Week Ten:
ADHD and Development Lab


Carhart Fellow in Clinical Psychology

ADHD and Development Lab, University of Iowa | Iowa City, Iowa

August 6, 2015

This week I spent my time doing data collection and data entry. I had two lab visits this week, on Monday and Thursday, both of which were with individuals with ADHD. On Tuesday, Dr. Nikolas and I discussed articles. This week was the last full week of data collection, as many of the research assistants in the lab are leaving to go onto other opportunities elsewhere (e.g. graduate school, new jobs, etc.) and the graduate students are beginning to prepare for the upcoming semester. During our meeting on Tuesday, Dr. Nikolas and I discussed three articles, two of which focused on response inhibition and executive functioning while the other article focused on moderator genes of stress in ADHD.

Boonstra et al. (2010) examined response inhibition in an attempt to elaborate on the theory of ADHD as  primarily a disorder of response inhibition set forth by Barkley (1997), which begets a series of deficits in other executive functioning (EF) areas. Barkley (1997) is a highly important article as it set forth decades of research on ADHD. According to Barkley (1997), response inhibition is subdivided into three separable constructs: inhibition of proponent response, inhibition of ongoing response, and inference control. Boonstra et al. (2010) wanted to examine the validity of this conception of response inhibition and the theory, generally, in a sample of adults (n = 49). To examine the assertion response inhibition begets deficits in other EF, they were interested in correlations between deficits in response inhibition with EF that have been implicated in ADHD, namely verbal and nonverbal fluency, verbal and spatial working memory, planning, and set-shifting (i.e. the ability to update goal-oriented processes in response to changes in the environment). Since IQ and non-executive functioning related performance account at least some of the variance in performance on EF tasks, Boonstra and colleagues also intended to examine these relationships between response inhibition and EF when covarying IQ and performance on non-EF tasks.

Figure 1. Effects sizes before and after covarying for IQ and non-EF. Credit: Boonstra et al. (2010).
Figure 1. Effects sizes before and after covarying for IQ and non-EF. Credit: Boonstra et al. (2010).

Before controlling for IQ and non-EF performance, Boonstra and colleagues found was that were large group differences in response inhibition in the areas of inhibition of proponent response and interference control, but not inhibition of ongoing response. Additionally, large group differences were found on measures of set-shifting, while groups differences with medium effects were found in verbal working memory. After controlling for both IQ and non-EF demands in independent analyses, response inhibition was the only measure that remained significant, while other group differences were rendered not significant. There were no significant gender differences. Figure 1 describes these results. These findings may partially support the assertions of Barkley (1997), while at the same time present counter-evidence for some hypotheses. Deficits in response inhibition may characterize ADHD, but these deficits do not necessarily explain the presence of deficits in other executive functions. However, it likely criticize of Boonstra et al. (2010) is such that IQ co-varying for IQ may demote important differences between individuals with ADHD and individuals sub-clinical or asymptomatic for the disorder. To put it another way, differences in IQ may help explain differential performance on various measures that we intend to study (e.g. response inhibition, working memory, set-shifting, sustained attention, delay aversion, etc.). In fact, we generally find clinical samples of children and adults with ADHD have on average lower IQ than controls. This is a controversy addressed in the very same paper Boonstra and colleagues were exploring: Barkley (1997).

Grane, Endestad, Pinto, & Solbakk (2014) intended to look at associations between performance on a sustained attention task and reporting of executive function deficits in a sample of adults. Utilizing the Test of Variables of Attention (TOVA), Grane and colleagues predicted greater errors of omission and commission and increased response time (RT) variability among adults with ADHD (n = 36) compared to controls (n = 35). Moreover, they predicted correlations between task performance and reported impairment of executive functioning from self-report and informant-report behavior rates, as well as correlations between task performance and measures of anxious and depressive symptomology.

Figure 2. Correlations between task performance (TOVA) and self and informant behavior ratings. Credit: Grane, Endestad, Pinto, & Solbakk (2014).
Figure 2. Correlations between task performance (TOVA) and self and informant behavior ratings. Credit: Grane, Endestad, Pinto, & Solbakk (2014).

Significant differences were found on all measures of sustained attention, namely commission errors, omission errors, and response time (RT) variability. Though there were correlations between task performance and behavioral ratings, only organizational difficulties was significant (Figure 2). Additionally, there were found to be correlations between behavior ratings and measures of depressive mood and anxiety (Figure 3), though task performance did not significantly correlate with DSM measures (Figure 2). These findings are similar to other studies that examine associations between EF-related tasks and behavioral ratings of EF, in that there is little association. See Kamradt, Ullsperger, & Nikolas (2014) for an exploration of these associations.

Figure 3. Associations between DSM measures and self and informant behavior ratings. Credit: Grane, Endestad, Pinto, & Solbakk (2014).
Figure 3. Associations between DSM measures and self and informant behavior ratings. Credit: Grane, Endestad, Pinto, & Solbakk (2014).

van der Meer et al. (2015) investigated 5-HTTLPR gene mediation of psychosocial stress to attempt to explain ADHD severity among a sample of adolescents and adults within the multi-site NeuroIMAGE study. 5-HTTLPR is a promoter region of the serotonin transporter gene SLC6A4, which has a 14-repeat short variant (S-allele) and 16-repeat long variant (L-allele). S-carriers have been found to have on average less connectivity between frontolimbic circuitry, which may beget less efficient top-down regulation of emotions and explain increased levels of psychiatric disorder, including ADHD, anxiety, and depression. van der Meer and colleagues ascertained stress exposure, ADHD symptoms, as well as whole-brain morphometry among S-carriers and L-allele homozygotes to examine mediations between these variables. Morphometric analyses indicated ADHD symptomology was mediated by gray matter volume in the frontal lobe and anterior cingulate gyrus (Figure 4). Consistent with previous findings, S-carriers had significantly less gray matter volume in the precentral gyrus, middle and superior frontal gyrus, frontal pole, and the paracingulate gyrus. Following this, it is plausible gene-environment interactions between the short allele variant of 5-HTTLPR and environmental stress can contribute to structural and functional deficits in the prefrontal cortex, leading to impairments in academic, social, and emotional domains seen in ADHD.

Figure 4. Associations between stress, ADHD symptom severity, and gray matter volume. Credit: van der Meer et al. (2015).
Figure 4. Associations between stress, ADHD symptom severity, and gray matter volume. Credit: van der Meer et al. (2015).

Barkley, R. A. (1997). Behavioral inhibition, sustained attention, and executive functions: Constructing a unifying theory of ADHD. Psychological Bulletin, 121(1), 65-94doi:10.1037/00332909.121.1.65

Boonstra, A. J., Kooij, J. J. S., Oosterlaan, J., Sargeant, J. A., & Buitelaar, J. K. (2010). To act or not to act, that’s the problem: Primarily inhibition difficulties in adult ADHD. Neuropsychology, 24(2), 209-221. doi:10.1037/a0017670

Grane, V. A., Endestad, T., Pinto, A. F., & Solbakk, A-K. (2014). Attentional control and subjective executive function in treatment-naive adults with attention deficit hyperactivity disorder. PLoS ONE, 9(12): e115227 doi:10.1371/journal.pone.0115227

Kramradt, J. K., Ullsperger, J. M., & Nikolas M. A. (2014). Executive function assessment and adult attention-deficit/hyperactivity disorder: Tasks versus ratings on the Barkley Deficits in Executive Functioning Scale. Psychological Assessment, 26(4), 1095-1105. doi:10.1037/pas0000006

van der Meer, D., Hoekstra, P. J., Zwiers, M., Mennes, M., Schweren, L. J., Franke, B., Heslenfeld, D. J., Oosterlann, J., Faraone, S. V., Buitelaar, J. K., & Hartman, C. A. (2015). Brain correlates of the interaction between 5-HTTLPR and psychosocial stress mediating attention deficit hyperactivity disorder severity. The American Journal of Psychiatry, 172(8), 768-775. doi:10.1176/appi.ajp.2015.14081035

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Andrew Crow '16

Andrew is a Psychology and Philosophy major from Milwaukee, Wisconsin.