The prefrontal cortex (PFC) has been implicated in higher level cognitive functioning, including attentional processes, working memory, inhibition and planning. The PFC has also been shown to be anatomically and reciprocally connected to practically all sensory and motor systems as well as a wide variety of subcortical structures (Miller, 2000
). This makes it an ideal site for learning and adaptation of behavior and goals as well as being able to exert a top-down influence on other brain structures in the facilitation of appropriate behaviors and allocation of attentional resources.
Anatomical and functional variations in PFC as well as deficits in constructs attributed to PFC, such as inhibition and attention, have been implicated in ADHD in a number of behavioral and imaging studies. However, controversy exists as to the degree of each type of deficit in both children and adults. Although a number of studies have suggested an inhibitory deficit in ADHD in ERP (Broyd et al., 2005
), imaging (Casey, Castellanos et al., 1997
; Casey, Durston, & Fossella, 2001
) and behavioral paradigms (Iaboni, Douglas, & Baker, 1995
; Konrad, Gauggel, Manz, & Scholl, 2000
; Oosterlaan & Sergeant, 1998
; Schachar, Mota, Logan, Tannock, & Klim, 2000
) some, including some of the aforementioned, authors have pointed out that these differences may be due to other factors than simply an inhibitory deficit alone per se.
Oosterlaan and Sergeant (1998)
, for example, suggested that a broader deficit underlies ADHD, perhaps a motivational problem or one related to more generally defined executive functions. They suggest that this may be attributable to frontal lobe dysfunction. In a further study, these authors (Kuntsi, Oosterlaan, & Stevenson, 2001
) found marginal differences in inhibitory processes between ADHD and control children. The authors support the theory that an inhibitory deficit is not the core deficit in ADHD, rather one of slower information processing and delay-aversion (Sonuga-Barke, Taylor, Sembi, & Smith, 1992
). Others again, suggest that adults may display greater deficits in inhibition whereas in children the core problem may be largely attributable to attentional difficulties (Nigg, Butler, Huang-Pollock, & Henderson, 2002
). In fact, a very recent review of the STOP inhibitory paradigm supports this view. The authors suggested that from the review it appeared that adults with ADHD experience inhibitory deficits, whereas inhibitory problems experienced by ADHD children are largely accounted for by additional attentional problems (Lijffijt, Kenemans, Verbaten, & van Engeland, 2005
In a behavioral study by Rubia and coworkers (Rubia, Oosterlaan, Sergeant, Brandeis, & Leeuwen, 1998
), the authors found a significant inhibitory deficit and more variable reaction times (RT) in ADHD participants in two different versions of a STOP paradigm and concluded that this may be due to problems either at the level of motor output or at a higher executive level due to inadequate attention and/or motivation. RT differences have also been found between participants with ADHD and normal controls in a number of tasks (Fallgatter et al., 2004
; Leth-Steensen, King Elbaz, & Douglas, 2000
). Findings of RT differences have been mixed however; some authors suggesting no overall difference but more erratic or variable RT in individuals with ADHD (Berwid et al., 2005
; Rucklidge & Tannock, 2002
). Others report overall slowing of RT (Fallgatter et al., 2004
; van Mourik, Oosterlaan, & Sergeant, 2005
) suggesting general difficulties or increased interference in such tasks in ADHD participants, whereas others again suggest slower and more variable reaction times in children at risk for ADHD (Berwid et al., 2005
Although behavioral tasks have been informative to a certain degree about ADHD, they can only provide limited information about the underlying neural anatomy associated with the behavioral function. For example, many different clinical groups may experience the same patterns of behavioral performance, hence different brain deficits can lead to the same patterns of performance, making them difficult or impossible to distinguish from one another. Occasionally different or hypo-active underlying brain circuitry may be accompanied by normal performance or alternatively performance differences may be too small too detect. Hence potential discrepancies in functioning may not be detected unless behavioral and brain imaging techniques are combined (Eldreth, Matochik, Cadet, & Bolla, 2004
; Rubia et al., 2000
). Imaging studies can also be a useful tool in increasing our understanding of brain differences in clinical groups. As Rubia et al. (2000)
point out, causality is not certain; abnormal brain function or structure may not be the root cause of abnormal behavior. In other words, brain differences may not be causing the deficit but may be caused by years of behaving differently from the norm. Although imaging techniques cannot determine the direction of an effect per se, they may prove useful in addressing the difficult question of causality between brain function and behavior.
In a PET study of adults with ADHD, global glucose metabolism was significantly decreased in participants with ADHD in comparison to controls (Zametkin et al., 1990
). This decrease was particularly evident in superior PFC and premotor regions. Imaging studies have also suggested differences in brain volume between ADHD participants and normal controls. With regard to PFC differences, a number of studies have found smaller volumes of PFC in children with ADHD (Castellanos et al., 1996
; Durston, Hulshoff Pol et al., 2004
; Kates et al., 2002
; Mostofsky, Cooper, Kates, Denckla, & Kaufmann, 2002
). In fact, Mostofsky et al. (2002)
found that reduction in the volume of the PFC in ADHD children accounted for nearly half of the reduction of total cerebral volume. However due to the small sample size in this study (12 ADHD and 12 control subjects) these results should, perhaps, be interpreted with caution. In a study by Filipek et al. (1997)
, the volume of superior frontal regions was significantly smaller in ADHD subjects, particularly in the right hemisphere. Bilateral inferior frontal regions were smaller in ADHD subjects. This region included caudate head and anterior basal ganglia. Finally, in a more recent study, Sowell et al. (2003)
found a decreased bilateral PFC volume (particularly in inferior parts of dorsal prefrontal cortex) in children and adolescents with ADHD when compared to normal controls. This study included a relatively large sample of ADHD and control children (27 children/adolescents with ADHD and 46 controls).
Casey, Castellanos et al. (1997)
also used behavioral performance on three tasks, a sensory selection, response selection and response inhibition task in addition to brain volume measurements in order to investigate differences in participants with ADHD and normal controls. Correlations between performance and brain volume in PFC among other areas were seen for both groups in these tasks (patterns of correlations differing between groups). Notably, right PFC volume correlated with performance on the inhibitory task for ADHD subjects. Yeo et al. (2003)
also found smaller right DLPFC volumes in ADHD children than control children. In the ADHD group this also correlated with neurometabolite concentrations (creatine and choline-containing compounds and N
-acetylaspartate). Interestingly, in this study greater volume in right dorsolateral PFC correlated with poorer performance on the continuous performance task. Hill et al. (2003)
also found a decreased superior prefrontal cortex, particularly in right hemisphere, in ADHD participants. In a similar vein to the Yeo et al. (2003)
study just discussed, greater volume in this region in ADHD subjects correlated with poorer performance on a task of sustained attention (Conners’ Continuous Performance Test).
ADHD has been associated with a right hemisphere deficit in behavioral (Rubia et al., 1998
), functional magnetic resonance imaging (fMRI) (Rubia et al., 1999
; Vaidya et al., 1998
) and electrophysiological studies (Pliszka, Liotti, & Woldorff, 2000
; Steger, Imhof, Steinhausen, & Brandeis, 2000
). Executive functions such as sustained attention (Manly et al., 2003
), working memory (D’Esposito, Ballard, Aguirre, & Zarahn, 1998
) and inhibition (Garavan, Ross, & Stein, 1999
; Konishi, Nakajima, Uchida, Sekihara, & Miyashita, 1998
) have also been attributed to the right hemisphere, particularly right PFC. It has been suggested that one of the principal deficits experienced in ADHD concerns problems with inhibition (Barkley, 1997
). In fact, hypo-activity in ADHD subjects has been observed in right PFC during a classic inhibitory paradigm, the STOP paradigm (Rubia et al., 1999
), Hyperactivity has been observed in PFC in adolescents (Schulz et al., 2004
) and children (Vaidya et al., 1998
) with ADHD during similar GO/NOGO tasks. In both studies functional differences were associated with inhibitory difficulties, as measured by a significant increase in errors of commission, in participants with ADHD.
There were, however, some discrepancies between these studies. For example, as mentioned, some studies have reported hypo-activity in PFC in ADHD when compared to controls (Zang et al., 2005
) whereas others report hyperactivity (Vaidya et al., 1998
). Whereas Rubia et al. (1999)
found reduced activity in right prefrontal regions in the STOP task, Vaidya et al. (1998)
noted an increase in activity in bilateral frontal regions, which was interpreted as an extra inhibitory effort in ADHD children. However, the GO/NOGO task employed by Vaidya et al. (1998)
used 50:50 GO to NOGO ratio, which may not fully tax the inhibitory systems of, at least, the control group.
Varying the ratio of GO to NOGO stimuli has previously been found to alter “inhibitory” activation patterns (de Zubicaray, Andrew, Zelaya, Williams, & Dumanoir, 2000
). When the ratio of NOGO to GO stimuli is low, a prepotent tendency to respond is established, making the stopping process more difficult upon presentation of the NOGO event. However, parametric manipulations of the number of GOs preceding a NOGO stimulus has previously been shown to have no significant effect on children with ADHD (Durston et al., 2003
), one preceding GO stimulus being enough to cause inhibitory difficulty on the following trial. Additionally, since inhibitory capabilities have been shown to develop throughout childhood (Rubia et al., 2000
), this task may have already been sufficiently demanding on inhibition in this group of age 8 to 13 years. The issue of the potential effect of the prepotency of the GO response should, however be kept in mind. A limitation of the study was that only selected regions were imaged and therefore information on functioning in other regions is not available.
Both hypo- and hyperactivity can be interpreted as being suggestive of inefficiency in underlying brain structures. When comparing a clinical group to normal controls hypo-activity in a certain brain region may suggest an incapability of that particular brain structure to function to the extent required by that particular task. In other words it may be considered to be “underpowered”. Hyperactivity in a region may be suggestive of a very similar problem. In this case it may be that the brain region needs to exert extra energy in order to perform a task to the same degree as the control group. Therefore these regions can be thought of as “inefficient” in that they use more energy than should be necessary to perform a given task. However, extra activity in the clinical group in a region that is not significantly active for the control group may be viewed as compensatory activity or brain regions that the clinical group are enrolling in order to compensate for under-activity in the “appropriate” network of brain areas. This will be discussed in more detail later.
More recently, exploratory analyses (with a very small sample of children) have also suggested increased bilateral prefrontal activity during NOGOs in adolescents with ADHD over normal controls in a GO/NOGO task (Schulz, Newcorn, Fan, Tang, & Halperin, 2005
). Furthermore ADHD adolescents were divided into those that displayed a remission of their symptoms in adolescence and those that did not (see for details). Adolescents that did not show remission displayed greater activity in ventrolateral PFC then those who did show remission, who in turn showed increased activity in these regions compared to normal control children. This increase in activity was also accompanied by an increase in commission errors in this task across the three groups. However a one-way ANOVA revealed that this trend failed to reach significance, probably due to the very small sample size (5 subjects in each group). As mentioned above, in a previous study by this group, using a similar GO/NOGO paradigm in adolescents, significant differences in performance were found between groups (Schulz et al., 2004
). These results may be interpreted as the recruitment of additional compensatory prefrontal regions in the ADHD group in order to perform the task, as normal control activation in this ventrolateral area was more prominent in response to actual GOs than NOGO stimuli.
In an electrophysiological study utilizing the STOP paradigm, differences in wave forms were found between ADHD and control children in right PFC (Pliszka et al., 2000
). This wave form was interpreted as reflecting inhibitory processes, although it has also been linked with response conflict monitoring (Nieuwenhuis, Yeung, van den Wildenberg, & Ridderinkhof, 2003
). Correlations were also found between behavioral performance and amplitude of the wave form in right PFC, particularly for the children with ADHD (Pliszka et al., 2000
). In a recent study, Fallgatter and colleagues (2004)
noted that the normal pattern of NOGO-anteriorization (NGA) (a significant increase in P3 amplitude at frontal and central electrodes for the NOGO over the GO trial) was not observed in children with ADHD. NGA has previously been pinpointed as an index of prefrontal response control, such as action and conflict monitoring (Fallgatter & Strik, 1999
). These authors argue that this suggests a problem with response control in children with ADHD, although this was not reflected by an increase in commission errors in this group (Fallgatter et al., 2004
Using fMRI, Rubia and coworkers suggested that the functional differences found between ADHD children and normal controls in their imaging study of response inhibition may have been due to an immaturity in the frontal lobes of children with ADHD (Rubia et al., 1999
). In order to investigate this further, these authors carried out an additional study which compared the activation patterns of normal adolescents and adults to those of adolescents with ADHD on an inhibitory paradigm and a delay task (2000). In this experiment, the behavioral results and activation patterns of normal adolescents and adults were quite similar, although the activation of adolescents was slightly reduced in prefrontal areas in comparison to adults. However, whereas adults tended to activate bilateral frontal areas, activation in the adolescents was concentrated mainly in right prefrontal cortex. The authors suggested that there is a maturation of the frontal cortex “from a functionally adequate but immature prototype system to a more definitive adult network” (page 18).
The activation patterns of adolescents with ADHD in the study by Rubia et al. were quite different. They tended to activate right pre- and post-central gyrii, right inferior parietal lobe and right caudate. For the delayed response task the ADHD subjects, unlike the comparison groups, did not activate frontal areas, except for a small focus of activation in the supplementary motor area (SMA) (Rubia et al., 2000
). The authors suggest that differences in the activation patterns of ADHD subjects and normal controls in the absence of significant behavioral difference may reflect differences in strategies for task performance. It may be that there is some compensatory mechanism at play, in which participants with ADHD, who have an immature prefrontal cortex (Rubia et al., 1999
), may compensate with the recruitment of additional cortical areas in order to perform at the same level as that of control participants. For example, Rubia and colleagues argue that lack of activation in “appropriate” task regions (i.e. PFC) may have been compensated for in the ADHD by the enrollment of more posterior prefrontal regions in their study (1999).
Other studies have supported the argument that individuals with ADHD use compensatory, alternative strategies and brain regions due to impaired functioning of the PFC (Schweitzer, Faber et al., 2000
; Schweitzer et al., 2004
). In two PET (positron emission tomography) studies of adults with ADHD, participants with ADHD activated a distinctly different network of brain regions during a working memory (WM) task. Both studies utilized a WM paradigm called the Paced Auditory Serial Addition Task (PASAT) (Gronwall, 1977
), which also requires participants to inhibit distracting information. Hence it can be seen as a task which taxes executive functioning. These male ADHD subjects did not significantly activate the same right PFC regions that were activated by controls. Instead they tended to activate a more diffuse network of regions that included the parietal, precuneus, and occipital lobe. This was interpreted as a use of more visual strategies in this aurally presented task in the individuals with ADHD (Schweitzer, Faber et al., 2000
). This hypothesis was supported by the men’s subsequent verbal testimony, which suggested that they had, in fact, used a visual strategy (see ); subjects reported visualizing the task stimuli that were aurally presented via headphones.
Fig. 1 Brain regions activated during a working memory task (i.e., PASAT) compared to random number generate control task. Images are displayed in radiological space with the right hemisphere displayed on the left side. The top row displays averaged t-maps from (more ...)
Visual or more “basic” strategies may be stronger in these subjects, due to a weakened ability to use verbal rehearsal strategies or possibly due to inefficiency of networks underlying WM. DLPFC has been linked to WM and manipulation of information held in WM in a number of studies (D’Esposito et al., 1998
; D’Esposito & Postle, 2002
; D’Esposito, Postle, Jonides, & Smith, 1999
; Postle & D’Esposito, 1999b
). A number of authors have also suggested that WM may involve a similar process to that used in sustaining attention (Awh & Jonides, 1998
; Coull, Frackowiak, & Frith, 1998
; Coull, Frith, Frackowiak, & Grasby, 1996
) a system that is also believed to be impaired in ADHD (Carter, Krener, Chaderjian, Northcutt, & Wolfe, 1995
). If PFC is, indeed, compromised in ADHD, it may be that subjects are unable to adequately recruit more “efficient” regions and may be forced to rely on alternative, more automatic strategies in order to perform certain paradigms. That is, subjects with ADHD may need to recruit alternative brain regions to boost a weakened neural circuitry.
In a follow-up PET study, the authors (Schweitzer et al., 2004
) found that the most common treatment for ADHD, methylphenidate (MPH), led to decreases in activity in the PFC in adults with ADHD. In this study the dose of the medication was individually, clinically determined for each subject. The MPH was interpreted as having “honed” the prefrontal system so that it was able to more efficiently inhibit distracters and boost performance of the task (Schweitzer et al., 2004
). In fact, in a previous study by this group on the effects of MPH on the activation patterns of participants with ADHD during rest, it was shown that subjects showed wider and more diffuse patterns of activity during the off-medication period than during the on-medication period (Schweitzer, Lee et al., 2003
). Activity during the rest period was primarily associated with cortical motor regions.
As an extension to the WM studies in adults, Schweitzer et al. used fMRI and a visual variant of the PASAT to test WM in children (mean age of 10 years) with ADHD (Schweitzer, Cortes, Gullapalli, Dunning, & Tagamets, 2003
). In this preliminary study, control subjects tended to activate the left hemisphere regions significantly more than ADHD children. In contrast, in the ADHD children there were wider spread activations, particularly in the right hemisphere throughout the cortices. Similar to the adult ADHD subjects, the pediatric ADHD subjects activated regions associated with visual processes (e.g., occipital gyrus, cuneus) to a greater extent than the control subjects, once again, suggesting use of a system more reliant on visual strategies and response to visual stimuli.
From the studies just examined it is apparent that PFC may have a central role to play in the deficits associated with ADHD. As mentioned, areas such as DLPFC have been associated with a number of different executive functions such as the maintenance of task set (Frith & Dolan, 1996
; MacDonald, Cohen, Stenger, & Carter, 2000
; Garavan, Ross, Murphy, Roche, & Stein, 2002
; Ruchsow, Grothe, Spitzer, & Kiefer, 2002
), inhibition of a prepotent response tendency (Aron, Fletcher, Bullmore, Sahakian, & Robbins, 2003
; Braver, Barch, Gray, Molfese, & Snyder, 2001
; de Zubicaray et al., 2000
; Garavan et al., 1999
; Kawashima et al., 1996
; Konishi et al., 1998
), sustaining attention (Coull et al., 1996
; Manly et al., 2003
; Sturm et al., 1999
; Wilkins, Shallice, & McCarthy, 1987
) and WM (D’Esposito et al., 1998
). In fact, a substantial number of structural brain imaging studies have reported smaller DLPFC volumes in participants with ADHD (Castellanos et al., 1996
; Durston, Hulshoff Pol et al., 2004
; Filipek et al., 1997
; Hill et al., 2003
; Kates et al., 2002
; Mostofsky et al., 2002
). Thus, dysfunction in areas of the PFC, such as DLPFC, may account for a large number of the symptoms experienced by individuals with ADHD, such as, trouble inhibiting, maintaining task set and sustaining attention on a task.
It has also been suggested that functional impairment of the PFC in ADHD may be due to catecholamine (e.g., dopamine, noradrenaline) signal transduction defects in this region (Arnsten, 2001
; Ernst, Zametkin, Matochik, Jons, & Cohen, 1998
; Mehta, Calloway, & Sahakian, 2000
). This is, however, beyond the scope of this review. Given that, as mentioned earlier, PFC has interconnections with a vast array of other cortical and subcortical regions, it is unlikely that prefrontal regions work in isolation. This may be particularly important with reference to striatal regions which are thought to play a very important role in ADHD as will be discussed further. Impairment in the PFC is likely to influence the integrity of detection of demands for a given task or situation. An altered PFC has the potential to limit how well it can recruit other brain regions with which it has interconnections to meet task demands.