Mark D. Rapport, Lauren M. Friedman, Samuel J. Eckrich & Catrina A. Calub
What is ADHD?
Attention-deficit/hyperactivity disorder (ADHD) is an early onset, highly heritable and chronic neurodevelopmental disorder characterized by clinically impairing levels of inattention, hyperactivity, and impulsivity (American Psychiatric Association, 2013). The disorder affects an estimated 3.5 million children in the United States at an annual cost of approximately $20.6 billion, the majority of which is allocated for outpatient care/education related costs (63.9%) and pharmaceutical (35.4%) costs (Bui et al., 2016).
Accumulating evidence indicates that the three ADHD core symptom clusters
—inattentiveness, impulsivity, and hyperactivity—and the myriad adverse func - tional outcomes associated with the disorder may be secondary to more basic Executive Function (EF) deficits such as Working Memory (WM), that in turn, are associated with underdeveloped prefrontal/frontal brain circuitry (Shaw, Malek, Watson, Sharp, Evans, & Greenstein, 2012). The Working Memory model of ADHD provides a framework for investigating these relations and will be discussed throughout this chapter.
The initial section summarizes recent changes in the diagnostic criteria for the disorder, including its recognition as a neurodevelopmental rather than an externalizing disorder of childhood. Associated clinical markers and the high degree of learning disabilities are also discussed. Executive Function (EF) deficits, and particularly those associated with WM mechanisms and subsystem processes, are highlighted in the second section. The ensuing section summarizes accumulating evidence derived from neuroimaging and EEG studies that reveal significant developmental delays and widely distributed hypoactivity in frontal/prefrontal cortical regions that underlie and contribute to EF deficits in children with ADHD.
The impact of the disorder on children’s daily activities, and its accumulating effects
on long-term functioning in late adolescence and early adulthood are summarized in the fourth chapter section. Afterwards, evidence is reviewed relevant to one of the most controversial topics involving ADHD—whether the excessive gross motor or hyperactivitycomponent of the disorder is ubiquitous and non-functional or better understood as a context dependent compensatory behavior. The final chapter section provides a succinct overview and critique of the gold standard treatments for ADHD—viz., psychostimulant medication and psychosocial inter - ventions—as well as novel, non-empirically validated treatments such as computer- based cognitive training and neurofeedback.
Diagnostic features
The moniker Attention-Deficit Disorder (ADD) was first used in 1980 in the third edition of the Diagnostic and Statistical Manual of Mental Disorders(DSM-3) and has undergone iterative revisions in each subsequent edition. In the most recent version (DSM-5, 2013), ADHD is classified as a neurodevelopmental disorder along with other conditions that manifest during early developmental stages (e.g., intellectual disability, communication disorders, autism spectrum disorder).
A diagnosis of ADHD is based on the number and level of impairment among symptom combinations related to inattention, hyperactivity, and impulsivity, and characterized by an early onset (prior to 12 years of age) and chronic and worsening course. Related impairments in interpersonal and academic functioning are common and contribute to social and occupational deficits in adolescence and early adulthood. The DSM-5 also requires that symptoms be present in more than one setting (e.g., at home, school, or work).
ADHD subtypes
ADHD was diagnostically differentiated into three subtypes or presentations begin - ning in the 1990s: ADHD-Combined presentation, wherein symptom thresholds for inattentiveness, hyperactivity, and impulsivity are met (ADHD-C); ADHD- Inattentive presentation, wherein only the inattentive symptom threshold is met (ADHD-I); and ADHD-Hyperactive/Impulsive presentation, in which only the symptom thresholds for excessive gross motor movement and impulsivity are met (ADHD-HI). Distinguishing among presentation types is challenging, particularly for cases with elevated but sub-threshold numbers of symptoms. For example, consider a child who meets diagnostic criteria for ADHD-I rather than ADHD- C because five rather than six hyperactivity–impulsivity symptoms were endorsed.
For these cases, the qualitative distinction between presentation types is specious and may be better conceptualized as a milder form of ADHD-C.
Debate continues regarding the ADHD-Inattention presentation subtype.
Children falling within this group often exhibit a cluster of symptoms referred to as a sluggish cognitive tempo in the literature and are usually described as hypoactive and daydreamers. Their symptom presentation includes mental confusion, fogginess,
staring, being easily confused, lethargic, and non-aggressive, accompanied by pro - cessing speed and selective attention deficits. Collectively, their symptom presenta - tion and related cognitive deficits suggests an entirely different neuro cognitive profile than is typically seen in ADHD-Combined subtype children.
Symptom continuity
Developmental changes in symptom presentation and the relative contribution of these symptoms to functional impairment between childhood and early adulthood are well documented. For example, hyperactivity and impulsivity symptoms are endorsed more often and are more sensitive to a clinical diagnosis relative to inattentive symptoms at 4 to 5 years of age; however, a majority of children exhibiting only hyperactivity and impulsivity symptoms in preschool display equally significant problems with inattention by elementary school (Curchack-Lichtin, Chacko, & Halperin, 2014). Children meeting diagnostic criteria for ADHD-C show a slight reduction in inattention symptoms between the first and second year following assessment (likely a manifestation of measurement artifact), but in attentiveness remains a significant feature of the disorder throughout adolescence for an estimated 78% of previously diagnosed children with ADHD and predicts poor educational outcome. In contrast, hyperactivity–impulsivity symptoms decline substantially over time (i.e., fewer than 20% of children with ADHD-C continue to exhibit excessive gross motor activity as adolescents) and contribute minimally to the disorder thereafter (DuPaul, Morgan, Farkas, Hillemeier, & Maczuga, 2017).
Working Memory (WM) and related Executive Function (EF) deficits
Despite recent assertions and theoretical papers suggesting the presence of myriad Executive Functions (EFs) in humans, meta-analytic reviews, factor analytic studies, and neuroimaging investigations consistently identify only three—viz., Working Memory, set shifting, and behavioral inhibition (cf. Rapport, Orban, Kofler, &
Friedman, 2013, for a review)—two of which (Working Memory, set shifting) show developmental continuity throughout the lifespan (Huizinga, Dolan, & van der Molen, 2006) and are associated with a strong, independent genetic basis (Friedman, Miyake, Young, DeFries, Corley, & Hewitt, 2008). The extent to which these EFs are (a) impaired among children with ADHD, (b) related to ADHD core symptoms (i.e., inattention, hyperactivity, and impulsivity), and (c) implicated in behavioral, cognitive, and educational outcomes, are reviewed subsequently.
Working Memory
Working Memory (WM) is a multi-component, limited-capacity cognitive system responsible for the temporary storage and processing of information used when engaged in reasoning, planning, problem solving, and other complex behaviors.
There are fewer than a handful of empirically supported comprehensive theories of WM, and despite their differences, there is widespread agreement that WM is comprised of three distinct components. The workingcomponent of WM (i.e., the central executive (CE)) is responsible for the mental processing of internally-held information using several interrelated processes such as updating, manipulation/
dual processing, serial reordering, and interference. The CE contains no memory of its own—rather, it serves as an attentional controller that oversees the pro cessing, manipulation, and preservation of information held in two, anatomically distinct storage/rehearsal memory systems—the phonological (PH) and visuospatial (VS) short-term memory subsystems that are responsible for verbal and nonverbal information, respectively (see Figure 5.1). WM has emerged as a candidate endophenotype for ADHD based on independent empirical findings demonstrating that children with ADHD exhibit large magnitude deficits on WM tasks (Kasper, Alderson, & Hudec, 2012) and complementary evidence that WM deficits underlie core and secondary symptoms of the disorder (reviewed below).
Visual analysis and
STS Central Executive
Attentional control Memory updating
Manipulation/dual processing Serial recording
Interference control
Visual Input
Orthographic to phonological
recording
Visuospatial output buffer Right premotor cortex
Motor Output Covert rehearsal
process Visual Input
Visuospatial
STS
Right hemisphere Visuospatial Analysis
Phonological output buffer Broca’s area-premotor
cortex
Spoken Output Covert
rehearsal process
Auditory Input
Phonological
STS Inferior parietal
lobe Phonological Analysis
FIGURE 5.1 Adapted and expanded schematic of Baddeley’s (2003) Working Memory model and associated anatomical loci. Primary central executive processes are shown at the top of the figure; STS = short-term store
Reprinted and expanded from Rapport et al. (2008) with permission from the author.
Differentiating between the working(CE) and memory (PH and VS short-term memory) components of Working Memory is critically important given their distinct neuroanatomical locations and degree to which WM components contribute to core ADHD symptoms and adverse functional outcomes such as learning deficits.
The CE is localized primarily in the prefrontal cortex, whereas the PH and VS short- term stores are localized in the (a) temporoparietal cortex and Broca’s area, and (b) posterior parietal and superior occipital cortices, respectively (Baddeley, 2007). Extant evidence indicates that children with ADHD evince large-magnitude deficits in the CE components of WM (Rapport, Alderson, Kofler, Sarver, Bolden, & Sims, 2008) that are related functionally to inattention (Kofler, Rapport, Bolden, Sarver, & Raiker, 2010; Orban, Rapport, Friedman, Eckrich, & Kofler, 2017), hyper activity (Rapport, Bolden, Kofler, Sarver, Raiker, & Alderson, 2009), and impulsivity (Raiker, Rapport, Kofler, & Sarver, 2012).
Underdeveloped CE processes also play a critically important role in ADHD- related reading difficulties (Friedman, Rapport, Raiker, Orban, & Eckrich, 2016), math deficits (Friedman, Rapport, Orban, Eckrich, & Calub, 2017), and social problems (Kofler, Rapport, Bolden, Sarver, Raiker, & Alderson, 2011). Conversely, children with ADHD exhibit small to moderate magnitude deficits in PH and VS short-term memory (Kasper et al., 2012), which are either minimally involved or unrelated to core diagnostic symptoms (Alderson, Rapport, Hudec, Sarver, & Kofler, 2010; Rapport et al., 2009) and important academic (Friedman et al., 2016, Sarver et al., 2011) and functional (Kofler et al., 2011) outcomes.
The WM model of ADHDprovides a framework for investigating ADHD-related WM deficits (see Figure 5.2). According to the model, underlying heritable etiological factors such as slowed nerve growth factors and corresponding reduced neurotransmitter functioning result in neural structure and function deficits, respectively. Evidence for this can be seen in the 2.5 to 3-year delay in cortical maturation observed among children with ADHD via neuroimaging between 5 and 15 years of age (Shaw et al., 2007), as well as the excess slow wave and decreased fast wave activity in frontal/prefrontal regions that implicate cortical underarousal (El-Sayed, Larsson, Persson, & Rydelius, 2002). Two interrelated phenomena result from these deficits: (a) slowed cortical maturation results in underdeveloped EFs such as WM that are requisite for attention demanding activities fundamental for reasoning, problem solving, behavioral/interpersonal discourse regulation, and developing foundational knowledge competencies (e.g., reading, mathematics); and (b) frontal/prefrontal underarousal results in excessive gross motor activity to maintain alertness when children are faced with environmental presses that place clear demands on the higher-order WM supervisory attentional controller and its associated central executive and subsidiary processes.
Behavioral inhibition
Behavioral inhibition (BI) is the ability to withhold (action restraint) or stop (action cancellation) an ongoing response. In the late 1990s, BI emerged as a possible core
deficit of ADHD following Barkley’s (1997) seminal theoretical paper and complementary evidence indicating large magnitude BI deficits in children with ADHD. According to Barkley’s theory, BI deficits affect the ability to inhibit (a) previously reinforced or well learned responses; (b) ongoing responses that need reconsideration due to newer, more relevant information; and (c) attention to irrelevant stimuli (i.e., distractions). BI processes are also hypothesized to super - intend four higher-order Executive Functions—WM, internalization of speech, reconstitution, and self-regulation of affect, motivation, and arousal—that serve to regulate behavior.
Empirical evidence for the BI model of ADHD, however, is lacking based on evidence from meta-analytic reviews and empirical studies indicating that BI deficits are explained more parsimoniously by deficits in basic attention, perform - ance variability, and/or WM (Alderson, Rapport, & Kofler, 2007). WM processes are also more accurately modeled as upstream of BI processes, rather than vice-a- versa, given that information must enter the WM system for processing prior to the initiation of inhibition processes (i.e., information must gain access to WM and be analyzed to determine the appropriateness of acting on it). Further, BI performance deficits are weakly or unrelated to core and secondary symptoms of ADHD (Alderson, Rapport, Kasper, Sarver, & Kofler, 2012). Collectively, extant literature indicates that BI processes are relatively intact among children with ADHD, weakly or unrelated to the disorder’s impairing symptoms, and downstream from WM processes.
FIGURE 5.2 An updated schematic of the Functional Working Memory (WM) Model of ADHD
Set shifting
Set shifting is the ability to be mentally flexible and switch between two or more tasks or mental sets. Tasks commonly used to measure set shifting involve holding two response sets simultaneously and switching between responses according to pre-specified criteria or performance feedback. Meta-analytic reviews reveal moderate deficits in set shifting among children with ADHD (Frazier, Demaree,
& Youngstrom, 2004) and that approximately 25% to 35% of children with ADHD evince set shifting deficits. Set shifting is related moderately to core symptoms of ADHD; however, the relations between set shifting and important functional outcomes such as reading and math performance are not reasonably well established.
Neurobiological underpinnings of ADHD
Structural brain imaging
The cerebral cortex comprises grey matter, consists mostly of cell bodies, and is the most recent brain region to be developed in mammals evolutionarily. It is anatomically divided into lobes or areas that perform specific functions. Over the past 30 years, researchers have used Magnetic Resonance Imaging (MRI) to analyze the thickness, volume, and architecture of different areas of the brain to understand structural brain abnormalities in ADHD. The most consistent find- ing is reduced total cerebral cortex volume (3–8%) across all lobes (occipital, temporal, parietal, and frontal), predominantly in the prefrontal cortex (Carmona et al., 2005).
Structural abnormalities in the prefrontal cortex are of particular interest due to their association with ADHD-related Executive Function deficits. Shaw and colleagues (2007) found a delay in brain maturation (older age of achieving peak cortical thickness) using MRI results across a large longitudinal sample comparing children diagnosed with ADHD to typically developing (TD) children. Peak cortical thickness in the cerebral cortex was attained at approximately 7 years of age in TD children but not until 10 years of age in children with ADHD, with the most prominent delays observed in superior and dorsal lateral prefrontal cortices. Consequently, the structural development of the part of the brain that controls attention, evaluation of reward contingencies, higher order motor control, impulsivity, and WM is approximately 2.5 to 3 years behind in approximately 81%
of children with ADHD.
Functional brain activity
The lobes of the cerebral cortex are anchored by white matter tracts that are largely comprised of the fatty, myelinated axons of neurons whose main purpose is to facilitate communication to subcortial structures among the lobes of the cerebral cortex.
A meta-analytic review examining subcortical region development in children with ADHD revealed reduced volume in multiple regions (accumbens, amygdala, caudate, hippocampus, and putamen) that underlie a wide range of functions including goal- directed behavior, emotional regulation, motivation/reward processing, memory consolidation, and motor control (Hoogman et al., 2017). These findings imply that the noted cortical deficits associated with ADHD may be secondary to diminished communicative abilities among subcortical regions.
Brain hypoactivity and arousal
Consistent with structural MRI studies, electroencephalogram (EEG) techniques have revealed aberrant activity in the dorsolateral frontostriatal and mesocortico - limbic circuits in ADHD, which may contribute to Executive Function and motivational deficits, respectively. EEG measures the electrical output of neuronal firing across the cerebral cortex. Findings from EEG studies consistently show increased low-frequency theta wave (4–7 Hz) activity in individuals with ADHD compared to healthy controls (Snyder & Hall, 2006), particularly in frontal and central midline cortical regions, and considered indicative of cortical underarousal.
Although EEGs are particularly useful for answering questions about when neurons are firing, they are somewhat unreliable at determining wherein the brain the electrical signal originates. Functional magnetic resonance imaging (fMRI) helps provide this information (i.e., spatial specificity) and offers a metabolic rationale for the correlation between low-frequency wave activity observed in EEG and underarousal (hypoactivation/fewer neurons firing) of certain brain areas in children with ADHD. fMRI measures the amount of oxygen the brain recruits via blood vessels while performing cognitive tasks and compares the measurement between groups (ADHD vs. TD) or between a baseline (easy task) and an active phase (difficult task). In general, task-based fMRI studies reveal hypoactivation of the frontostriatal, frontoparietal, and mesocorticolimbic circuits in children with ADHD relative to TD children. That is, less oxygen is recruited to neurons that connect the frontal lobe (responsible for planning, organizing, integrating long-term and short-term memories, evaluating reward) to the striatum (motor coordination), parietal lobe (language and mathematical operations), and limbic system (emotional regulation, memory formation, motivation/reward).
A popular theory related to altered neuronal connectivity in children with ADHD involves the default mode network (DMN). The DMN is a neural circuit that involves pieces of the cingulate, medial prefrontal, and lateral and inferior parietal lobes and is thought to manage self-referential cognitions, introspection, and mind wandering.
In a typically developing person, the DMN switches off when there is a goal-directed task and the cognitive control network (CCN)—which encompasses the anterior cingulate, frontal, prefrontal, insula, and posterior parietal lobes integral to Working Memory, inhibitory control, and set-shifting—becomes activated. fMRI investiga - tions reveal that the DMN is overactive and the CCN is underactive in children with ADHD relative to TD children during tasks requiring high attentional demands.
In summary, structural MRI studies have identified delayed development of cortical and subcortical brain tissue, and EEGs and fMRIs investigations have identified underarousal of frontal/prefrontal brain areas and circuits in children with ADHD. Although underdevelopment may beget underarousal, it is interesting to note that the Shaw et al. (2007) study identified delayed cortical development in most (81%), but not all children with ADHD. Perhaps the remaining 19% of children have intact cortical development, but underaroused (decreased neuronal activity) cortical regions. This ADHD-HI presentation subgroup would likely be normalized by an active psychostimulant regimen secondary to increased activity of neurons that transmit dopamine (DA) and norepinephrine (NE) in underaroused/hypoactive brain regions.
Impact of the disorder in daily functioning
Academic and learning outcomes
Children with ADHD are susceptible to myriad adverse academic and learning- related outcomes. Relative to their typically developing peers, childhood ADHD is associated with higher rates of grade retention and use of special education services, lower grade point averages and classroom productivity. Children with ADHD also score lower on standardized academic achievement measures, and fewer graduate from high school (68% vs. 100%) and attend college (21% vs. 78%) (Barkley, Fischer, Smallish, & Fletcher, 2006; Langberg, Dvorsky, & Evans, 2013). Many of the adverse outcomes described above are associated with or secondary to an increased risk of learning disabilities. For example, comorbidity rates vary between 10% to 92% for any type of learning disability, 59–65% for Specific Learning Disorder in Writing, 11% to 52% for Specific Learning Disorder in Reading, and 5% to 30% for Specific Learning Disorder in Math (DuPaul, Gormley, & Laracy, 2013). Recent growth mixture model analyses also indicate that comorbidity for reading and math deficits is particularly strong and unlikely to improve over time in children who begin elementary school with the combination of behavioral and academic deficits, regardless of whether they receive treatment (DuPaul, Morgan, Farkas, Hillemeier,
& Maczuga, 2016).
Core symptoms of inattention, hyperactivity, and impulsivity alone do not provide a viable explanation for foundational knowledge and academic achieve - ment deficits in ADHD. For example, difficulty paying attention in school is likely to affect the acquisition of learned knowledge; however, children with ADHD continue to experience significant deficiencies in classroom performance and academic achievement even after receiving individually titrated psychostimulant treatment and intensive behavioral treatment to normalize their attention problems (Molina et al., 2009). A more likely mechanism and set of cognitive processes implicated in ADHD-related academic achievement difficulties entails WM based on the (a) large magnitude WM deficits evinced among children with ADHD, and (b) fundamental role WM plays in the acquisition of foundational knowledge