Background: Attention deficit/hyperactivity disorder (ADHD) is one of the most prevalent and commonly studied forms of psychopathology in children and adolescents. Causal models of ADHD have long implicated dysfunction in fronto-striatal and frontal-parietal networks supporting executive function, a hypothesis that can now be examined systematically using functional neuroimaging. The present work provides an objective, unbiased statistically-based meta-analysis of published functional neuroimaging studies of ADHD. Methods: A recently developed voxel-wise quantitative meta-analytic technique known as activation likelihood estimation (ALE) was applied to 16 neuroimaging studies examining and contrasting patterns of neural activity in patients with ADHD and healthy controls. Voxel-wise results are reported using a statistical threshold of p < .05, corrected. Given the large number of studies examining response inhibition, additional meta-analyses focusing specifically on group differences in the neural correlates of inhibition were included. Results: Across studies, significant patterns of frontal hypoactivity were detected in patients with ADHD, affecting anterior cingulate, dorsolateral prefrontal, and inferior prefrontal cortices, as well as related regions including basal ganglia, thalamus, and portions of parietal cortex. When focusing on studies of response inhibition alone, a more limited set of group differences were observed, including inferior prefrontal cortex, medial wall regions, and the precentral gyrus. In contrast, analyses focusing on studies of constructs other than response inhibition revealed a more extensive pattern of hypofunction in patients with ADHD than those of response inhibition. Conclusions: To date, the most consistent findings in the neuroimaging literature of ADHD are deficits in neural activity within fronto-striatal and fronto-parietal circuits. The distributed nature of these results fails to support models emphasizing dysfunction in any one frontal sub-region. While our findings are suggestive of the primacy of deficits in frontal-based neural circuitry underlying ADHD, we discuss potential biases in the literature that need to be addressed before such a conclusion can be fully embraced. Keywords: Attention deficit/hyperactivity disorder (ADHD), meta-analysis, neuroimaging, functional magnetic resonance imaging (fMRI), positron emission tomography (PET), executive function.

PHARMACOLOGY does not usually publish papers describing the behavior of computer simulations, even if the simulated neurons are ostensibly influenced by dopamine (see Williams and Dayan 2005, this issue, pp 160-179). However, we will argue that their analysis of an abstract model of neuronal functioning has yielded at least two insights that should be tested by clinical investigators, and that have the potential to impact the clinical practice of psychopharmacology.Williams and Dayan base their analysis on two foundations. The first derives from the seminal observations of Wolfram Schultz et al. that a key function of certain dopaminergic cells is to signal errors of prediction between expected and experienced rewards (Schultz et al. 1992;Schultz 2002), thus providing the basis for learning and conditioning. The second is the observation that many children with attentiondeficit/hyperactivity disorder (ADHD) prefer smaller, sooner rewards to larger, later ones (Solanto et al. 2001;Sonuga-Barke et al. 1992). They pose the question of what factors may influence such preferences, and under what circumstances might a tendency to delay gratification emerge in a simple system. Their goal is the creation and computational testing of an abstract model that will reflect the self-organizing properties of a system that can learn and select between "impulsive" and "mature" choices.For their simulation, they choose a basic task, the delayed response time task, which repeatedly asks the participant the question, "Do you wish to wait or prefer to 'press the button' now?" at 5 time points. At each time point, a decision is required; once the "button is pressed," that trial is over. Pressing the button at time 2 yields a small reward, and pressing the button at time 5 yields a larger reward. Responses at any of the other time points (1, 3, or 4) are not rewarded. The accumulation of repeated trials represents repeated experiences, and the history of response-reward relationships accrues. Success is judged by how quickly (if ever) the model learns that waiting results in larger rewards. One value of such a simple task is that it can be used by monkeys, children, and even computers.

Pervasive developmental disorders (PDDs) and autistic disorder in particular are neurodevelopmental diseases characterized by qualitative impairments in social interaction and communication skills and by the presence of restricted and stereotyped behaviors, interests, and activities. The pathophysiological mechanisms underlying these three core symptom clusters are not yet fully understood, and currently there are no treatments which cure these core features of PDD. Psychosocial treatment modalities for individuals with PDD include special education, language therapy, and family support, each of which aims to improve global functioning and increase adaptability. Pharmacotherapy may play an essential role in augmenting an individual's ability to participate fully in these treatments, especially in individuals who have maladaptive behaviors and those with comorbid psychiatric disorders. Pharmacological strategies intend to reduce either the intensity of core symptoms of PDD or the interference of comorbid psychiatric disorders. Clinicians must judiciously use medications that treat the symptoms of comorbid disorders or the symptoms associated with the core triad of PDD. Most recently, in placebo‐controlled trials, risperidone and serotonim selective reuptake inhibitors (SSRIs) have been shown to reduce the restricted behaviors, interests, and activities of some individuals with PDD. In this chapter, we review current pharmacological studies on PDD. Specifically, we will highlight published studies of typical and atypical antipsychotics, serotonergic agents, mood stabilizers, stimulants, α‐2‐adrenergic medications, and others. General pharmacotherapy strategies to target symptom domains in PDD are then discussed.