Attention-Deficit/Hyperactivity Disorder (ADHD) Brain Activity Changes to Psychostimulants
|First Received Date ICMJE||March 7, 2011|
|Last Updated Date||March 7, 2011|
|Start Date ICMJE||May 2004|
|Primary Completion Date||June 2010 (final data collection date for primary outcome measure)|
|Current Primary Outcome Measures ICMJE||Not Provided|
|Original Primary Outcome Measures ICMJE||Not Provided|
|Change History||No Changes Posted|
|Current Secondary Outcome Measures ICMJE||Not Provided|
|Original Secondary Outcome Measures ICMJE||Not Provided|
|Current Other Outcome Measures ICMJE||Not Provided|
|Original Other Outcome Measures ICMJE||Not Provided|
|Brief Title ICMJE||Attention-Deficit/Hyperactivity Disorder (ADHD) Brain Activity Changes to Psychostimulants|
|Official Title ICMJE||A Placebo-controlled Trial of Brain Activity Changes Following Psychostimulant Medication in Adolescent Combined-subtype ADHD|
The purpose of this study is to examine the neural basis of response inhibition, working memory, and sustained attention in adolescents and adults with Attention-Deficit/Hyperactivity Disorder (ADHD), with particular emphasis on quantifying the effects of methylphenidate (i.e., treatment with psychostimulants) on neural function. Participants will undergo electrophysiological measurement of brain function during laboratory cognitive tasks. This research is aimed to develop a better understanding of how ADHD neural dysfunction relates to clinical presentation and medication response during the transition from adolescence to adulthood. The specific aims and hypotheses are:
Specific Aim: To characterize the effect of Ritalin (methylphenidate) on neural activity underlying performance on the response inhibition task in ADHD adolescents and adults. Hypothesis 1) Methylphendiate will increase N2 and P3 amplitude in ADHD persons during medicated EEG sessions; Hypothesis 2) There will be a significant age × medication interaction such that ADHD teens will show increased amplitude of N2 while medicated, particularly at frontal sites, whereas ADHD adults will show differentially greater effect of medication on P3 amplitude and latency at central sites. Hypothesis 3) Brain activity assessed by fMRI will differ between unmedicated and medicated states.
By conservative estimate, Attention-Deficit Hyperactivity Disorder (ADHD) is a common disorder that occurs in at least 3 to 6% of school-aged children (Barkley, 1990). It is marked by symptoms of inattention and hyperactive-impulsive behavior that are developmentally inappropriate. These symptoms must occur in multiple settings and impair functioning to a clinically significant degree (DSM-IV; American Psychiatric Association, 1994). ADHD is believed to be a developmental disorder that begins in early childhood, which distinguishes it from disorders of attention and behavioral control that arise later as consequence of brain injury. Although ADHD was once thought to affect only children, considerable evidence has accumulated to show that ADHD frequently continues into adulthood. Approximately 60% of ADHD youth (about 3-4% of all adults) have clinically significant residual problems as adults (Faraone, 1999; Hechtman, 2000; Mannuzza & Klein, 1999). Although inattention problems appear to persevere into adulthood unchanged, studies suggest that some persons' ADHD hyperactive/impulsive symptoms diminish following teenage years. However, the mechanism for this decrease is not currently known (Wender, 1987; Weiss & Hechtman, 1986, 1993; Brown, 1995).
Expert consensus holds that a deficit in response inhibition is a core feature of ADHD (Barkley, 1998). Supporting this, neuropsychological research suggests that ADHD persons' commonly perform poorly on tasks that require inhibition of response. These tasks, called Go/No-Go or Stop Signal tasks, require continual manual responding to successively presented stimuli and an occasionally withheld response following a predefined signal. Numerous neuropsychological studies have shown that ADHD children, teens, and adults respond more variably on Go trials on such tasks. They also have longer reaction times and more failures to inhibit responses on No-Go trials (Koshack et al., 2003; Oosterlaan, et al., 1998; Wodushek & Neumann, 1999). Psychostimulant medications like methylphenidate improve performance deficits (Bedard et al., 2003).
The link between abnormalities of brain structure/function and cognitive test performance in ADHD persons is well-established, if poorly understood. There is evidence for smaller right frontal lobe volume, abnormalities in basal ganglia size, and reductions in white matter tracts in persons with ADHD (Castellanos et al., 1994; Castellanos et al., 1996; Filipek et al., 1997; Hynd et al.,1993; Mataro et al., 1997). Prefrontal cortex and basal ganglia are involved in planning, initiation, execution, and supervision of ongoing cognitive and motor functions (Fuster, 1997). Structural brain abnormalities correlate with deficits in these cognitive functions and with impulsive behaviors that are symptoms of ADHD (Casey et al., 1997; Mataro et al., 1997; Semrud-Clikeman et al., 2000). Functional imaging techniques, which quantify neural systems operation with respect to cognitive processes, are particularly valuable tools used to characterize dysfunctional neural networks. The most frequently employed method is electrophysiology, in which small voltage changes on the scalp occurring during task performance are recorded and averaged into waveforms that depict brain function to events of interest. These average EEG waveforms are called event-related potentials (ERPs). ERPs to Go/No-Go tasks are well characterized in healthy, non-clinical samples (Logan, 1994). The most frequently observed component to No-Go trials is a large negative potential occurring approximately 275 msec following stimulus presentation (N2) that has a fronto-central distribution. The large N2 has been interpreted as a reflection of early response inhibition processes. Electrophysiological studies find that the large N2 often seen with successful inhibition is diminished in ADHD children and adolescents (Overtoom et al., 2002; Pilszka et al., 2000; Yong-Liang et al., 2000). A literature review reveals no comparable studies of ADHD adults, so the degree of N2 abnormality in older ADHD persons is not known.
ERP source localization suggests that the No-Go N2 arises from activity in inferior prefrontal cortex (Bokura, 2001; Pliszka, 2000). The few FMRI studies of ADHD are consistent with this finding (Garavan et al., 1999; Liddle et al., 2001; Watanabe et al., 2002). Rubia et al. (1999) find less brain activity in right superior-lateral prefrontal cortex, right inferior prefrontal cortex, and left caudate nucleus in unmedicated ADHD adolescent boys relative to controls. Vaidya et al. (1998) report similar findings for ADHD children, and also showed that methylphenidate increased activity in the striatum for ADHD participants. These results support a fronto-temporal N2 decrease in ADHD in brain areas implicated by structural studies as abnormal.
Durston and colleagues also found evidence that compared to non-ADHD, ADHD children also activate a more diffuse network of posterior and dorsolateral prefrontal cortex regions to subserve successful response inhibition (Durston et al., 2003). Increasing age also significantly alters the pattern of activity seen on Go/No-Go tasks for healthy, non-ADHD persons in these brain regions. Children activate more volume of prefrontal cortex compared to adults (Casey et al., 1997). There also is evidence that healthy adults and teenagers use different neural networks to achieve comparable response inhibition task performance (Rubia et al., 2000). Healthy adults show modulation of ventral prefrontal activity depending on task difficulty, whereas children appear to maximally activate these areas generally (Durston et al., 2002). In a sample of ADHD participants ages 8 to 20, age was found to correlate positively with left inferior frontal cortex, and correlate negatively with hemodynamic activity in left dorsolateral prefrontal cortex (Tamm et al., 2002). In other words, there was increasing use of cortex known to be a primary substrate of response inhibition, while reliance on cortex that is a primary substrate of working memory and other "on-line" cognitive processes decreased with age. These differences suggest that age is an important variable in understanding response inhibition neural activity in both ADHD and non-ADHD persons.
Age-related changes to behavior or cognitive functioning are typically interpreted within a developmental framework. Researchers hypothesize that age-related improvements in neural function (i.e., increased neural connectivity or functional specialization) are responsible for improvements in ADHD hyperactive/impulsive symptomatology. A body of evidence indirectly supports such contentions. Adults and adolescents are developmentally distinct with regard to brain structure and function. Structural MR studies consistently show increases in white matter volume throughout early childhood to early adulthood (Caviness et al.,1996; Giedd et al., 1999) reflecting increasing connectivity among cortical areas, especially in reciprocal connections between prefrontal and posterior brain areas (Goldman-Rakic, 1987). Gray matter is seen to increase in a linear fashion until puberty and decrease during adolescence in most brain regions. These curves peak in the frontal and parietal lobes at about age 12, the temporal lobes at age 16, and the occipital lobes at increase until 20 (Giedd et al., 1999). These findings are paralleled by histological animal and in vivo studies of human brain development that show a sharp reduction in syntapogenesis at puberty, followed by an period of synaptic pruning that continues at a similar rate throughout middle adulthood (Bourgeois, 2001). These changes presumably reflect the shaping of brain structure/function following experience (Purves, 1988), and such changes likely reflect continuing performance improvements on some cognitive tests throughout adolescence.
The juxtaposition of changes in brain structure/function and ADHD behavior from adolescence to adulthood raises the possibility that the two might be linked. Furthermore, if these factors are directly related, a link should be observable in a study that focuses on a core impairment of ADHD (i.e., response inhibition) across different age groups. Two positions have arisen in the field of developmental neurobiology to explain how ADHD symptoms diminish. First, some researchers hold that brain areas crucial for behavioral inhibition (i.e., ventral prefrontal cortex) may continue to mature, albeit at a delay. Second, it is possible that other, unimpaired cognitive mechanisms develop to compensate for behavioral inhibition system impairment. Among others, some candidate compensatory mechanisms include stimulus evaluation or working memory processes. Because of the lack of research, neither of these positions have great support at the current time; moreover, the two possibilities are not incompatible. However, this question is crucial in understanding the pathophysiology of ADHD. Figure 2 (right) depicts a two possible relationships of response inhibition development in terms of ERP N2 amplitude. In Figure 2A, the diminished N2 seen in ADHD youth could be hypothesized to resolve with increasing age. Alternatively (Figure 2B), there may be no such gains in response inhibition N2 neural function. Rather, other cognitive processes that can be measured with different ERP indices may reflect the development of compensatory neural mechanisms in older ADHD persons, such as those reflected by the P3.
Summary Previous research shows that response inhibition measured on Go/No-Go tasks is abnormal in all ages of ADHD persons, and that methylphenidate improves performance and alters neural function. When electrophysiological indices of response inhibition (i.e., the N2 ERP) are compared between No-Go success and failure trials, ADHD persons show differences related to automatic processes involved with response inhibition thought to involve prefrontal brain activity. This conclusion is supported by fMRI studies that localize No-Go hemodynamic response to inferior lateral prefrontal cortex and medial cortex (i.e., anterior cingulate and premotor cortex). Therefore, the N2 measures the strength of inhibitory neural processing, likely reflecting activity in brain structures known to be abnormal in ADHD with respect to both structure and hemodynamic function. However, electrophysiology has not yet been used to measure behavioral inhibition in ADHD adults, or to compare ADHD adults and youth.
This study will use electrophysiology to determine whether age-related differences in ADHD symptom expression are related to differences in brain activity involved with response inhibition. Furthermore, by quantifying ADHD brain function both on and off psychostimulant medication, it will be possible to determine how age influences ADHD persons' neural response to methylphenidate. We broadly hypothesize that methylphenidate will affect each groups' ERPs differently. Medication-related differences also will be observed in ADHD symptom severity and neuropsychological test performance. Innovations include that this will be the first electrophysiology study 1) of response inhibition in ADHD adults, 2) that attempts to directly link brain function changes to symptomatology changes in maturation, and 3) that examines medication effects on cognition and behavior across age groups in ADHD.
|Study Type ICMJE||Observational|
|Study Design ICMJE||Observational Model: Case-Crossover
Time Perspective: Prospective
|Target Follow-Up Duration||Not Provided|
|Biospecimen||Retention: Samples With DNA
Saliva samples for genotyping
|Sampling Method||Non-Probability Sample|
Participants will be recruited from the community and referred from psychiatric outpatient clinics.
|Condition ICMJE||Attention Deficit Hyperactivity Disorder|
|Intervention ICMJE||Not Provided|
|Study Group/Cohort (s)||ADHD adolescents and adults
30 adolescents and adults diagnosed with Combined-subtype AD/HD
|Publications *||Not Provided|
* Includes publications given by the data provider as well as publications identified by ClinicalTrials.gov Identifier (NCT Number) in Medline.
|Recruitment Status ICMJE||Completed|
|Completion Date||June 2010|
|Primary Completion Date||June 2010 (final data collection date for primary outcome measure)|
|Eligibility Criteria ICMJE||
ADHD will be diagnosed based on DSM-IV criteria for ADHD combined subtype ADHD. Combined subtype ADHD requires at least 6 of 9 possible symptoms within both the Hyperactive-Impulsive symptom cluster and the Inattentive symptom cluster. This will be assessed using information gathered from the K-SADS-PL interview with either the potential participant or their parent, and from published self- and parent-report ADHD symptom rating scales (Brown, 1996; Barkley, 1998). Predominantly Inattentive ADHD persons will not be included. The Predominantly Inattentive subtype is the subject of much theoretical debate, as it is not clear that these persons represent a unitary disorder, or that they are neurobiologically similar to combined-subtype ADHD (Millich et al., 2001).
To further aid proper ADHD diagnosis, all potential participants will be administered a battery of neuropsychological tests. Potential ADHD participants will undergo testing while unmedicated. This battery will include IQ, and attention and memory tests (WASI, Trail Making, Symbol Digit, Stroop Test, and Rey AVLT), as well as several measures of executive functioning known to be sensitive to the cognitive deficits observed in ADHD samples (Kaplan & Stevens, 2002). Normal performance on all cognitive tests known to be sensitive to ADHD will exclude participants from the study. Full Scale IQ score from the WASI below 80 or above 120 will exclude participants from further participation. Diagnostic interviews using the SCID-IV (First et al., 1996) will be used to obtain a detailed psychiatric history. Lifetime or current history of other major Axis I psychiatric disorders, including bipolar disorder, schizophrenia, substance dependence disorders, or obsessive-compulsive disorders, will exclude potential participants. These disorders may better explain the presence of attention symptomatology, which DSM-IV criteria indicate precludes an ADHD diagnosis. In addition, the disruptive behavior disorders module of the K-SADS-PL will be used to evaluate the presence of childhood Conduct Disorder and adult Antisocial Personality Disorder (ASPD). These diagnoses will also exclude further participation, as these conditions may be better associated with different abnormalities in prefrontal brain function (Bauer, 1997; Stevens et al., 2001). Potential participants also will be excluded if they report a history of head injury (e.g., loss of consciousness > 10 min), seizure disorder, life threatening disease, family history of schizophrenia, uncorrected visual or auditory deficits, or conditions contraindicated for MRI (claustrophobia, metal in body, pregnancy, etc.). Up to 25% of persons with ADHD suffer from learning disorders (Tannock & Brown, 2000). Because educational failure is so prevalent in this group, we will include these people into the study. While the strict inclusion criteria will exclude many potential participants, this is necessary to ensure a homogenous participant population that varies by the presence or absence of ADHD.
Only ADHD persons who are regularly prescribed a classic psychostimulant(Ritalin, dexedrine, etc) will be recruited. This will confirm that such persons show a beneficial therapeutic response to stimulants that can be characterized using brain function measurements. While this will prevent the comparison of brain activity response among various medications, it will simplify interpretation of the results. Finally, subjects will be excluded if they are taking any adjunctive medication for ADHD symptoms (e.g., Wellbutrin, etc.) or another psychoactive medication.
|Ages||13 Years to 50 Years|
|Accepts Healthy Volunteers||No|
|Contacts ICMJE||Contact information is only displayed when the study is recruiting subjects|
|Location Countries ICMJE||United States|
|NCT Number ICMJE||NCT01310439|
|Other Study ID Numbers ICMJE||HH126115|
|Has Data Monitoring Committee||No|
|Responsible Party||Michael C. Stevens, Hartford Hospital|
|Study Sponsor ICMJE||Hartford Hospital|
|Collaborators ICMJE||Yale University|
|Information Provided By||Hartford Hospital|
|Verification Date||March 2011|
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