Symptom-correlated brain regions in young adults with combined-type ADHD: Their organization, variability, and relation to behavioral performance
Introduction
Various brain regions are implicated as dysfunctional in individuals with Attention Deficit Hyperactivity Disorder (ADHD), although many can be profitably grouped into functional sets. Frontal cortex consistently shows reduced activity and volume in individuals with ADHD, including lateral prefrontal cortex (PFC; Booth et al., 2005, Valera et al., 2005, Rubia et al., 2005), inferior frontal cortex (IFC; Booth et al., 2005, Rubia et al., 2005), anterior cingulate cortex (ACC; Bush et al., 1999) and orbital frontal cortex (OFC; Hesslinger et al., 2002). These frontal regions, thought to underlie cognitive control, modulate the ability to hold task-relevant information online, allocate attention, inhibit distraction, and process reward contingencies, all of which have been previously found to be impaired in individuals with ADHD (Bush et al., 1999, Barkley, 1997, Casey et al., 1997, Schweitzer et al., 2000). A second functional set, comprising the striatum and/or basal ganglia, is often discussed in tandem with frontal regions in ADHD because of dense connections between these regions (Alexander et al., 1990). Reduced activation and/or volume in striatal regions are observed in individuals with ADHD, including the caudate (Rubia et al., 1997, Vaidya et al., 1998, Castellanos et al., 2002), putamen (Konrad et al., 2006), and ventral striatum (Scheres et al., 2007). The striatal connections with PFC via cortical loops (Alexander et al., 1990) are thought to provide important signals related to cognitive control, such as signaling of the updating of working memory and information about the contingencies and regularities of events. A third region often identified is the cerebellum, as numerous studies show reduced activation (Valera et al., 2005, Durston et al., 2008) and decreased volume (Castellanos, 1997, Berquin et al., 1998) of the cerebellum in individuals with ADHD. The cerebellum has been suggested as being important for stimulus expectancy and detection, which is dependent on stimulus timing (Rubia et al., 2007a). As proposed by Nigg and Casey (2005), these sets of results taken together suggest that the neural dysfunction in individuals with ADHD is likely to involve a variety of brain regions or circuits rather than being limited to a couple of key nodes or areas. The goal of the current study is to identify such circuits and their relationship to behavioral symptomatology in young adults with ADHD.
In typical neuroimaging studies involving a population with a psychiatric disorder, the strategy used to identify neural dysfunction in the clinical group (e.g., ADHD) is to compare brain activation in that group with a control group during performance of an experimental task that taps a function compromised in the clinical group (e.g. attentional control). The logic is that the clinical group has symptoms, while the control group does not. Hence, the difference in activation between the two groups should isolate critical regions involved in the disorder. Indeed, we have previously performed just such an analysis on portions of the data reported in the current study in which we compare the level of brain activation in young adults with ADHD vs. control individuals during performance of the attentionally-demanding Stroop task. In particular, the young adults with ADHD exhibit less activation than non-ADHD individuals in regions involved in attentional control, such as the DLPFC and ACC (Banich et al., 2009).
Such an approach, however, may not identify all regions involved in a disorder. For example, a group difference may not emerge using such an approach because of variability of the severity of symptoms within the clinical group. For example, compared to controls, some individuals with ADHD may exhibit increased activation in an area to compensate for attentional difficulties, while other individuals with ADHD, whose disorder may be more severe, will show decreased activation because they have a reduced ability to recruit such an area in the face of attentional demand. Hence, areas that may relate meaningfully to an important manifestation of the disorder, symptom severity, may not be detected in a standard clinical-control group contrast.
Therefore, the approach taken in the present study is to identify the neural circuitry related to ADHD symptoms by determining the set of brain regions whose activity during performance of an attentionally-demanding task in young adults with ADHD is correlated with symptom severity. In particular, symptomatology was correlated with brain activation during performance of the Stroop task under three different attentional experimental conditions, as these conditions index many key aspects of attentional control that are likely to be disrupted in ADHD (Bush et al., 1999, Konrad et al., 2006). These processes include the ability to maintain a top–down attentional set, to select among competing representations used to guide behavior, and response-related aspects of attentional control (Banich et al., 2000). Accordingly, this task is likely to (i) index processes that are highly related to attentional symptomatology, and hence (ii) be an effective challenge to the neural structures that underlie attentional control.
If this approach is indeed helpful in identifying the circuitry underlying ADHD, one would then expect that characteristics of activation in the regions so identified should differ in significant ways from (non-affected) control individuals. Rather than simply examining levels of activation in these regions (for the reasons discussed above), the current study focused on the variability of activation in these regions, both between (inter-individual) and within individuals (intra-individual) (Bellgrove et al., 2005, Simmonds et al., 2007). Such an approach may be especially fruitful in understanding the neural underpinnings of ADHD, as one of the key deficits that have emerged between ADHD and control individuals is increased variability in behavioral responses (Rubia et al., 2007a). Response variability is found to be exaggerated in ADHD populations during attention (Leth-Steenson et al., 2000), executive control (Rubia et al., 2001), and timing tasks (Rubia et al., 1999, Rubia et al., 2003), and is one of the most predictive measures of impaired functioning and severity of ADHD diagnosis (Rubia et al., 2007a, Rubia et al., 2007b). In addition, it shows some of the largest effect sizes in group comparisons (Klein et al., 2006, Castellanos et al., 2005, Sergeant et al., 2003). Moreover, there is some initial evidence that such variability may also be reflected in brain functioning. In particular, low oscillatory fluctuation in the brain's default network during the resting state (Helps et al., 2008) and intrusions of the default mode during cognitive tasks (Sonuga-Barke and Castellanos, 2007) are linked to attentional lapses and increased within group (intra-individual) response variability in ADHD individuals.
Our hypothesis therefore was that the severity of symptomatology related to attention across ADHD individuals would predict the level of activity in brain regions that are involved in attentional control (LPFC) as well as potentially predicting activity in brain regions whose function might be affected by or contribute to reduced control (e.g., stimulus–response linkage; rIFG; stimulus association and timing inferior temporal lobe and cerebellum). Furthermore, the characteristics (i.e., variability) of brain activation in regions linked to symptom severity in the ADHD group would differ significantly from that of a control group. We predicted that the ADHD group would exhibit more variability in brain activation in these regions than a control group and that such variability would be linked to variability of behavioral performance on the Stroop task.
Section snippets
Participants
Participants included twenty-three young adults with combined-type ADHD (14 male, 9 female) and 23 healthy controls (14 males, 9 females) between 18 and 23 years of age.
Stimuli and experimental design
Participants performed a variant of the Color-Word Stroop task in the scanner. Participants saw a series of words printed in one of four ink colors (red, blue, green, or yellow), and indicated the ink color via a manual keypress. There were three
Results
Behavioral results of the Stroop task can be found in Supplementary material: S2.
Discussion
The current study yielded important new insights regarding the neural underpinning of ADHD in young adults, as well as the type of approach that can be fruitfully used to reveal them. The primary result indicated that a large group of brain regions spanning both cortical and sub-cortical regions, as well as anterior and posterior regions, exhibited activity that was significantly negatively correlated with the severity of ADHD inattentive symptomatology. Consistency of the findings with these
Acknowledgements
NIMH grant R01 MH 070037 (Banich, P.I.) provided support for data collection and analysis as well as salary support for all but the fourth author. We thank Bruce Pennington for helpful discussion of this data. In addition, appreciation is also given to Deb Singel for her assistance with data collection and MR technical issues. Finally, we thank Anonymous Reviewer #2 for insightful comments in our review process.
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