD tests usually focus on the evaluation of executive functions and working memory (Gallagher & Blader, 2001; Willcutt, Doyle, Nigg, Faraone, & Pennington, 2005). However, heterogeneity exists between tools that allegedly examine similar cognitive functions. This heterogeneity might contribute to the complexity of generalizing concepts from findings of different studies. Meta-analyses and reviews show that executive function processes demonstrate considerable variability in ADHD samples, with only
a proportion of participants with ADHD displaying impairment in one or more of these measures (Nigg, Willcutt, Doyle, & Sonuga-Barke, 2005; Willcutt et al., 2005). In addition, different executive functions (EFs) tend to correlate with one another. For example, Freedman et al. have shown substantial correlations among three EF latent variables (updating, shifting, and inhibition; Friedman, Miyake, Robinson, & Hewitt, 2011). Therefore, differences between testing tools might have an important ramification when trying to integrate or compare results from different studies assessing similar cognitive functions (Corkum & Siegel, 1993; Nigg, 2005). Several laboratory tests have been developed to assess continuous performance, one of the key cognitive domains known to be impaired in ADHD (Seidman et al., 2004; Willcutt et al., 2005). The basic paradigm of a continuous performance test (CPT) involves selective attention or vigilance for an infrequently occurring stimulus (Eliason & 1
Shalvata Mental Health Care Center, Hod-Hasharon, Israel Tel-Aviv University, Israel 3 Haifa University, Israel 2
Corresponding Author: Hagai Maoz, The Emotion-Cognition Research Center, Shalvata Mental Health Care Center, Hod-Hasharon 45100, Israel. Email: [email protected]
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Richman, 1987). CPTs are generally characterized by rapid presentation of continuously changing stimuli among which there is a designated “target” stimulus or pattern. The duration of the tasks varies, but all are intended to be of sufficient length to measure sustained attention. Various components of the CPT tasks have been found to be associated with altered dopaminergic functioning in the mesolimbic cortical branch (Huang-Pollock, Karalunas, Tam, & Moore, 2012). For many years, the CPT has been used in the study of attention, as well as impulsivity, with consistent findings of sensitivity to central nervous system dysfunction (Riccio, Waldrop, Reynolds, & Lowe, 2001). However, extensive variations in CPT paradigms exist (HuangPollock et al., 2012; Riccio, Reynolds, Lowe, & Moore, 2002). For example, different CPT tasks include varying amounts of target stimuli. Also, some tasks require the identification of a single stimulus (i.e., the Test of Variables of Attention [TOVA]; Greenberg & Waldman, 1993), while others require identification of a sequence of stimuli (i.e., the Rapid Visual Processing [RVP] test; Gau & Huang, 2014). Variations in CPT types may affect the level of their sensitivity. The abundance of variations in task parameters as well as CPT demands makes generalization of performance data difficult, particularly with regard to attentional asymmetry (Riccio et al., 2001). Furthermore, the large number of CPT versions is a vexing disadvantage when trying to quantitatively synthesize data from different studies (e.g., through meta-analysis). Despite the extensive literature concerning CPTs in children and adults with ADHD, no study to date has examined the relative sensitivity of different CPT tasks or score types. In addition to the CPT, other tests measure response inhibition, another fundamental executive control process that comes into play in situations requiring withholding, switching, or suddenly interrupting ongoing actions and thoughts (Doyle, 2006). Deficient inhibitory control is mainly a result of frontal or prefrontal lobe dysfunction (Homack & Riccio, 2004), and is a well-replicated finding in children and adults with ADHD (Oosterlaan, Logan, & Sergeant, 1998; Schachar, Mota, Logan, Tannock, & Klim, 2000; Seidman et al., 2004; Willcutt et al., 2005). The Stroop inhibitory control was found in a number of studies (Barkley, 1997a; Soreni, Crosbie, Ickowicz, & Schachar, 2009) but not all (Schwartz & Verhaeghen, 2008; van Mourik, Oosterlaan, & Sergeant, 2005), to reflect impairments in response inhibition in individuals with ADHD. Given the fact that continuous performance and inhibitory control represent different executive functions that are dependent on different brain areas, there is a need to verify whether the segregation between different paradigms is indeed validated. The main purpose of the present study was to validate the hypothesis that different CPTs indeed measure similar performances and correlate in their results in adults with ADHD (i.e., whether impairments in one CPT
are correlated with parallel impairments as reflected in another type of CPT). To substantiate the specificity of this function, we compared the two different CPT batteries with a response inhibition test (RIT) to validate the differentiation between CPTs and RITs. Our hypothesis was that the two CPTs will highly correlate in the main domains being examined (e.g., reaction time [RT], accuracy).
Method Participants Participants in the study were 36 consecutive patients suffering from adult ADHD. Participants were recruited from the outpatient clinic of Shalvata Mental Health Center, School of Medicine Tel-Aviv University. Patients were diagnosed by a psychiatrist experienced in adult ADHD. The diagnosis was based on clinical interviews and was also assisted by the Adult ADHD Self Report Scale (ASRS; Kessler et al., 2005) and the Wender–Utah Adult ADHD Scale (WUAAS; Ward, Wender, & Reimherr, 1993). At the time of diagnosis, none of the patients was taking pharmacological treatment. Patients with other psychiatric disorders, which could affect their performance in the cognitive tests (e.g., history of neurologic disease, major depression, and severe anxiety), were excluded. The study was approved by the institutional review board, and all patients signed an informed consent form.
Procedure All patients performed two continuous performance tests— the TOVA and the RVP. In addition, all participants performed a RIT—the Stroop test. TOVA. This test uses geometric stimuli. The participant is instructed to press a button for every target and inhibit his or her response for every non-target. Stimuli (targets and nontargets) are presented at a rate of 1 every 2 s for 21 min. Each presentation is flashed for 100 ms and then removed until the presentation of the next stimulus. The test contains two conditions: target infrequent and target frequent. Variables measured and analyzed include response time (time between stimuli presentation and response), variability of response time (consistency), errors of commissions (response given when there was no stimulus—reflecting mainly response inhibition), errors of omission (no response when a stimuli was presented—reflecting sustained attention), and ADHD score, which is a comparison with an age-/gender-specific ADHD group. Impaired TOVA (Greenberg, Kindschi, & Corman, 2000) results in adults with ADHD were shown to be associated with disturbed fronto-striatal circuitry (Konrad et al., 2010). Extensive studies show that the TOVA has high internal consistency.
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Maoz et al. However, its moderate sensitivity and specificity in diagnosing ADHD limit it as a diagnostic tool (Greenberg & Waldman, 1993; Llorente et al., 2001; Preston, Fennell, & Bussing, 2005). RVP. This task is part of the CPT test used in the Cambridge Neuropsychological Test Automated Battery (CANTAB). The CANTAB uses a computer with a touch screen. In the RVP, the participant is required to detect three target sequences consisting of three digits each among serially appearing digits. The nine RVP (Robbins et al., 1998) outcome measures include latency, hits, misses, false alarms, correct rejections, probabilities, and sensitivity. The RVP belongs to the more complicated “A-X” CPTs. Thus, it includes a more complicated response inhibition—not to react when the last digit was presented but not preceded by the correct sequence. Variables that were measured included A′ (a measure of the ability of the examinee to detect target sequences using probability of hits and probability of false alarm), B″ (a measure of the tendency to respond regardless of whether the target sequence is present—response inhibition), and mean latency. The RVP task involves activation of the bilateral inferior frontal gyrus, parietal cortex, fusiform gyrus, and right frontal superior gyrus (Gau & Huang, 2014). The Stroop color–word test. This test was originally developed to measure selective attention and cognitive flexibility. However, throughout the years, it has also been used to measure cognitive inhibition (Homack & Riccio, 2004). The task contains three components. First, the individual is asked to name a series of color words (Word task). This component reflects basic reading rate and may be affected by speech motor problems or learning disabilities. Second, the participant is instructed to name the color of a bar (Color task). Performance in this task may be affected by speech motor function, the individual’s ability to name colors, or colorblindness. The final task, the Color–Word task, contains two conditions—: In the congruent condition, the name of the color is written in the same color, and in the incongruent condition, the words (“red,” “blue,” “green”) are in incongruent color (e.g., the word “blue” appears in red). The participant is requested to name the color of the letters, thereby inhibiting the prepotent response of reading the word. This task mainly measures mental flexibility and the ability to inhibit a dominant response (Golden, EspePfeifer, & Waschler-Fedler, 2000). Neuroimaging studies show that the brain areas that are active, while participants perform Stroop-like tasks, include the anterior cingulate cortex, the anterior prefrontal cortex, the inferior frontal regions, and the inferior parietal lobule (van Mourik et al., 2005). As can be seen, the Stroop test (Stroop, 1935) suffers from task-impurity problem because it includes systematic variance also attributed to non-EF processes (e.g., color
processing, articulation speed; Miyake & Friedman, 2012). Individuals with ADHD were found to have impaired response inhibition compared with age-matched controls (Barkley, 1997b; van Mourik et al., 2005), and lower scores in both reading ability (word condition) and naming speed (color condition; Doyle, Biederman, Seidman, Weber, & Faraone, 2000; Semrud-Clikeman et al., 1992; Tannock, Martinussen, & Frijters, 2000; van Mourik et al., 2005). We used the computerized version of the task.
Statistical Analysis Scores of the different batteries were calculated using manuals of each specific battery. Pearson correlation coefficient was used to determine correlations between TOVA, RVP, and Stroop scores. Data were analyzed using the statistical software package SPSS, Version 19.0.
Results Thirty-six patients participated in the study (age 30.7 ± 5.1, 61% males; 16 patients with ADHD–Inattentive type, 7 with ADHD–Hyperactive/Impulsive type, and 13 with ADHD–Combined type). The mean ASRS total score was 61.3 ± 11.4, and the mean WUAAS was 44.8 ± 16.5.
TOVA The mean ADHD score was −9.22 ± 9.5. All TOVA parameters were lower than the norm (RT 79.6 ± 24.1 ms, omissions 64.7 ± 25.7, and commissions 84.6 ± 25.2). There were no statistically significant differences in any of the variables between subgroups of patients, except for lower commission scores in patients with ADHD–Combined and ADHD–Hyperactive/Impulsive when compared with patients with ADHD–Inattentive (p = .03 and p = .02, respectively).
RVP The mean RVP A′ was 0.89 ± 0.05, and mean B″ was 0.96 ± 0.06 (both lower from the adjusted norm—15th and 40th percentile, respectively). The mean latency was 521.65 ± 136.22 ms. There were no statistically significant betweengroup differences, except for lower B″ scores in patients with ADHD–Combined and ADHD–Hyperactive/Impulsive when compared with patients with ADHD–Inattentive (p = .02 and p = .05, respectively). Similar differences were found in the probability of false alarm.
Stroop The mean RT for both congruent and incongruent conditions were lower than norm (Barbarotto et al., 1998). RT for
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Table 1. Correlation Matrix Between TOVA and RVP. TOVA Measures RVP A′ B″ M Latency Probability of false alarm Probability of hit
Omissions .514** .261 −.427* −.269 .496**
Commissions .069 .574** −.091 .581** −.004
RT
Variability
d′ prime
ADHD score
.296 .327 −.628** −.408* .254
.408* .269 −.455** −.283 .378*
.615** .127 −.322 −.167 .622**
.392* .180 −.735** −.254 .368*
Note. TOVA = Test of Variables of Attention; RVP = Rapid Visual Processing; RT = reaction time. *Significant at level ≤ .05. **Significant at level ≤ .01.
Table 2. Correlation Matrix Between Stroop and TOVA and RVP. Stroop Measures TOVA Omission Commission RT Variability d′ prime ADHD score RVP A′ B″ M latency Probability of false alarm Probability of hit
Congruent RT
Non-congruent RT
Stroop effect
−.059 .128 −.262 −.243 −.131 −.155
−.200 −.037 −.287 −.424* −.213 −.418*
−.171 −.252 .034 −.178 −.075 −.310
.042 −.019 .319 .041 .052
−.037 −.158 .444** .195 −.011
−.117 −.182 .087 .197 −.098
Note. TOVA = Test of Variables of Attention; RVP = Rapid Visual Processing; RT = reaction time. *Significant at level ≤ .05. **Significant at level ≤ .01.
the congruent condition was 836.12 ± 147.63 ms (norm 145 ± 66) and for the incongruent condition, 918.34 ± 132.89 ms (norm 285 ± 117). There were no statistically significant differences in Stroop effect between ADHD subgroups. Significant correlations were found between parallel items in the two CPT tasks that were examined (Table 1). For example, there was a significant correlation between RT as measured by the TOVA and mean latency as measured by the RVP (r = −.628, p ≤ .01). Also, there were significant correlations between the measure of omissions in the TOVA and probability of hit and A′ in the RVP (r = .514, p ≤ .01), and between the measures of commission in the TOVA and probability of false alarm and B″ in the RVP (r = .581 and r = .574, respectively, all p values ≤ .01). The variability measure in the TOVA was highly correlated with A′ and mean latency in the RVP (r = .408 and r = −.455 respectively, all p values ≤ .05). ADHD score in the TOVA was mostly correlated with mean latency in the RVP (r = −.735, p ≤ .01). The d′, which is a measure of the rate of
deterioration in performance over time, was highly correlated with the RVP A′ and probability of hit (rs = .615 and .622 respectively, all p values ≤ .01). In contrast to the significant correlation between the two models of CPT, there were almost no correlations between scores of either of these tests and the Stroop test (Table 2). The only correlation found was between the non-congruent RT in the Stroop and ADHD score and the variability measure in TOVA and mean latency measure in the RVP (rs = −.418, −.424, and .444, respectively, all p values ≤ .05).
Discussion Many different cognitive tasks have been developed for clinical and research use in children and adults with ADHD. Some of these tools, allegedly measuring similar cognitive functions, might be significantly different. Comprehending the similarities and dissimilarities between different diagnostic tools is part of the understanding of different domains
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Maoz et al. affected in ADHD. In this study, similar domains in the CPTs (i.e., TOVA and RVP) were highly correlated, while results in the Stroop test, mainly measuring response inhibition, had only minimal correlation with the results of the two CPTs. These findings suggest that despite common underlying abilities, there is still importance in specifying discriminative impaired cognitive domains in ADHD. The main purpose of continuous performance tasks is to examine vigilance and sustained attention. However, the two CPT tests that were used in our study are different, and therefore, it is not intuitive that they will yield similar results. While the TOVA uses single target detection, the RVP uses a sequence of numbers and is also dependent on working memory, known to be impaired in patients with ADHD (Alderson, Kasper, Hudec, & Patros, 2013). Sustained attention is mainly dependent on the lateral fronto-striato-parietal regions, while the working memory also relies on the dorso-lateral prefrontal cortex. The correlations found in our study between corresponding measures in the TOVA and RVP imply that although these tasks are not identical, they indeed measure the same domain of sustained attention. Nonetheless, the correlations between corresponding measures were only moderate-strong, reflecting also important differences between the tasks. For example, it is possible that the inhibition required by the RVP task is more complicated than inhibition required by the TOVA and requires activation of additional brain areas, because the sequence of numbers creates additional anticipation of the examinee to react to an anticipated stimulus. The absence of correlation between results in the CPT and the Stroop test, measuring mainly response inhibition, suggests that these two different domains might be separately affected in ADHD. Hence, poor result in the measure of RT in the CPT (either TOVA or RVP) probably reflects deficiency in a different domain from RT measured by the Stroop test. Previous studies showed that impulsive type errors in the CPT (e.g., commission errors) were elevated in psychiatric groups characterized by impulsive behavior such as adolescents with disruptive behavior disorders (Dougherty et al., 2003). Interestingly, we found significant correlation between measures of response time in the CPTs and the Stroop’s non-congruent condition but not the congruent condition. However, we found no correlations between commission errors in the TOVA or B″ in the RVP and the Stroop’s non-congruent condition. This might support the view that it is the intensification caused by the combined effect of different cognitive malfunctions that causes in diverse venues the severity of the clinical picture. When relating to theories and concepts regarding ADHD, some researchers have abandoned specific cognitive theories and address a more general malfunction related mainly to motivation as expressed by processes of reward. These include, for example, reduced response to punishment and non-reward (Quay, 1997), sensitivity to removal of reward
(Douglas & Parry, 1994), delay aversion (Sonuga-Barke, Dalen, & Remington, 2003), and deficient extinction processes (Sagvolden, Johansen, Aase, & Russell, 2005). In contrast, findings of differentiation in performance in different tests (with a possible additive effect as discussed above) support the role of cognitive domains in the subtyping of ADHD. Therefore, the results of the present study strengthen the hypothesis that ADHD symptomatology is dependent on impairments in different domains and that impairment in one domain is not necessarily associated with impairment in another one. These results also support the view that execution of CPTs is associated with cerebral asymmetric activation such that individuals with right hemisphere damage show longer response time in simple RT tests compared with individuals with left hemisphere damage, while CPT demands greater left hemisphere involvement (Riccio et al., 2002). This hypothesis is also supported by neuroimaging studies that found only partial overlap between activated areas while performing the Stroop test or the CPT (Schneider et al., 2010; van Mourik et al., 2005). It is important to stress some limitations of the study. First, our sample was small, and relevant confounders (e.g., gender, learning disabilities) could not be addressed. Some of the correlations that were found moderate might have been stronger if the sample size was larger. In addition, we could not address different dimensions of ADHD separately (e.g., impulsivity). Second, we did not have a control group. Third, patients were not randomly assigned to perform the tests in different order. Finally, we did not compare performance under medication examining correlations in improvement in performance. In conclusion, the present study supports the specificity of the different cognitive domains (continuous attention vs. response inhibition) beyond the tests used (TOVA vs. RVP) in the study of ADHD. Declaration of Conflicting Interests The author(s) declared no potential 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.
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Test–retest reliability of two inhibition measures in ADHD children. Journal of Attention Disorders, 13, 137-143. doi:10.1177/1087054708326110 Stroop, J. R. (1935). Studies of interference in serial verbal reactions. Journal of Experimental Psychology, 18, 643-662. Tannock, R., Martinussen, R., & Frijters, J. (2000). Naming speed performance and stimulant effects indicate effortful, semantic processing deficits in attention-deficit/hyperactivity disorder. Journal of Abnormal Child Psychology, 28, 237-252. van Mourik, R., Oosterlaan, J., & Sergeant, J. A. (2005). The Stroop revisited: A meta-analysis of interference control in AD/HD. Journal of Child Psychology and Psychiatry, 46, 150-165. doi:10.1111/j.1469-7610.2004.00345.x Ward, M. F., Wender, P. H., & Reimherr, F. W. (1993). The Wender Utah Rating Scale: An aid in the retrospective diagnosis of childhood attention deficit hyperactivity disorder. American Journal of Psychiatry, 150, 885-890. Willcutt, E. G., Doyle, A. E., Nigg, J. T., Faraone, S. V., & Pennington, B. F. (2005). Validity of the executive function theory of attention-deficit/hyperactivity disorder: A meta-analytic review. Biological Psychiatry, 57, 1336-1346. doi:10.1016/j.biopsych.2005.02.006
Author Biographies Hagai Maoz, MD, is a senior psychiatrist in the child and adolescent psychiatric outpatient clinic and a researcher in the cognitiveemotion research lab in Shalvata Mental Health Center. His main field of research areas are mood disorders and ADHD, focusing mainly on social cognition and executive functions in these disorders. Shai Aviram, MA, is a student in cognitive psychology at Haifa University. He is a research assistant and statistical consultant at the cognitive-emotion research lab, Shalvata Mental Health Care Center. Uri Nitzan, MD, works as a senior psychiatrist in a psychiatric department and in the brain stimulation unit of the hospital. His central fields of interest are resistant depression, placebo effect, and adherence to treatment. Aviv Segev, MD, is a senior psychiatrist at Shalvata Mental Health Care Center. He studies the interactions of psychopathology and computer games, as well as biological correlates of schizophrenia and other severe mental disorders. Yuval Bloch, MD, is the director of the child and adolescent psychiatric outpatient clinic and a senior researcher in the cognitiveemotion research lab in Shalvata Mental Health Center. He is a lecturer in Tel-Aviv University medical school. Central fields of interest include brain stimulation, and cognitive and emotional assessment in different mental disorders especially ADHD.
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research-article2015
JADXXX10.1177/1087054715584056Journal of Attention DisordersMaoz et al.
Article
Association Between Continuous Performance and Response Inhibition Tests in Adults With ADHD
Journal of Attention Disorders 1–7 © 2015 SAGE Publications Reprints and permissions: sagepub.com/journalsPermissions.nav DOI: 10.1177/1087054715584056 jad.sagepub.com
Hagai Maoz1,2, Shai Aviram1,3, Uri Nitzan1,2, Aviv Segev1,2, and Yuval Bloch1,2
Abstract Objective: The study of ADHD uses various computerized tests to assess cognitive functions. Uncertainty exists regarding the association between deficits found by different tools testing similar or different cognitive functions (e.g., continuous performance tests [CPT] and response inhibition [RI] tests).We hypothesized that different tools that measure continuous performance will be better correlated between themselves than with a tool that examines RI. Method: Thirty-six adults with ADHD performed two different CPTs and a RI task. We analyzed correlations between different measures examined by the tasks. Results: There were strong correlations between corresponding measures in the CPTs. Correlations between the results in CPT and the RI task were only minimal. Conclusion: These findings support the specificity of impairments in different cognitive domains (continuous attention vs. RI) beyond the specific test used in the study of ADHD. Also, these findings strengthen the importance of specific discriminative cognitive domains in ADHD. (J. of Att. Dis. XXXX; XX(X) XX-XX) Keywords continuous performance, response inhibition, executive functions
Introduction ADHD is a prevalent neurodevelopmental disorder usually first diagnosed in childhood but with symptoms that tend to persist into adolescence and adulthood. The diagnosis of ADHD is based on behavioral symptoms clustered into inattention, hyperactivity, and impulsivity. Conceptually, these behaviors are caused by cognitive deficits that reflect malfunction of different neuronal networks (Cortese et al., 2012). Several neurocognitive tests have been developed for research in ADHD, as well as auxiliary instruments for diagnosis and assessment of treatment efficacy in children and adults with ADHD (Bloch et al., 2012; Gallagher & Blader, 2001; McGough & Barkley, 2004). When developing computerized cognitive tasks, researchers base their tools on the hypothesized impaired cognitive function that they demand. ADHD tests usually focus on the evaluation of executive functions and working memory (Gallagher & Blader, 2001; Willcutt, Doyle, Nigg, Faraone, & Pennington, 2005). However, heterogeneity exists between tools that allegedly examine similar cognitive functions. This heterogeneity might contribute to the complexity of generalizing concepts from findings of different studies. Meta-analyses and reviews show that executive function processes demonstrate considerable variability in ADHD samples, with only
a proportion of participants with ADHD displaying impairment in one or more of these measures (Nigg, Willcutt, Doyle, & Sonuga-Barke, 2005; Willcutt et al., 2005). In addition, different executive functions (EFs) tend to correlate with one another. For example, Freedman et al. have shown substantial correlations among three EF latent variables (updating, shifting, and inhibition; Friedman, Miyake, Robinson, & Hewitt, 2011). Therefore, differences between testing tools might have an important ramification when trying to integrate or compare results from different studies assessing similar cognitive functions (Corkum & Siegel, 1993; Nigg, 2005). Several laboratory tests have been developed to assess continuous performance, one of the key cognitive domains known to be impaired in ADHD (Seidman et al., 2004; Willcutt et al., 2005). The basic paradigm of a continuous performance test (CPT) involves selective attention or vigilance for an infrequently occurring stimulus (Eliason & 1
Shalvata Mental Health Care Center, Hod-Hasharon, Israel Tel-Aviv University, Israel 3 Haifa University, Israel 2
Corresponding Author: Hagai Maoz, The Emotion-Cognition Research Center, Shalvata Mental Health Care Center, Hod-Hasharon 45100, Israel. Email: [email protected]
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Richman, 1987). CPTs are generally characterized by rapid presentation of continuously changing stimuli among which there is a designated “target” stimulus or pattern. The duration of the tasks varies, but all are intended to be of sufficient length to measure sustained attention. Various components of the CPT tasks have been found to be associated with altered dopaminergic functioning in the mesolimbic cortical branch (Huang-Pollock, Karalunas, Tam, & Moore, 2012). For many years, the CPT has been used in the study of attention, as well as impulsivity, with consistent findings of sensitivity to central nervous system dysfunction (Riccio, Waldrop, Reynolds, & Lowe, 2001). However, extensive variations in CPT paradigms exist (HuangPollock et al., 2012; Riccio, Reynolds, Lowe, & Moore, 2002). For example, different CPT tasks include varying amounts of target stimuli. Also, some tasks require the identification of a single stimulus (i.e., the Test of Variables of Attention [TOVA]; Greenberg & Waldman, 1993), while others require identification of a sequence of stimuli (i.e., the Rapid Visual Processing [RVP] test; Gau & Huang, 2014). Variations in CPT types may affect the level of their sensitivity. The abundance of variations in task parameters as well as CPT demands makes generalization of performance data difficult, particularly with regard to attentional asymmetry (Riccio et al., 2001). Furthermore, the large number of CPT versions is a vexing disadvantage when trying to quantitatively synthesize data from different studies (e.g., through meta-analysis). Despite the extensive literature concerning CPTs in children and adults with ADHD, no study to date has examined the relative sensitivity of different CPT tasks or score types. In addition to the CPT, other tests measure response inhibition, another fundamental executive control process that comes into play in situations requiring withholding, switching, or suddenly interrupting ongoing actions and thoughts (Doyle, 2006). Deficient inhibitory control is mainly a result of frontal or prefrontal lobe dysfunction (Homack & Riccio, 2004), and is a well-replicated finding in children and adults with ADHD (Oosterlaan, Logan, & Sergeant, 1998; Schachar, Mota, Logan, Tannock, & Klim, 2000; Seidman et al., 2004; Willcutt et al., 2005). The Stroop inhibitory control was found in a number of studies (Barkley, 1997a; Soreni, Crosbie, Ickowicz, & Schachar, 2009) but not all (Schwartz & Verhaeghen, 2008; van Mourik, Oosterlaan, & Sergeant, 2005), to reflect impairments in response inhibition in individuals with ADHD. Given the fact that continuous performance and inhibitory control represent different executive functions that are dependent on different brain areas, there is a need to verify whether the segregation between different paradigms is indeed validated. The main purpose of the present study was to validate the hypothesis that different CPTs indeed measure similar performances and correlate in their results in adults with ADHD (i.e., whether impairments in one CPT
are correlated with parallel impairments as reflected in another type of CPT). To substantiate the specificity of this function, we compared the two different CPT batteries with a response inhibition test (RIT) to validate the differentiation between CPTs and RITs. Our hypothesis was that the two CPTs will highly correlate in the main domains being examined (e.g., reaction time [RT], accuracy).
Method Participants Participants in the study were 36 consecutive patients suffering from adult ADHD. Participants were recruited from the outpatient clinic of Shalvata Mental Health Center, School of Medicine Tel-Aviv University. Patients were diagnosed by a psychiatrist experienced in adult ADHD. The diagnosis was based on clinical interviews and was also assisted by the Adult ADHD Self Report Scale (ASRS; Kessler et al., 2005) and the Wender–Utah Adult ADHD Scale (WUAAS; Ward, Wender, & Reimherr, 1993). At the time of diagnosis, none of the patients was taking pharmacological treatment. Patients with other psychiatric disorders, which could affect their performance in the cognitive tests (e.g., history of neurologic disease, major depression, and severe anxiety), were excluded. The study was approved by the institutional review board, and all patients signed an informed consent form.
Procedure All patients performed two continuous performance tests— the TOVA and the RVP. In addition, all participants performed a RIT—the Stroop test. TOVA. This test uses geometric stimuli. The participant is instructed to press a button for every target and inhibit his or her response for every non-target. Stimuli (targets and nontargets) are presented at a rate of 1 every 2 s for 21 min. Each presentation is flashed for 100 ms and then removed until the presentation of the next stimulus. The test contains two conditions: target infrequent and target frequent. Variables measured and analyzed include response time (time between stimuli presentation and response), variability of response time (consistency), errors of commissions (response given when there was no stimulus—reflecting mainly response inhibition), errors of omission (no response when a stimuli was presented—reflecting sustained attention), and ADHD score, which is a comparison with an age-/gender-specific ADHD group. Impaired TOVA (Greenberg, Kindschi, & Corman, 2000) results in adults with ADHD were shown to be associated with disturbed fronto-striatal circuitry (Konrad et al., 2010). Extensive studies show that the TOVA has high internal consistency.
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Maoz et al. However, its moderate sensitivity and specificity in diagnosing ADHD limit it as a diagnostic tool (Greenberg & Waldman, 1993; Llorente et al., 2001; Preston, Fennell, & Bussing, 2005). RVP. This task is part of the CPT test used in the Cambridge Neuropsychological Test Automated Battery (CANTAB). The CANTAB uses a computer with a touch screen. In the RVP, the participant is required to detect three target sequences consisting of three digits each among serially appearing digits. The nine RVP (Robbins et al., 1998) outcome measures include latency, hits, misses, false alarms, correct rejections, probabilities, and sensitivity. The RVP belongs to the more complicated “A-X” CPTs. Thus, it includes a more complicated response inhibition—not to react when the last digit was presented but not preceded by the correct sequence. Variables that were measured included A′ (a measure of the ability of the examinee to detect target sequences using probability of hits and probability of false alarm), B″ (a measure of the tendency to respond regardless of whether the target sequence is present—response inhibition), and mean latency. The RVP task involves activation of the bilateral inferior frontal gyrus, parietal cortex, fusiform gyrus, and right frontal superior gyrus (Gau & Huang, 2014). The Stroop color–word test. This test was originally developed to measure selective attention and cognitive flexibility. However, throughout the years, it has also been used to measure cognitive inhibition (Homack & Riccio, 2004). The task contains three components. First, the individual is asked to name a series of color words (Word task). This component reflects basic reading rate and may be affected by speech motor problems or learning disabilities. Second, the participant is instructed to name the color of a bar (Color task). Performance in this task may be affected by speech motor function, the individual’s ability to name colors, or colorblindness. The final task, the Color–Word task, contains two conditions—: In the congruent condition, the name of the color is written in the same color, and in the incongruent condition, the words (“red,” “blue,” “green”) are in incongruent color (e.g., the word “blue” appears in red). The participant is requested to name the color of the letters, thereby inhibiting the prepotent response of reading the word. This task mainly measures mental flexibility and the ability to inhibit a dominant response (Golden, EspePfeifer, & Waschler-Fedler, 2000). Neuroimaging studies show that the brain areas that are active, while participants perform Stroop-like tasks, include the anterior cingulate cortex, the anterior prefrontal cortex, the inferior frontal regions, and the inferior parietal lobule (van Mourik et al., 2005). As can be seen, the Stroop test (Stroop, 1935) suffers from task-impurity problem because it includes systematic variance also attributed to non-EF processes (e.g., color
processing, articulation speed; Miyake & Friedman, 2012). Individuals with ADHD were found to have impaired response inhibition compared with age-matched controls (Barkley, 1997b; van Mourik et al., 2005), and lower scores in both reading ability (word condition) and naming speed (color condition; Doyle, Biederman, Seidman, Weber, & Faraone, 2000; Semrud-Clikeman et al., 1992; Tannock, Martinussen, & Frijters, 2000; van Mourik et al., 2005). We used the computerized version of the task.
Statistical Analysis Scores of the different batteries were calculated using manuals of each specific battery. Pearson correlation coefficient was used to determine correlations between TOVA, RVP, and Stroop scores. Data were analyzed using the statistical software package SPSS, Version 19.0.
Results Thirty-six patients participated in the study (age 30.7 ± 5.1, 61% males; 16 patients with ADHD–Inattentive type, 7 with ADHD–Hyperactive/Impulsive type, and 13 with ADHD–Combined type). The mean ASRS total score was 61.3 ± 11.4, and the mean WUAAS was 44.8 ± 16.5.
TOVA The mean ADHD score was −9.22 ± 9.5. All TOVA parameters were lower than the norm (RT 79.6 ± 24.1 ms, omissions 64.7 ± 25.7, and commissions 84.6 ± 25.2). There were no statistically significant differences in any of the variables between subgroups of patients, except for lower commission scores in patients with ADHD–Combined and ADHD–Hyperactive/Impulsive when compared with patients with ADHD–Inattentive (p = .03 and p = .02, respectively).
RVP The mean RVP A′ was 0.89 ± 0.05, and mean B″ was 0.96 ± 0.06 (both lower from the adjusted norm—15th and 40th percentile, respectively). The mean latency was 521.65 ± 136.22 ms. There were no statistically significant betweengroup differences, except for lower B″ scores in patients with ADHD–Combined and ADHD–Hyperactive/Impulsive when compared with patients with ADHD–Inattentive (p = .02 and p = .05, respectively). Similar differences were found in the probability of false alarm.
Stroop The mean RT for both congruent and incongruent conditions were lower than norm (Barbarotto et al., 1998). RT for
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Table 1. Correlation Matrix Between TOVA and RVP. TOVA Measures RVP A′ B″ M Latency Probability of false alarm Probability of hit
Omissions .514** .261 −.427* −.269 .496**
Commissions .069 .574** −.091 .581** −.004
RT
Variability
d′ prime
ADHD score
.296 .327 −.628** −.408* .254
.408* .269 −.455** −.283 .378*
.615** .127 −.322 −.167 .622**
.392* .180 −.735** −.254 .368*
Note. TOVA = Test of Variables of Attention; RVP = Rapid Visual Processing; RT = reaction time. *Significant at level ≤ .05. **Significant at level ≤ .01.
Table 2. Correlation Matrix Between Stroop and TOVA and RVP. Stroop Measures TOVA Omission Commission RT Variability d′ prime ADHD score RVP A′ B″ M latency Probability of false alarm Probability of hit
Congruent RT
Non-congruent RT
Stroop effect
−.059 .128 −.262 −.243 −.131 −.155
−.200 −.037 −.287 −.424* −.213 −.418*
−.171 −.252 .034 −.178 −.075 −.310
.042 −.019 .319 .041 .052
−.037 −.158 .444** .195 −.011
−.117 −.182 .087 .197 −.098
Note. TOVA = Test of Variables of Attention; RVP = Rapid Visual Processing; RT = reaction time. *Significant at level ≤ .05. **Significant at level ≤ .01.
the congruent condition was 836.12 ± 147.63 ms (norm 145 ± 66) and for the incongruent condition, 918.34 ± 132.89 ms (norm 285 ± 117). There were no statistically significant differences in Stroop effect between ADHD subgroups. Significant correlations were found between parallel items in the two CPT tasks that were examined (Table 1). For example, there was a significant correlation between RT as measured by the TOVA and mean latency as measured by the RVP (r = −.628, p ≤ .01). Also, there were significant correlations between the measure of omissions in the TOVA and probability of hit and A′ in the RVP (r = .514, p ≤ .01), and between the measures of commission in the TOVA and probability of false alarm and B″ in the RVP (r = .581 and r = .574, respectively, all p values ≤ .01). The variability measure in the TOVA was highly correlated with A′ and mean latency in the RVP (r = .408 and r = −.455 respectively, all p values ≤ .05). ADHD score in the TOVA was mostly correlated with mean latency in the RVP (r = −.735, p ≤ .01). The d′, which is a measure of the rate of
deterioration in performance over time, was highly correlated with the RVP A′ and probability of hit (rs = .615 and .622 respectively, all p values ≤ .01). In contrast to the significant correlation between the two models of CPT, there were almost no correlations between scores of either of these tests and the Stroop test (Table 2). The only correlation found was between the non-congruent RT in the Stroop and ADHD score and the variability measure in TOVA and mean latency measure in the RVP (rs = −.418, −.424, and .444, respectively, all p values ≤ .05).
Discussion Many different cognitive tasks have been developed for clinical and research use in children and adults with ADHD. Some of these tools, allegedly measuring similar cognitive functions, might be significantly different. Comprehending the similarities and dissimilarities between different diagnostic tools is part of the understanding of different domains
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Maoz et al. affected in ADHD. In this study, similar domains in the CPTs (i.e., TOVA and RVP) were highly correlated, while results in the Stroop test, mainly measuring response inhibition, had only minimal correlation with the results of the two CPTs. These findings suggest that despite common underlying abilities, there is still importance in specifying discriminative impaired cognitive domains in ADHD. The main purpose of continuous performance tasks is to examine vigilance and sustained attention. However, the two CPT tests that were used in our study are different, and therefore, it is not intuitive that they will yield similar results. While the TOVA uses single target detection, the RVP uses a sequence of numbers and is also dependent on working memory, known to be impaired in patients with ADHD (Alderson, Kasper, Hudec, & Patros, 2013). Sustained attention is mainly dependent on the lateral fronto-striato-parietal regions, while the working memory also relies on the dorso-lateral prefrontal cortex. The correlations found in our study between corresponding measures in the TOVA and RVP imply that although these tasks are not identical, they indeed measure the same domain of sustained attention. Nonetheless, the correlations between corresponding measures were only moderate-strong, reflecting also important differences between the tasks. For example, it is possible that the inhibition required by the RVP task is more complicated than inhibition required by the TOVA and requires activation of additional brain areas, because the sequence of numbers creates additional anticipation of the examinee to react to an anticipated stimulus. The absence of correlation between results in the CPT and the Stroop test, measuring mainly response inhibition, suggests that these two different domains might be separately affected in ADHD. Hence, poor result in the measure of RT in the CPT (either TOVA or RVP) probably reflects deficiency in a different domain from RT measured by the Stroop test. Previous studies showed that impulsive type errors in the CPT (e.g., commission errors) were elevated in psychiatric groups characterized by impulsive behavior such as adolescents with disruptive behavior disorders (Dougherty et al., 2003). Interestingly, we found significant correlation between measures of response time in the CPTs and the Stroop’s non-congruent condition but not the congruent condition. However, we found no correlations between commission errors in the TOVA or B″ in the RVP and the Stroop’s non-congruent condition. This might support the view that it is the intensification caused by the combined effect of different cognitive malfunctions that causes in diverse venues the severity of the clinical picture. When relating to theories and concepts regarding ADHD, some researchers have abandoned specific cognitive theories and address a more general malfunction related mainly to motivation as expressed by processes of reward. These include, for example, reduced response to punishment and non-reward (Quay, 1997), sensitivity to removal of reward
(Douglas & Parry, 1994), delay aversion (Sonuga-Barke, Dalen, & Remington, 2003), and deficient extinction processes (Sagvolden, Johansen, Aase, & Russell, 2005). In contrast, findings of differentiation in performance in different tests (with a possible additive effect as discussed above) support the role of cognitive domains in the subtyping of ADHD. Therefore, the results of the present study strengthen the hypothesis that ADHD symptomatology is dependent on impairments in different domains and that impairment in one domain is not necessarily associated with impairment in another one. These results also support the view that execution of CPTs is associated with cerebral asymmetric activation such that individuals with right hemisphere damage show longer response time in simple RT tests compared with individuals with left hemisphere damage, while CPT demands greater left hemisphere involvement (Riccio et al., 2002). This hypothesis is also supported by neuroimaging studies that found only partial overlap between activated areas while performing the Stroop test or the CPT (Schneider et al., 2010; van Mourik et al., 2005). It is important to stress some limitations of the study. First, our sample was small, and relevant confounders (e.g., gender, learning disabilities) could not be addressed. Some of the correlations that were found moderate might have been stronger if the sample size was larger. In addition, we could not address different dimensions of ADHD separately (e.g., impulsivity). Second, we did not have a control group. Third, patients were not randomly assigned to perform the tests in different order. Finally, we did not compare performance under medication examining correlations in improvement in performance. In conclusion, the present study supports the specificity of the different cognitive domains (continuous attention vs. response inhibition) beyond the tests used (TOVA vs. RVP) in the study of ADHD. Declaration of Conflicting Interests The author(s) declared no potential 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.
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Author Biographies Hagai Maoz, MD, is a senior psychiatrist in the child and adolescent psychiatric outpatient clinic and a researcher in the cognitiveemotion research lab in Shalvata Mental Health Center. His main field of research areas are mood disorders and ADHD, focusing mainly on social cognition and executive functions in these disorders. Shai Aviram, MA, is a student in cognitive psychology at Haifa University. He is a research assistant and statistical consultant at the cognitive-emotion research lab, Shalvata Mental Health Care Center. Uri Nitzan, MD, works as a senior psychiatrist in a psychiatric department and in the brain stimulation unit of the hospital. His central fields of interest are resistant depression, placebo effect, and adherence to treatment. Aviv Segev, MD, is a senior psychiatrist at Shalvata Mental Health Care Center. He studies the interactions of psychopathology and computer games, as well as biological correlates of schizophrenia and other severe mental disorders. Yuval Bloch, MD, is the director of the child and adolescent psychiatric outpatient clinic and a senior researcher in the cognitiveemotion research lab in Shalvata Mental Health Center. He is a lecturer in Tel-Aviv University medical school. Central fields of interest include brain stimulation, and cognitive and emotional assessment in different mental disorders especially ADHD.
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