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Puppets, robots, critics, and actors within a taxonomy of attention for developmental disorders

Published online by Cambridge University Press:  03 September 2008

MAUREEN DENNIS*
Affiliation:
Program in Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, Canada Department of Surgery, University of Toronto, Toronto, Canada Department of Psychology, University of Toronto, Toronto, Canada
KATIA J. SINOPOLI
Affiliation:
Program in Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, Canada Department of Psychology, University of Toronto, Toronto, Canada
JACK M. FLETCHER
Affiliation:
Department of Psychology, University of Houston, Houston, Texas
RUSSELL SCHACHAR
Affiliation:
Program in Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, Canada Department of Psychiatry, University of Toronto, Toronto, Canada
*
Correspondence and reprint requests to: Maureen Dennis, Ph.D., Program in Neuroscience and Mental Health, The Hospital for Sick Children, 555 University Avenue, Toronto, Ontario M5G 1X8, Canada. E-mail: [email protected]
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Abstract

This review proposes a new taxonomy of automatic and controlled attention. The taxonomy distinguishes among the role of the attendee (puppet and robot, critic and actor), the attention process (stimulus orienting vs. response control), and the attention operation (activation vs. inhibition vs. adjustment), and identifies cognitive phenotypes by which attention is overtly expressed. We apply the taxonomy to four childhood attention disorders: attention deficit hyperactivity disorder, spina bifida meningomyelocele, traumatic brain injury, and acute lymphoblastic leukemia. Variations in attention are related to specific brain regions that support normal attention processes when intact, and produce disordered attention when impaired. The taxonomy explains group differences in behavioral inattention, hyperactivity, and impulsiveness, as well as medication response. We also discuss issues relevant to theories of the cognitive and neural architecture of attention: functional dissociations within and between automatic and controlled attention; the relative importance of type of brain damage and developmental timing to attention profile; cognitive-energetic models of attention and white matter damage; temporal processing deficits, attention deficits and cerebellar damage; and the issue of cognitive phenotypes as candidate endophenotypes. (JINS, 2008, 14, 673–690.)

Type
Critical Review
Copyright
Copyright © The International Neuropsychological Society 2008

INTRODUCTION

Attention is unobservable, so models of attention and its components are based on inferences about how an individual perceives, thinks, and acts. This article presents a new, three-dimensional functional taxonomy that organizes contingent relationships among perception, cognition, and movement into a framework for understanding attention and its disorders in children. Herein, we:

  1. a. Describe the architecture of the taxonomy in terms of three unobservable constructs and an observable cognitive phenotype.

  2. b. Apply the taxonomy to four childhood attention disorders, making functional comparisons within each disorder.

  3. c. Demonstrate compatibility of the taxonomy with the neurobiology of attention.

  4. d. Compare behavioral profiles of inattention, impulsivity, and hyperactivity across disorders and predict treatment responsiveness.

  5. e. Discuss some theoretical issues pertaining to attention and predict attention profiles in disorders not yet studied.

ATTENTION TAXONOMY

Stimulus Orienting Versus Response Control

Models of attention include both stimulus orienting and response control. Stimulus orienting is the automatic capture of attention by salient sensations (James, Reference James1890; more recently, automatic disengaging and shifting attention, Mirsky et al., Reference Mirsky, Anthony, Duncan, Ahearn and Kellam1991; Posner & Peterson, Reference Posner and Peterson1990; filtering of salience information, Knudsen, Reference Knudsen2007; or creating saliency maps, Treue, Reference Treue2003). Response control is the voluntary direction of a motor response, corresponding to Posner and Peterson's (Reference Posner and Peterson1990) anterior attention system and to Knudsen's (Reference Knudsen2007) response selection. Being an unobservable construct, attention is inferred in both stimulus orienting and response control from manipulations of the relation between sensation and movement. In stimulus orienting, inhibition of return (IOR) is inferred from the contingencies between motor engaging and disengaging. In response control, stopping an ongoing action is inferred from the relation between go and stop actions.

A new taxonomy (Figure 1) was prompted by considerations relevant to the specific aims. First, we aimed to integrate stimulus orienting and response control into a single taxonomy. Some models of attention used in childhood clinical disorders focus on only one process; for example, Barkley's (Reference Barkley1997) model of attention considers only response control. Second, we wanted to distinguish among operations within stimulus orienting and response control. Some earlier models of attention that considered both processes (e.g., Mirsky et al., Reference Mirsky, Anthony, Duncan, Ahearn and Kellam1991; Posner & Peterson, Reference Posner and Peterson1990) have not separated activation, inhibition, and adjustment. Third, we aimed to incorporate recent parsings of attendee roles (e.g., the distinction in striatal learning between a “critic” who evaluates performance and an “actor” who performs) and cognitive phenotypes (e.g., the distinction in response control between restraining a prepotent response and canceling an ongoing response). Fourth, we wanted to integrate the three attention dimensions into a factorially structured taxonomy to identify both functional assets and deficits. Such an integration will facilitate functional comparisons both within and across clinical disorders and generate not only descriptions, but also principled inferences about the neural and behavioral correlates of attention.

Fig. 1. Attention taxonomy.

Puppet Versus Robot Versus Critic Versus Actor

Within stimulus orienting, the attendee may be a puppet or robot. We devised the puppet metaphor to capture the idea of a passive attendee whose attention is driven by bottom-up, stimulus-driven orienting to exogenous (external) stimuli, such as a flash of light. We devised the robot metaphor to capture the idea of an active attendee whose orienting is top-down and task-driven, in accord with endogenous (internal) programs, scripts, or symbols, such as an arrow.

Within response control, the attendee may be a critic or an actor. The critic metaphor captures the idea of looped, model-driven responding, involving an active attendee who evaluates performance options and reward contingencies in light of an existing model of desired behavior. The actor metaphor captures the idea of a top-down, action-driven, active attendee responding in accordance with an instructional set and attention priorities. We adopted the actor-critic metaphors from habit-driven learning (Dayan & Balleine, Reference Dayan and Balleine2002; O'Reilly & Frank, Reference O'Reilly and Frank2006) and animal studies separating a dorsal striatum (actor) role in performance from a ventral striatum (actor and critic) role in performance and learning (Atallah et al., Reference Atallah, Lopez-Paniagua, Rudy and O'Reilly2007).

Activation Versus Inhibition Versus Adjustment

The attendee is involved in activation, inhibition, or adjustment. Activation enables directed attention towards the attended material. Inhibition refers to diverse attention processes, some of which concern automatic avoidance of previously attended locations (e.g., IOR), and some of which involve voluntary acts of inhibitory control (e.g., stopping an ongoing action in response to a signal). Adjustment refers to a number of evaluative-regulative processes by which previous attention modifies subsequent attention (Larson et al., Reference Larson, Aronoff and Stearns2007), including error detection, performance monitoring, and adjusting the contingency between present action and future reward (Holroyd & Coles, Reference Holroyd and Coles2002; Nigg et al., Reference Nigg, Willcutt, Doyle and Sonuga-Barke2005; Sagvolden et al., Reference Sagvolden, Aase, Zeiner and Berger1998).

Attention Measures Express Cognitive Phenotypes

The italicized entries in Figure 1 are cognitive phenotypes, which are overt and measurable expressions of the attention constructs. For each cognitive phenotype, we identify a representative task measure, below.

The attendee as puppet

Activation enables automatic stimulus engagement. The engage cognitive phenotype may be measured by the time to orient to a target following an exogenous cue, such as a flash of light (Posner & Peterson, Reference Posner and Peterson1990). Inhibition enables the attendee to avoid orienting to a previously attended location or stimulus. The IOR cognitive phenotype is indexed by a longer time to return to a previously attended cue location (Klein, Reference Klein2000). Adjustment enables a disengage process to withdraw attention from one stimulus so that it may be moved to another. The disengagement cognitive phenotype may be measured by disengagement cost, the time to detach from an exogenous cue conditionalized on engage time (Dennis et al., Reference Dennis, Edelstein, Copeland, Frederick, Francis, Hetherington, Blaser, Kramer, Drake, Brandt and Fletcher2005a).

The attendee as robot

Activation enables a voluntary focus on the stimulus. The focus cognitive phenotype may be measured by time to attend to a target following an endogenous cue, such as a symbol or an arrow (Posner & Peterson, Reference Posner and Peterson1990). Inhibition slows responses to recently ignored stimulus relative to new stimuli. The negative priming (NP) cognitive phenotype may be measured by a longer time to attend to recently ignored stimuli (Tipper, Reference Tipper1992). Adjustment enables set shift to redirect attention. The shift cognitive phenotype may be measured by shifting attention in response to an endogenous cue (Schmitter-Edgecombe & Langill, Reference Schmitter-Edgecombe and Langill2006).

The attendee as critic

Activation enables a voluntary allocation of attention. The divide cognitive phenotype may be measured by the ability to activate concurrent attention streams (e.g., Manly et al., Reference Manly, Robertson, Anderson and Nimmo-Smith1999). Inhibition enables the suppression of one of two interfering schemata or behaviors. The conflict cognitive phenotype may be measured by the ability to perform a controlled act while inhibiting a prepotent or competing response (e.g., to say “Day” for a moon picture, Gerstadt et al., Reference Gerstadt, Hong and Diamond1994, or to inhibit an automatic process like word decoding in favor of a controlled process like color naming, Stroop, Reference Stroop1935). Adjustment enables monitoring of response conflict, errors, and top-down response control (Larson et al., Reference Larson, Aronoff and Stearns2007). The conflict cognitive phenotype may be measured by error detection and performance adjustment (Holroyd & Coles, Reference Holroyd and Coles2002).

The attendee as actor

Activation concerns response control. The sustain cognitive phenotype may be measured by the slope of the curve of attentional vigilance over time (Seidel & Joschko, Reference Seidel and Joschko1990). Inhibition enables cancellation or withdrawal of a response being executed. The cancel cognitive phenotype may be measured by canceling an act being executed (e.g., the stop-signal task, Logan, Reference Logan, Dagenbach and Carr1994). Adjustment enables withholding or delaying a prepotent response. The restrain cognitive phenotype may be measured by restraining a response (e.g., Axelrod et al., Reference Axelrod, Leiber and Noonan1978) or delaying an action (e.g., Gordon, Reference Gordon1983).

Interrelation of Attention Processes

The taxonomy parses a set of attention processes and roles that normally work together in a complex choreography (Mesulam, Reference Mesulam1990). Bottom-up, top-down, and looped operations operate in the same attention space. Stimulus orienting serves as a circuit breaker for response control (as when a flash of lightning draws attention from a book and we orient to the window). Dissociable inhibitory processes work together; for example, IOR not only aids visual search, but also helps adjust behavioral demands in a dynamic environment (Ivanoff & Taylor, Reference Ivanoff and Taylor2006). Arousal influences the level of activation. Controlled attention helps maintain instructional set, even for stimulus orienting tasks.

While the key to the taxonomy is attendee roles in stimulus orienting and response control, time is a thread throughout, and the terms time binding (Dennis, Reference Dennis, Risberg and Grafman2006) and intertemporal competence (Barkley, Reference Barkley1997) characterize temporal processes in attention, such as time estimation, time management, and rule maintenance (Barkley et al., Reference Barkley, Koplowitz, Anderson and McMurray1997). The taxonomy does not explicitly address working memory, which is the product of currently activated attention, including the activated subset that can be manipulated or inhibited (i.e., the products of the right side of Figure 1). Although it is not an account of executive function, the taxonomy does address executive constructs like response control, conflict, and monitoring.

APPLYING THE TAXONOMY TO CHILDHOOD ATTENTION DISORDERS

Overview

Disordered attention characterizes several childhood conditions, including attention deficit hyperactivity disorder considered as a primary form of adaptive impairment (P-ADHD, Barkley, Reference Barkley1997), and other congenital brain malformations such as spina bifida meningomyelocele (SBM; Dennis et al., Reference Dennis, Edelstein, Copeland, Frederick, Francis, Hetherington, Blaser, Kramer, Drake, Brandt and Fletcher2005a, Reference Dennis, Edelstein, Copeland, Frederick, Francis, Hetherington, Blaser, Kramer, Drake, Brandt and Fletcher2005b) and Sotos syndrome (a haploinsufficiency of the Nuclear receptor Set Domain containing protein 1 gene, NSD 1; de Boer et al., Reference de Boer, Roder and Wit2006; Kurotaki et al., Reference Kurotaki, Imaizumi, Harada, Masuno, Kondoh, Nagai, Ohashi, Naritomi, Tsukahara, Makita, Sugimoto, Sonoda, Hasegawa, Chinen, Tomita Ha, Kinoshita, Mizuguchi, Yoshiura Ki, Ohta, Kishino, Fukushima, Niikawa and Matsumoto2002). Impaired attention is also a consequence of acquired brain insults, including traumatic brain injury (TBI; Levin et al., Reference Levin, Hanten, Max, Li, Swank, Ewing-Cobbs, Dennis, Menefee and Schachar2007), childhood brain tumors (Dennis et al., Reference Dennis, Hetherington and Spiegler1998), and acute lymphoblastic leukemia (ALL; Schatz et al., Reference Schatz, Kramer, Ablin and Matthay2004).

Using the taxonomy in Figure 1, we now review attention in four disorders that vary in prevalence, etiology, and developmental course: P-ADHD, TBI, SBM, and ALL. Attention deficits define P-ADHD, and occur in a subset of children with the three other disorders, in which the presenting problem is explicit brain injury. In P-ADHD and SBM, attention is disordered early in development; in contrast, in TBI and ALL, disordered attention is acquired after some period of normal development.

To facilitate the review, we consider two paradigmatic tasks for stimulus orienting (covert orienting, Figure 2) and response control (stop signal, Figure 3). Most components of Figure 1 can be understood in the context of these two tasks. We also summarize the review in Table 1.

Fig. 2. Covert stimulus orienting paradigms. In exogenous orienting (left), the participant maintains central fixation and then an exogenous cue, such as a luminance change, appears to one side of fixation, followed by a target, to which the participant must respond. In this example, the brightness cue will facilitate target detection because it draws attention to the side on which the target will appear (a misleading cue would have appeared on the side opposite to the upcoming target). In endogenous orienting (right), the participant maintains central fixation, which is then replaced by a central endogenous cue, such as an arrow, followed by a target, to which the participant must respond. In this example, the arrow cue will facilitate target detection because it draws attention to the side on which the target will appear (a misleading arrow would have directed attention to the side opposite to the upcoming target).

Fig. 3. Stop signal paradigm. The participant fixates a central dot and then a go stimulus appears, either an X indicating a left hand response (shown in figure) or an O indicating a right hand response. One-third of the trials involve a stop signal (a background color change) following the go signal to indicate that the participant should not respond. Because of the adaptively manipulated delay interval between go and stop signals, each participant will fail to stop on half of the stop trials. Failed stop trials activate the error detection system, so that go trials that follow a failed stop trial (circled in figure) will be slower than go trials that do not follow failures to stop.

Table 1. Robots, puppets, critics, and actors: The fractionation of attention in developmental disorders

Note

Bold entries are from strong, clear data; regular text entries represent a less clear, more limited, or more qualified database, or data from related tasks or age group. Intact or impaired refer to group, not individual, data.

Primary Attention Deficit Hyperactivity Disorder

P-ADHD affects 4–7% of children worldwide (Szatmari, Reference Szatmari and Weiss1992) and is defined by hyperactive, impulsive, inattentive, and/or maladaptive behavior (Barkley, Reference Barkley2004; Goldman et al., Reference Goldman, Genel, Bezman and Slanetz1998; Jensen et al., Reference Jensen, Kettle, Roper, Sloan, Dulcan, Hoven, Bird, Bauermeister and Payne1999). P-ADHD persists into adulthood, although heterogeneity in ADHD is considerable throughout development (Barkley et al., Reference Barkley, Murphy and Fischer2008), with hyperactivity being more common in children than in adults (Biederman et al., Reference Biederman, Mick and Faraone2000).

Puppet and robot

Meta-analysis of 14 studies on exogenous stimulus orienting (Figure 2) in children with P-ADHD show preserved engage and move operations (Huang-Pollock & Nigg, Reference Huang-Pollock and Nigg2003). Children with P-ADHD have normal IOR (Li et al., Reference Li, Chang and Lin2003). Neither adolescents (Pritchard et al., Reference Pritchard, Neumann and Rucklidge2007) nor adults (Nigg et al., Reference Nigg, Butler, Huang-Pollock and Henderson2002) with P-ADHD exhibit difficulties with NP. Children with P-ADHD show no set shifting deficits (Piek et al., Reference Piek, Dyck, Francis and Conwell2007; Riccio et al., Reference Riccio, Homack, Jarratt and Wolfe2006).

Critic and actor

Children with P-ADHD often have response inhibition deficits (Barkley, Reference Barkley1997; McLean et al., Reference McLean, Dowson, Toone, Young, Bazanis, Robbins and Sahakian2004; Nigg, Reference Nigg2003; Pennington & Ozonoff, Reference Pennington and Ozonoff1996; Rhodes et al., Reference Rhodes, Coghill and Matthews2005; Schachar et al., Reference Schachar, Tannock, Marriott and Logan1995; Westerberg et al., Reference Westerberg, Hirvikoski, Forssberg and Klingberg2004), especially on the stop signal task (Figure 3; Willcutt et al., Reference Willcutt, Doyle, Nigg, Faraone and Pennington2005). Children with P-ADHD have deficits both in the ability to cancel a prepared response with a signal to stop (stop signal presented with a variable delay after go signal) and to restrain a strong response tendency pending a signal to stop (stop and go signals presented concurrently) (Schachar et al., Reference Schachar, Logan, Robaey, Chen, Ickowicz and Barr2007). These children cannot delay responding to achieve a motivationally salient outcome (Kuntsi et al., Reference Kuntsi, Oosterlaan and Stevenson2001; Neef et al., Reference Neef, Bicard and Endo2001; Schweitzer & Sulzer-Azaroff, Reference Schweitzer and Sulzer-Azaroff1995; Sonuga-Barke, Reference Sonuga-Barke1994; Sonuga-Barke et al., Reference Sonuga-Barke, Williams, Hall and Saxton1996; Tripp & Alsop, Reference Tripp and Alsop2001).

Divided attention is impaired in children with P-ADHD, whether treated or drug-naïve (Pasini et al., Reference Pasini, Paloscia, Alessandrelli, Porfirio and Curatolo2007; Tucha et al., Reference Tucha, Walitza, Mecklinger, Sontag, Kubber, Linder and Lange2006). Children and adults with P-ADHD are impaired on Stroop interference (Lansbergen et al., Reference Lansbergen, Kenemans and van Engeland2007), suggesting conflict impairment. Children with P-ADHD fail to slow after errors, indicating difficulties in monitoring errors, post-error adjustment, or conflict management (Schachar et al., Reference Schachar, Chen, Logan, Ornstein, Crosbie, Ickowicz and Pakulak2004b).

Children with P-ADHD struggle to sustain attention over time (Seidel & Joschko, Reference Seidel and Joschko1990); they show increased reaction time (RT) over trial blocks and commit more omission errors (Anderson et al., Reference Anderson, Anderson and Anderson2006; Brewer et al., Reference Brewer, Fletcher, Hiscock and Davidson2001; but see Huang-Pollock & Nigg, Reference Huang-Pollock and Nigg2003). Increased performance variability includes transient temporal fluctuations in attention (Teicher et al., Reference Teicher, Lowen, Polcari, Foley and McGreenery2004), more variable RT to primary task stimuli (Alderson et al., Reference Alderson, Rapport and Kofler2007), lower response predictability (Aase et al., Reference Aase, Meyer and Sagvolden2006; Aase & Sagvolden, Reference Aase and Sagvolden2005), higher intraindividual variability (Douglas, Reference Douglas, Quay and Hogan1999; Klein et al., Reference Klein, Wendling, Huettner, Ruder and Peper2006), and increased RT, especially in the slow tail of the distribution (Hervey et al., Reference Hervey, Epstein and Curry2004, Reference Hervey, Epstein, Curry, Tonev, Eugene, Keith, Hinshaw, Swanson and Hechtman2006; Leth-Steensen et al., Reference Leth-Steensen, Elbaz and Douglas2000).

Spina Bifida Meningomyelocele

Spina bifida is a common disabling birth defect, occurring in about 19.3 per 100,000 live births in North America (Martin et al., Reference Martin, Hamilton, Sutton, Ventura, Menacker and Kirmeyer2006). The most severe form, spina bifida meningomyelocele (SBM), occurs in 90% of cases (Detrait et al., Reference Detrait, George, Etchevers, Gilbert, Vekemans and Speer2005). Compared to siblings or to normative samples, children with SBM are more distractible and less attentive (Ammerman et al., Reference Ammerman, Kane, Slomka, Reigel, Franzen and Gadow1998; Burmeister et al., Reference Burmeister, Hannay, Copeland, Fletcher, Boudousquie and Dennis2005; Colvin et al., Reference Colvin, Yeates, Enrile and Coury2003; Rose & Holmbeck, Reference Rose and Holmbeck2007; Vachha & Adams, Reference Vachha and Adams2005) and around one-quarter to one-third is inattentive (Burmeister et al., Reference Burmeister, Hannay, Copeland, Fletcher, Boudousquie and Dennis2005; Davidovitch et al., Reference Davidovitch, Manning-Courtney, Hartmann, Watson, Lutkenhoff and Oppenheimer1999; Fletcher et al., Reference Fletcher, Copeland, Frederick, Blaser, Kramer, Northrup, Hannay, Brandt, Francis, Villarreal, Drake, Laurent, Townsend, Inwood, Boudousquie and Dennis2005). It is not clear whether attention deficits extend into adulthood.

Puppet and robot

Children with SBM show accurate but slow covert orienting to both exogenous and endogenous cues (a deficit in the engage and focus processes; Figure 2), but increased disengagement costs only to exogenous cues (a deficit in the disengage/move process, Dennis et al., Reference Dennis, Edelstein, Copeland, Frederick, Francis, Hetherington, Blaser, Kramer, Drake, Brandt and Fletcher2005a). Those with beaking of the midbrain tectum show attenuated IOR (Dennis et al., Reference Dennis, Edelstein, Copeland, Frederick, Francis, Hetherington, Blaser, Kramer, Drake, Brandt and Fletcher2005b). Their normal disengagement costs for endogenously cued information suggests intact NP.

Critic and actor

Children with SBM have not been evaluated on tests of divided attention. They exhibit difficulties with speed of response rather than conflict; for example, they show deficient naming speed but not poorer Stroop interference (Fletcher et al., Reference Fletcher, Brookshire, Landry, Bohan, Davidson, Francis, Levin, Brandt, Kramer and Morris1996a,Reference Fletcher, McCauley, Brandt, Bohan, Kramer, Francis, Thorstad and Brookshireb). Some monitor skills appear intact: They adapt to prismatic distortion (Colvin et al., Reference Colvin, Yeates, Enrile and Coury2003), respond to error information with corrective saccades (Salman et al., Reference Salman, Sharpe, Eizenman, Lillakas, To, Westall, Steinbach and Dennis2006b), and recalibrate movement after forced ballistic movement errors (Dennis et al., Reference Dennis, Jewell, Edelstein, Brandt, Hetherington, Blaser and Fletcher2006).

Children with SBM can sustain attention over time, and their RT does not increase over time (Brewer et al., Reference Brewer, Fletcher, Hiscock and Davidson2001; Swartwout et al., Reference Swartwout, Cirino, Hampson, Fletcher, Brandt and Dennisin press). Studies of commission errors are not consistent even on similar tasks, with some finding decreased (Colvin et al., Reference Colvin, Yeates, Enrile and Coury2003) and others finding increased error rates (Swartwout et al., Reference Swartwout, Cirino, Hampson, Fletcher, Brandt and Dennisin press), so the nature of restraint is unclear, especially in the absence of prototypic response control tasks (see Figure 3). Delay has not been studied.

Traumatic Brain Injury

Traumatic brain injury (TBI) is frequent in children and adolescents (180 in 100,000 youths annually, Kraus & McArthur, Reference Kraus and McArthur1996; Kraus et al., Reference Kraus, Rock and Hemyari1990), and long-term neuropsychological deficits include inattention (Yeates, Reference Yeates, Yeates, Taylor and Ris2000). Premorbid P-ADHD contributes to post-TBI attention symptoms (Gerring et al., Reference Gerring, Brady, Chen, Vasa, Grados, Bandeen-Roche, Bryan and Denckla1998, Reference Gerring, Brady, Chen, Quinn, Herskovits, Bandeen-Roche, Denckla and Bryan2000; Levin et al., Reference Levin, Hanten, Max, Li, Swank, Ewing-Cobbs, Dennis, Menefee and Schachar2007; Max et al., Reference Max, Lindgren, Knutson, Pearson, Ihrig and Welborn1998), although some 15–20% of TBI survivors with no ADHD history meet diagnostic criteria for secondary ADHD (S-ADHD; Gerring et al., Reference Gerring, Brady, Chen, Vasa, Grados, Bandeen-Roche, Bryan and Denckla1998, Reference Gerring, Brady, Chen, Quinn, Herskovits, Bandeen-Roche, Denckla and Bryan2000; Herskovits et al., Reference Herskovits, Megalooikonomou, Davatzikos, Chen, Bryan and Gerring1999; Max et al., Reference Max, Schachar, Levin, Ewing-Cobbs, Chapman, Dennis, Saunders and Landis2005b, Reference Max, Schachar, Levin, Ewing-Cobbs, Chapman, Dennis, Saunders and Landis2005c; Slomine et al., Reference Slomine, Salorio, Grados, Vasa, Christensen and Gerring2005; Yeates et al., Reference Yeates, Armstrong, Janusz, Taylor, Wade, Stancin and Drotar2005), and even more develop subthreshold attention symptoms.

S-ADHD is associated not only with severe TBI (Max et al., Reference Max, Lansing, Koele, Castillo, Bokura, Schachar, Collings and Williams2004) but also with mild or moderate TBI (Gerring et al., Reference Gerring, Brady, Chen, Vasa, Grados, Bandeen-Roche, Bryan and Denckla1998, Reference Gerring, Brady, Chen, Quinn, Herskovits, Bandeen-Roche, Denckla and Bryan2000; Herskovits et al., Reference Herskovits, Megalooikonomou, Davatzikos, Chen, Bryan and Gerring1999; Max et al., Reference Max, Lindgren, Knutson, Pearson, Ihrig and Welborn1998; Max et al., Reference Max, Manes, Robertson, Mathews, Fox and Lancaster2005a, Reference Max, Schachar, Levin, Ewing-Cobbs, Chapman, Dennis, Saunders and Landis2005b; Schachar et al., Reference Schachar, Levin, Max, Purvis and Chen2004a; Slomine et al., Reference Slomine, Salorio, Grados, Vasa, Christensen and Gerring2005), as well as with high levels of pre-injury behavioral difficulties (Schachar et al., Reference Schachar, Levin, Max, Purvis and Chen2004a), maladaptive function, or psychosocial adversity (Gerring et al., Reference Gerring, Brady, Chen, Vasa, Grados, Bandeen-Roche, Bryan and Denckla1998; Max et al., Reference Max, Lansing, Koele, Castillo, Bokura, Schachar, Collings and Williams2004, Reference Max, Schachar, Levin, Ewing-Cobbs, Chapman, Dennis, Saunders and Landis2005b, Reference Max, Schachar, Levin, Ewing-Cobbs, Chapman, Dennis, Saunders and Landis2005c). S-ADHD manifests as early as 3 months post-TBI (Gerring et al., Reference Gerring, Brady, Chen, Vasa, Grados, Bandeen-Roche, Bryan and Denckla1998, Reference Gerring, Brady, Chen, Quinn, Herskovits, Bandeen-Roche, Denckla and Bryan2000) and persists over years (Gerring et al., Reference Gerring, Brady, Chen, Vasa, Grados, Bandeen-Roche, Bryan and Denckla1998; Levin et al., Reference Levin, Hanten, Max, Li, Swank, Ewing-Cobbs, Dennis, Menefee and Schachar2007; Max et al., Reference Max, Schachar, Levin, Ewing-Cobbs, Chapman, Dennis, Saunders and Landis2005c). Inattentive symptoms peak at six months post-injury and later decline, whereas hyperactive/impulsive symptoms fluctuate for two years (Levin et al., Reference Levin, Hanten, Max, Li, Swank, Ewing-Cobbs, Dennis, Menefee and Schachar2007) and then diminish (Levin et al., Reference Levin, Hanten, Max, Li, Swank, Ewing-Cobbs, Dennis, Menefee and Schachar2007; Max et al., Reference Max, Schachar, Levin, Ewing-Cobbs, Chapman, Dennis, Saunders and Landis2005b, Reference Max, Schachar, Levin, Ewing-Cobbs, Chapman, Dennis, Saunders and Landis2005c). Although poor inhibitory control improves over time (Leblanc et al., Reference Leblanc, Chen, Swank, Ewing-Cobbs, Barnes, Dennis, Max, Levin and Schachar2005), children with TBI with or without S-ADHD exhibit impaired long-term attention (e.g., Dennis et al., Reference Dennis, Wilkinson, Koski, Humphreys, Broman and Michel1995; Konrad et al., Reference Konrad, Gauggel, Manz and Scholl2000a, Reference Konrad, Gauggel, Manz and Scholl2000b; Schachar et al., Reference Schachar, Levin, Max, Purvis and Chen2004a).

Puppet and robot

Young adults with severe TBI have intact engage and disengage/move processes (Bate et al., Reference Bate, Mathias and Crawford2001). Adults with TBI shift set as well as controls (Schmitter-Edgecombe & Langill, Reference Schmitter-Edgecombe and Langill2006) and show no NP deficits (Ries & Marks, Reference Ries and Marks2005; Simpson & Schmitter-Edgecombe, Reference Simpson and Schmitter-Edgecombe2000), suggesting intact endogenous stimulus orienting.

Critic and actor

Children with mild or severe TBI slow less than controls after making an error (Ornstein et al., Reference Ornstein, Levin, Chen, Hanten, Ewing-Cobbs, Dennis, Max, Logan and Schacharin press), suggesting monitor impairment. Children with severe TBI have divided attention deficits, especially as task demands increase (Catroppa et al., Reference Catroppa, Anderson, Morse, Haritou and Rosenfeld2007). Conflict difficulty characterizes TBI: Stroop errors occur more frequently in both the short term and long term in children and adolescents with mild TBI complicated by abnormalities detected by computed tomography (CT) scans (Levin et al., Reference Levin, Hanten, Roberson, Li, Ewing-Cobbs, Dennis, Chapman, Max, Hunter, Schachar, Luerssen and Swank2008) or with moderate-severe TBI (Chadwick et al., Reference Chadwick, Rutter, Shaffer and Shrout1981; Nolan & Mathieu, Reference Nolan and Mathieu2000; Ward et al., Reference Ward, Shum, McKinlay, Baker and Wallace2006). Children with TBI have difficulty sustaining attention (Dennis et al., Reference Dennis, Wilkinson, Koski, Humphreys, Broman and Michel1995), and those with S-ADHD tend to have longer RT (Slomine et al., Reference Slomine, Salorio, Grados, Vasa, Christensen and Gerring2005). Children with TBI, or children with S-ADHD and TBI, exhibit longer stop signal RT than controls (Konrad et al., Reference Konrad, Gauggel, Manz and Scholl2000a, Reference Konrad, Gauggel, Manz and Scholl2000b; Leblanc et al., Reference Leblanc, Chen, Swank, Ewing-Cobbs, Barnes, Dennis, Max, Levin and Schachar2005), especially those with more severe injury and a de novo diagnosis of S-ADHD (Schachar et al., Reference Schachar, Levin, Max, Purvis and Chen2004a), suggesting cancel difficulty. Children with TBI make more commission errors (Konrad et al., Reference Konrad, Gauggel, Manz and Scholl2000a; Levin et al., Reference Levin, Hanten, Zhang, Swank and Hunter2004), and exhibit an inability to delay their motor responses, with or without reward (Dennis et al., Reference Dennis, Wilkinson, Koski, Humphreys, Broman and Michel1995; Konrad et al., Reference Konrad, Gauggel, Manz and Scholl2000a), suggesting difficulty with cancel/restrain processes.

Acute Lymphoblastic Leukemia

Of the 3,000–6,000 people diagnosed with acute lymphoblastic leukemia (ALL) each year in the United States, two-thirds are children (Cortes & Kantarjian, Reference Cortes and Kantarjian1995; Parker et al., Reference Parker, Tong, Bolden and Wingo1997), and 80% will survive (Parker et al., Reference Parker, Tong, Bolden and Wingo1997). ALL is associated with cognitive deficits, including poor attention, after treatment with cranial radiation therapy (CRT) and/or chemotherapy, (Christie et al., Reference Christie, Leiper, Chessells and Vargha-Khadem1995; Cousens et al., Reference Cousens, Waters, Said and Stevens1988; Fletcher & Copeland, Reference Fletcher and Copeland1988; Goff et al., Reference Goff, Anderson and Cooper1980; Hertzberg et al., Reference Hertzberg, Huk, Ueberall, Langer, Meier, Dopfer, Skalej, Lackner, Bode, Janssen, Zintl and Beck1997; Mennes et al., Reference Mennes, Stiers, Vandenbussche, Vercruysse, Uyttebroeck, De Meyer and Van Cool2005), especially with early exposure and longer time since treatment (Cousens et al., Reference Cousens, Waters, Said and Stevens1988; Jankovic et al., Reference Jankovic, Brouwers, Valsecchi, Van Veldhuizen, Huisman, Kamphuis, Kingma, Mor, Van Dongen-Melman, Ferronato, Mancini, Spinetta and Masera1994). Attention problems are evident at least 7–14 years following ALL treatment (Lockwood et al., Reference Lockwood, Bell and Colegrove1999; Schatz et al., Reference Schatz, Kramer, Ablin and Matthay2004), especially in females and in children treated with CRT at a younger age (Lockwood et al., Reference Lockwood, Bell and Colegrove1999; Schatz et al., Reference Schatz, Kramer, Ablin and Matthay2004).

Puppet and robot

Children with ALL treated with CRT, especially those radiated in early childhood, have difficulties with stimulus orienting (Lockwood et al., Reference Lockwood, Bell and Colegrove1999). ALL participants treated with CRT demonstrate an exaggerated cue validity effect, suggesting disengage difficulties (Schatz et al., Reference Schatz, Kramer, Ablin and Matthay2004). Compared to controls, children with ALL have slower but equally accurate focused attention (Mennes et al., Reference Mennes, Stiers, Vandenbussche, Vercruysse, Uyttebroeck, De Meyer and Van Cool2005). Set shifting is compromised in children with ALL, even those with chemotherapy but no CRT (Buizer et al., Reference Buizer, de Sonneville, van den Heuvel-Eibrink and Veerman2005), although intensive chemotherapy (Buizer et al., Reference Buizer, de Sonneville, van den Heuvel-Eibrink and Veerman2005) and CRT (Lockwood et al., Reference Lockwood, Bell and Colegrove1999) both exacerbate deficits.

Childhood survivors of ALL are slow but accurate when focusing attention (Lahteenmaki et al., Reference Lahteenmaki, Holopainen, Krause, Helenius, Salmi and Heikki2001), especially if treated with methotrexate (Mennes et al., Reference Mennes, Stiers, Vandenbussche, Vercruysse, Uyttebroeck, De Meyer and Van Cool2005). IOR and negative priming are yet to be studied.

Critic and actor

Divided attention, monitoring, and conflict have not been studied in ALL. Some studies report intact sustained attention in children with ALL (Mennes et al., Reference Mennes, Stiers, Vandenbussche, Vercruysse, Uyttebroeck, De Meyer and Van Cool2005; Rodgers et al., Reference Rodgers, Marckus, Kearns and Windebank2003; but see Spiegler et al., Reference Spiegler, Kennedy, Maze, Greenberg, Weitzman, Hitzler and Nathan2006). However, Lockwood et al. (Reference Lockwood, Bell and Colegrove1999) found that children with ALL had poor sustained attention, especially if female, diagnosed at a younger age, treated with higher doses of methotrexate (Buizer et al., Reference Buizer, de Sonneville, van den Heuvel-Eibrink and Veerman2005), or treated with CRT at a younger age.

Children with ALL treated with methotrexate chemotherapy are slower and more variable than (but as accurate as) controls on response inhibition tasks (Mennes et al., Reference Mennes, Stiers, Vandenbussche, Vercruysse, Uyttebroeck, De Meyer and Van Cool2005). CRT does not exacerbate inhibition problems (Lockwood et al., Reference Lockwood, Bell and Colegrove1999). Children with ALL treated with chemotherapy differ from age norms in delayed response tasks (Spiegler et al., Reference Spiegler, Kennedy, Maze, Greenberg, Weitzman, Hitzler and Nathan2006). The sustain process appears intact in many, if not all children with ALL, and response inhibition (whether cancel or restrain/delay) processes are sometimes unimpaired.

NEUROBIOLOGY OF ATTENTION

The taxonomy is function-based, but we next demonstrate that: a) the elements of the taxonomy are compatible with the neurobiology of stimulus orienting and response control; and b) within each of the childhood attention disorders, functional deficits are present when the putative neural substrates are impaired and absent when they are intact.

Stimulus Orienting and the Posterior Cortex, Midbrain, and Superior Colliculus

Deficits in disengaging (not shifting attentional set) are associated with superior colliculus and posterior cortex lesions in adults (Posner et al., Reference Posner, Walker, Friedrich and Rafal1984). IOR deficits in adults are associated with superior colliculus lesions (Rafal et al., Reference Rafal, Calabresi, Brennan and Sciolto1989, Reference Rafal, Henik and Smith1991; Sapir et al., Reference Sapir, Soroker, Berger and Henik1999) and midbrain lesions such as those in progressive supranuclear palsy (Rafal & Grimm, Reference Rafal and Grimm1981; Rafal et al., Reference Rafal, Posner, Friedman, Inhoff and Bernstein1988).

SBM involves malformations of the cerebellum, hindbrain, and midbrain (Fletcher et al., Reference Fletcher, Copeland, Frederick, Blaser, Kramer, Northrup, Hannay, Brandt, Francis, Villarreal, Drake, Laurent, Townsend, Inwood, Boudousquie and Dennis2005; Salman et al., Reference Salman, Blaser, Sharpe and Dennis2006a). The midbrain abnormality, tectal beaking (Barkovich et al., Reference Barkovich, Kuzniecky, Jackson, Guerrini and Dobyns2005; Fletcher et al., Reference Fletcher, Copeland, Frederick, Blaser, Kramer, Northrup, Hannay, Brandt, Francis, Villarreal, Drake, Laurent, Townsend, Inwood, Boudousquie and Dennis2005), is a mechanical consequence of brain development in a small posterior fossa (McLone & Knepper, Reference McLone and Knepper1989). Brain growth in SBM affects posterior more than anterior cortical structures, producing selective reduction in posterior cortical volume (Dennis et al., Reference Dennis, Fitz, Netley, Sugar, Harwood-Nash, Hendrick, Hoffman and Humphreys1981; Fletcher et al., Reference Fletcher, Brookshire, Landry, Bohan, Davidson, Francis, Levin, Brandt, Kramer and Morris1996a,Reference Fletcher, McCauley, Brandt, Bohan, Kramer, Francis, Thorstad and Brookshireb; Juranek et al., Reference Juranek, Fletcher, Hasan, Breier, Cirino, Alvarez, Diaz, Ewing-Cobbs, Dennis and Papanicolaou2008) and impairments in white matter integrity (Hasan et al., Reference Hasan, Eluvathingal, Kramer, Ewing-Cobbs, Dennis and Fletcher2008a), with relative preservation, even hypertrophy, of anterior cortex (Juranek et al., Reference Juranek, Fletcher, Hasan, Breier, Cirino, Alvarez, Diaz, Ewing-Cobbs, Dennis and Papanicolaou2008) and some cortical and subcortical structures (Hasan et al., Reference Hasan, Sankar, Halphen, Kramer, Ewing-Cobbs, Dennis and Fletcher2008b; Miller et al., Reference Miller, Widjaja, Blaser, Dennis and Raybaud2008).

In SBM, deficits in disengaging and shifting are associated with tectal beaking and posterior brain volume loss (Dennis et al., Reference Dennis, Edelstein, Copeland, Frederick, Francis, Hetherington, Blaser, Kramer, Drake, Brandt and Fletcher2005a), and attenuated IOR is associated with tectal beaking (Dennis et al., Reference Dennis, Edelstein, Copeland, Frederick, Francis, Hetherington, Blaser, Kramer, Drake, Brandt and Fletcher2005b). Individual differences in stimulus orienting deficits are correlated with individual differences in structural brain damage observed in children with SBM in the posterior cortex, midbrain, and superior colliculus.

The midbrain is involved in dopamine dysfunction in children with P-ADHD. Ernst et al. (Reference Ernst, Zametkin, Matochik, Pascualvaca, Jons and Cohen1999) found that accumulation of [F-18]DOPA, a measure of dopa decarboxylase activity in synaptic terminals of dopaminergic-rich regions, was nearly 50% higher in the right midbrain in children with ADHD, measures being correlated with symptom severity. However, this excess of midbrain dopamine does not disrupt stimulus orienting in P-ADHD.

We predict that structural or neurochemical damage to the midbrain should produce stimulus-orienting deficits at any age. For example, childhood acquired midbrain tumors, such as pineal germinomas, should be associated with impaired stimulus orienting.

Response Control and Frontal-Striatal Circuits

Response control develops throughout childhood (Davidson et al., Reference Davidson, Amso, Anderson and Diamond2006; Rubia et al., Reference Rubia, Smith, Woolley, Nosarti, Heyman, Taylor and Brammer2006) and involves two principal dopamine-modulated pathways: a prefrontal-dorsal striatum circuit and an orbitofrontal-ventral striatum circuit. Activation of the superior, medial, and inferior frontal gyri as well as midline networks are associated with withholding and monitoring motor responses (Chevrier et al., Reference Chevrier, Noseworthy and Schachar2007; Rubia et al., Reference Rubia, Russell, Overmeyer, Brammer, Bullmore, Sharma, Simmons, Williams, Giampietro, Andrew and Taylor2001). The withdrawal or canceling of responses has been shown to activate the right inferior frontal gyrus, the right anterior cingulate cortex (ACC), supplementary motor cortex, and caudate (Chevrier et al., Reference Chevrier, Noseworthy and Schachar2007; Rubia et al., Reference Rubia, Russell, Overmeyer, Brammer, Bullmore, Sharma, Simmons, Williams, Giampietro, Andrew and Taylor2001). These data are congruent with the idea of distinct brain systems for intentional actions and the withholding of intended actions (Brass & Haggard, Reference Brass and Haggard2007). Frontal regions are also implicated in conflict management: Better interference control is associated with activity in the right middle frontal gyrus and left inferior frontal gyrus (Bunge et al., Reference Bunge, Ochsner, Desmond, Glover and Gabrieli2001).

There is ongoing debate about the neural basis of error detection and performance monitoring. The extensive limbic connections of the ACC contribute to the modulation of emotional expression (Critchley, Reference Critchley2005), and the dorsal ACC is directly involved in higher-order cognitive functions such as attention and response selection (e.g., Bush et al., Reference Bush, Luu and Posner2000). Although the striatum has an important role as critic, the ACC also supports evaluative aspects of performance monitoring (Dias & Aggleton, Reference Dias and Aggleton2000) that require integration of cognitive and limbic input. It is activated preceding errors (Li et al., Reference Li, Yan, Bergquist and Sinha2007), responds to both internal and external error signals (Holroyd et al., Reference Holroyd, Nieuwenhuis, Yeung, Nystrom, Mars, Coles and Cohen2004), and is more activated by error responses than by correct responses and by error feedback than by correct feedback (Holroyd et al., Reference Holroyd, Nieuwenhuis, Yeung, Nystrom, Mars, Coles and Cohen2004). The dorsal ACC is particularly activated by error detection invoked by failed inhibition trials of the stop signal task (Chevrier et al., Reference Chevrier, Noseworthy and Schachar2007), and by changes in task “sets” that signal adaptive changes in response style (Woodward et al., Reference Woodward, Metzak, Meier and Holroyd2008). The role of the ACC in conflict monitoring may be domain-general because dorsal ACC activity is related to a cognitive conflict between major and minor musical modes (Mizuno & Sugishita, Reference Mizuno and Sugishita2007).

Individuals with P-ADHD show selective cortical thinning of networks serving attention and executive control (Makris et al., Reference Makris, Biederman, Valera, Bush, Kaiser, Kennedy, Caviness, Faraone and Seidman2007). Structural imaging of children with P-ADHD has identified volume reduction in the whole cerebrum (Castellanos et al., Reference Castellanos, Lee, Sharp, Jeffries, Greenstein, Clasen, Blumenthal, James, Ebens, Walter, Zijdenbos, Evans, Giedd and Rapoport2002), cortical gray matter, caudate nucleus, globus pallidus, prefrontal cortex, ACC (Castellanos et al., Reference Castellanos, Giedd, Marsh, Hamburger, Vaituzis, Dickstein, Sarfatti, Vauss, Snell, Lange, Kaysen, Krain, Ritchie, Rajapakse and Rapoport1996; Filipek et al., Reference Filipek, Semrud-Clikeman, Steingard, Renshaw, Kennedy and Biederman1997; Seidman et al., Reference Seidman, Valera, Makris, Monuteaux, Boriel, Kelkar, Kennedy, Caviness, Bush, Aleardi, Faraone and Biederman2006), and especially, the right inferior frontal cortex (Durston et al., Reference Durston, Hulshoff Pol, Schnack, Buitelaar, Steenhuis, Minderaa, Kahn and van Engeland2004; Sowell et al., Reference Sowell, Thompson, Welcome, Henkenius, Toga and Peterson2003), with relatively lesser involvement of the posterior cortex, midbrain, and cerebellum (Berquin et al., Reference Berquin, Giedd, Jacobsen, Hamburger, Krain, Rapoport and Castellanos1998). Various brain regions have been implicated in P-ADHD symptoms (Seidman et al., Reference Seidman, Valera and Makris2005), including dorsolateral prefrontal cortex and orbitofrontal cortex (Spencer et al., Reference Spencer, Biederman and Mick2007), and dysfunction has been identified in dorsolateral and orbitofrontal cortices, ACC, inferior frontal gyri, and striatal-pallidal-thalamic circuits (e.g., Bush et al., Reference Bush, Valera and Seidman2005; Spencer et al., Reference Spencer, Biederman and Mick2007).

Inhibitory control deficits associated with P-ADHD are correlated with functional alterations in a frontostriatal network. Poor interference control in children with P-ADHD is associated with decreased activation of the left inferior frontal gyrus (Vaidya et al., Reference Vaidya, Bunge, Dudukovic, Zalecki, Elliott and Gabrieli2005), and hypoactivation of the dorsal ACC occurs in adults with P-ADHD (Bush et al., Reference Bush, Frazier, Rauch, Seidman, Whalen, Jenike, Rosen and Biederman1999). During inhibition trials, children with P-ADHD fail to activate the right inferior frontal or precentral gyri (Vaidya et al., Reference Vaidya, Bunge, Dudukovic, Zalecki, Elliott and Gabrieli2005), exhibit abnormal activity in the dorsal ACC (no activation, Durston et al., Reference Durston, Tottenham, Thomas, Davidson, Eigsti, Yang, Ulug and Casey2003, hypoactivation, Tamm et al., Reference Tamm, Menon, Ringel and Reiss2004), and exhibit striatal dysfunction, including decreased left caudate activity (Durston et al., Reference Durston, Tottenham, Thomas, Davidson, Eigsti, Yang, Ulug and Casey2003; Vaidya et al., Reference Vaidya, Austin, Kirkorian, Ridlehuber, Desmond, Glover and Gabrieli1998). Poor cancellation by P-ADHD patients is associated with hypoactive mesial prefrontal cortex (i.e., near the dorsal ACC) and ventrolateral prefrontal cortex, and decreased left caudate activity (Rubia et al., Reference Rubia, Overmeyer, Taylor, Brammer, Williams, Simmons and Bullmore1999).

TBI is frequently associated with dysfunction of the prefrontal and frontal cortex (Levin et al., Reference Levin, Fletcher, Kusnerik, Kufera, Lilly, Duffy, Chapman, Mendelsohn and Bruce1996; Wilde et al., Reference Wilde, Hunter, Newsome, Scheibel, Bigler, Johnson, Fearing, Cleavinger, Li, Swank, Pedroza, Roberson, Bachevalier and Levin2005), and corpus callosum and frontal lobe white matter (Levin et al., Reference Levin, Benavidez, Verger-Maestre, Perachio, Song, Mendelsohn and Fletcher2000), with some cerebellar involvement (Spanos et al., Reference Spanos, Wilde, Bigler, Cleavinger, Fearing, Levin, Li and Hunter2007). S-ADHD is associated with damage to neural regions known to be abnormal in P-ADHD, including the orbitofrontal gyrus (Max et al., Reference Max, Schachar, Levin, Ewing-Cobbs, Chapman, Dennis, Saunders and Landis2005b), thalamus (Gerring et al., Reference Gerring, Brady, Chen, Quinn, Herskovits, Bandeen-Roche, Denckla and Bryan2000), and basal ganglia (Gerring et al., Reference Gerring, Brady, Chen, Quinn, Herskovits, Bandeen-Roche, Denckla and Bryan2000; Herskovits et al., Reference Herskovits, Megalooikonomou, Davatzikos, Chen, Bryan and Gerring1999; Max et al., Reference Max, Manes, Robertson, Mathews, Fox and Lancaster2005a; and see Max et al., Reference Max, Schachar, Levin, Ewing-Cobbs, Chapman, Dennis, Saunders and Landis2005c). Children with TBI/S-ADHD also exhibit response inhibition deficits, although there is no clear association with lesion site (Leblanc et al., Reference Leblanc, Chen, Swank, Ewing-Cobbs, Barnes, Dennis, Max, Levin and Schachar2005; Levin et al., Reference Levin, Hanten, Zhang, Swank and Hunter2004). ACC activity in adults with TBI is abnormal during conflict tasks (Soeda et al., Reference Soeda, Nakashima, Okumura, Kuwata, Shinoda and Iwama2005), possibly because of diffuse axonal damage disrupting frontal-cortical and subcortical networks, leading to reduced post-error slowing (Larson et al., Reference Larson, Aronoff and Stearns2007). In children with TBI, inhibitory impairments are correlated with prefrontal injury. Restraining a prepotent response on go/no-go tasks is related to volume of left prefrontal lesions (Levin et al., Reference Levin, Culhane, Mendelsohn, Lilly, Bruce, Fletcher, Chapman, Harward and Eisenberg1993, Reference Levin, Hanten, Zhang, Swank and Hunter2004), as well as to injury severity (Konrad et al., Reference Konrad, Gauggel, Manz and Scholl2000a; Levin et al., Reference Levin, Hanten, Zhang, Swank and Hunter2004, but see Leblanc et al., Reference Leblanc, Chen, Swank, Ewing-Cobbs, Barnes, Dennis, Max, Levin and Schachar2005).

Children with P-ADHD and children with TBI have deficits in response control, with individual differences being correlated with individual differences in prefrontal-dorsal striatum and orbitofrontal-ventral striatum circuits. The caudate, putamen, and globus pallidus are part of a striatal-pallidal-thalamic circuit. In feedforward and feedback relations with the cortex, this circuit modulates inhibitory control and sensitivity to reward (Alexander et al., Reference Alexander, DeLong and Strick1986), which is consistent with the idea that dopaminergic and/or noradrenergic medications affect ADHD by increasing inhibitory effects of frontal cortical activity on subcortical brain regions (Zametkin & Rapoport, Reference Zametkin and Rapoport1987). The thalamus is part of two subcortical networks that are implicated in P-ADHD symptomatology as well as response inhibition (Gerring et al., Reference Gerring, Brady, Chen, Quinn, Herskovits, Bandeen-Roche, Denckla and Bryan2000), and damage to the thalamus produces distractibility and disinhibition (Gentilini et al., Reference Gentilini, De Renzi and Crisi1987). To be sure, there is considerable heterogeneity in the brain systems associated with inhibition. Furthermore, the link of S-ADHD or P-ADHD to the thalamus is less clear than that of either of these disorders to the caudate, putamen, or inferior frontal gyrus.

CROSS-DISORDER COMPARISONS OF INATTENTION, IMPULSIVITY, AND HYPERACTIVITY

Inattentive and/or hyperactive-impulsive behaviors are features of P-ADHD, and exhibited by some children with TBI, SBM, and ALL. The association of inattention, impulsivity, and hyperactivity is strongest in P-ADHD. Between 65% and 90% of children with P-ADHD are hyperactive (Morgan et al., Reference Morgan, Hynd, Riccio and Hall1996; Paternite et al., Reference Paternite, Loney and Roberts1995; Spencer et al., Reference Spencer, Biederman and Mick2007; Wolraich et al., Reference Wolraich, Hannah, Pinnock, Baumgaertel and Brown1996), although the recession of hyperactivity with age may imply an age-dependent association. In TBI and S-ADHD, inattention and impulsivity, but not hyperactivity, are associated, in that most children with S-ADHD do not show hyperactivity, although they may exhibit inattention and impulsivity (Max et al., Reference Max, Manes, Robertson, Mathews, Fox and Lancaster2005a, Reference Max, Schachar, Levin, Ewing-Cobbs, Chapman, Dennis, Saunders and Landis2005b, Reference Max, Schachar, Levin, Ewing-Cobbs, Chapman, Dennis, Saunders and Landis2005c). Children with ALL exhibit some hyperactive symptoms, with approximately one-third of children with ALL achieving a mildly atypical score on the Conners' Parent Rating Scale–Hyperactivity Index (T-score > 60; Conklin, personal communication, November 26, 2007). Unlike those with P-ADHD or S-ADHD, children with SBM rarely show hyperactivity or impulsivity (Fletcher et al., Reference Fletcher, Copeland, Frederick, Blaser, Kramer, Northrup, Hannay, Brandt, Francis, Villarreal, Drake, Laurent, Townsend, Inwood, Boudousquie and Dennis2005).

The cross-disorder comparison of inattentiveness, hyperactivity, and impulsivity prompts three testable predictions about stimulant mediation treatment. Methylphenidate blocks the dopamine transporter (Dresel et al., Reference Dresel, Krause, Krause, LaFougere, Brinkbaumer, Kung, Hahn and Tatsch2000), which has a greater effect on the striatum than on the prefrontal cortex (Durston et al., Reference Durston, Fossella, Casey, Hulshoff Pol, Galvan, Schnack, Steenhuis, Minderaa, Buitelaar, Kahn and van Engeland2005), given that the dopamine transporter gene is more highly expressed in the striatum than in the cortex, where other means of dealing with intrasynaptic dopamine predominate. The first prediction is that methylphenidate should affect response control more than stimulus orienting. This prediction is supported by the data reviewed in this article and also by evidence that methylphenidate specifically affects sustained attention and top-down control, rather than arousal (Johnson et al., Reference Johnson, Barry, Bellgrove, Cox, Kelly, Dáibhis, Daly, Keavey, Watchorn, Fitzgerald, McNicholas, Kirley, Robertson and Gill2008).

P-ADHD is a disorder of neurotransmission (synthesis, release, reuptake, effect) mediated by genes that code for dysfunctional or suboptimally functioning dopamine, whereas S-ADHD arises from damaged neural networks, which may or may not include striatal dysfunction. Given the different underlying mechanisms in the two conditions, the second prediction is that methylphenidate will be more effective in treating response control in P-ADHD than in S-ADHD. Methylphenidate also improves behavioral (not cognitive) hyperactivity/impulsiveness in S-ADHD, although improvement occurs acutely and is less robust than that in children with P-ADHD (Jin & Schachar, Reference Jin and Schachar2004).

Combined inattention and hyperactivity may reflect striatal and prefrontal-striatal dysfunction, whereas inattention may be primarily a problem of the prefrontal cortex and the prefrontal-parietal circuit (Diamond, Reference Diamond2005). This distinction, made within P-ADHD, prompts a third prediction across disorders, that treatment responsiveness should be positively correlated with hyperactivity and impulsiveness (specifically, should be highest in P-ADHD, moderate in S-ADHD, lower in ALL, and lowest in SBM). Stimulants have effectively treated P-ADHD for over more than three decades of randomized clinical trials, with 65% to 75% of individuals with P-ADHD being clinical responders, compared to 4% to 30% of individuals treated with placebo (Greenhill, Reference Greenhill, Jensen and Cooper2002). Granted that a smaller proportion of children with S-ADHD (7%; Levin et al., Reference Levin, Hanten, Max, Li, Swank, Ewing-Cobbs, Dennis, Menefee and Schachar2007) than P-ADHD (56%; Visser et al., Reference Visser, Lesesne and Perou2007) receive stimulant treatment, methylphenidate does improve attention in children after TBI (Mahalick et al., Reference Mahalick, Carmel, Greenberg, Molofsky, Brown, Heary, Marks, Zampella, Hodosh and von der Schmidt1998). Methylphenidate ameliorates attention problems in ALL (Conklin et al., Reference Conklin, Khan, Reddick, Helton, Brown, Howard, Bonner, Christensen, Wu, Xiong and Mulhern2007), and both moderate and low doses of methylphenidate improve parent and teacher attention ratings of ADHD symptoms, as well as teacher ratings of social-academic competence (Mulhern et al., Reference Mulhern, Khan, Kaplan, Helton, Christensen, Bonner, Brown, Xiong, Wu, Gururangan and Reddick2004). Inattention in children with SBM does not respond robustly to methylphenidate treatment. In a large double blind, placebo-controlled trial of methylphenidate medication in a clinic population of children with SBM, Davidovitch et al. (Reference Davidovitch, Manning-Courtney, Hartmann, Watson, Lutkenhoff and Oppenheimer1999) found no statistically significant medication effects (but see positive medication effects in a smaller, heterogeneous sample in Mayes et al., Reference Mayes, Crites, Bixler, Humphrey and Mattison1994).

INFERENCES AND PREDICTIONS

The application of the taxonomy to childhood disorders of attention has produced descriptive comparisons within and between disorders. New information has been added for each condition: for P-ADHD, the diversity of deficits in response control and the intactness of stimulus orienting; for SBM and ALL, the intactness of response control; and for S-ADHD, the similarity to P-ADHD with respect to deficits in response control and adaptive regulation. Individual children with P-ADHD are known to have uncorrelated deficits in multiple processes (e.g., delay intolerance is independent of inhibitory dyscontrol, Solanto et al., Reference Solanto, Abikoff, Sonuga-Barke, Schachar, Logan, Wigal, Hechtman, Hinshaw and Turkel2001; Sonuga-Barke et al., Reference Sonuga-Barke, Houlberg and Hall1994), and we show this to be true for other childhood attention disorders. In addition, our data prompt inferences about theoretical questions and predictions about attention in disorders not yet studied.

Double Dissociation Between Automatic and Controlled Attention

Within- and between-disorder comparisons in childhood conditions have provided functional and neurobiological evidence of a double dissociation between automatic and controlled forms of attention. This is congruent with a long history of adult lesion studies, and also with new evidence from markers of event-related potentials. For example, listening to Mozart's D major sonata K.448 has opposite effects on event-related potentials markers of involuntary and voluntary attention (Zhu et al., Reference Zhu, Zhao, Zhang, Ding, Liu, Ni, Ma and Zhou2008).

Inhibition Is a Diverse Attention Construct

Inhibition constitutes a diverse and often uncorrelated group of functions. In children with P-ADHD, the puppet is intact (normal IOR), but the actor is impaired (poor restrain). Different conditions have the same inhibitory impairment (P-ADHD and TBI both show impaired actor role and have restrain deficits). Adult disorders show differently dissociated forms of inhibition; for example, patients with Parkinson's disease demonstrate intact IOR but impaired endogenously evoked inhibition (NP) (Grande et al., Reference Grande, Crosson, Heilman, Bauer, Kilduff and McGlinchey2006).

Dissociations also exist within and between top-down and bottom-up processes. Children with P-ADHD are impaired on top-down response inhibition of the actor but not on endogenous top-down stimulus orienting of the robot. In children with SBM, bottom-up exogenous stimulus orienting deficits in the puppet are uncorrelated with intact top-down endogenous stimulus orienting in the robot.

Brain Injury Trumps Age at Onset

Anatomy trumps age at onset with respect to the puppet in stimulus orienting, in that SBM and ALL share deficits in this domain despite differences in age at onset, although stimulus-orienting deficits may have different anatomical origins in these two conditions. Anatomy certainly trumps age at onset for response control. Despite differences in age at onset, response control is largely unimpaired in SBM and ALL, and impaired in P-ADHD and TBI/S-ADHD, highlighting the role of anterior brain regions and the subcortical dopaminergic system in the production of response control deficits. Age at onset seems relevant to persistence of deficits in the two congenital conditions and the relative volatility over time of deficits in acquired conditions.

Although both P-ADHD and SBM are congenital conditions, they have distinct attentional and neurobiological profiles. Children with SBM have difficulties with error detection, although not with post-error adjustment. It is possible that they share error detection difficulties with children with P-ADHD because of shared midbrain dysfunction, perhaps related to mesolimbic dopamine (Di Chiara, Reference Di Chiara1998), or mesencephalic function more generally, affecting dorsal ACC and right frontal function. We predict some error detection deficits in children with other forms of structural or neurochemical midbrain dysfunction (e.g., children with pontine tumors).

Temporal Stability of Attention Deficits

Both P-ADHD and SBM have attention deficits that persist over time and, at least for P-ADHD, into adult life. Their common pattern of stability of attention problems over time is consistent with their shared status as genetically based life-long developmental conditions with no period of normal development.

Compared to P-ADHD, children with TBI and S-ADHD have more volatile attention symptoms over time. Children with P-ADHD are evaluated in the school-aged years, and are already into the chronic stage of their attention disorder. It is unclear whether the picture of enhanced symptom volatility in children with TBI and S-ADHD arises because they have been studied in relatively short terms in relation to injury onset. Perhaps S-ADHD recovers over time, while formative brain anomalies ensure that P-ADHD will persist. However, one issue is that the time frame for resolution of cognitive deficits matches long-term TBI degenerative processes (e.g., loss of axonal connections and secondary focal brain atrophy) better than the short-term recovery mechanisms known to be operative (e.g., reduction in inflammatory processes and brain swelling).

Based on our data, we predict that attention deficits, whatever their form, will be more stable over time in developmental conditions (e.g., Sotos syndrome) than in acquired conditions (e.g., childhood strokes).

Cognitive-Energetic Models, White Matter Damage, and Activating the Actor

In their cognitive-energetic model of attention, Russell et al. (Reference Russell, Oades, Tannock, Killeen, Auerbach, Johansen and Sagvolden2006) propose that P-ADHD involves inefficient astrocyte function from deficient ATP production in neurons, over milliseconds, and deficient myelination of axons during development, over months and years. Poor formation and supply of lactate produces inefficient and inconsistent performance in P-ADHD and other white matter disorders (Russell et al., Reference Russell, Oades, Tannock, Killeen, Auerbach, Johansen and Sagvolden2006).

Although ALL treatment produces cortical atrophy (Baron et al., Reference Baron, Fennell and Voeller1995), CRT and/or chemotherapy (Moore, Reference Moore2005) particularly disrupt white matter, disturbances of which range from folate deficiency and subacute myeloencephalopathy to leukoencephalopathy with myelin degeneration and white matter necrosis (Maria et al., Reference Maria, Dennis and Obonsawin1993). Antimetabolites such as methotrexate involved in ALL treatment particularly affect white matter (Cole & Kamen, Reference Cole and Kamen2006). SBM involves two types of white matter disruption, the first involving abnormal white matter development and the second, persistent white matter degeneration with increased age. Diffusion tensor tractography in children with SBM reveals abnormal development in the association pathways (e.g., poor visualization of tracts, impairment in myelination) as well as acquired abnormalities in intrinsic axonal characteristics (Hasan et al., Reference Hasan, Eluvathingal, Kramer, Ewing-Cobbs, Dennis and Fletcher2008a).

The cognitive-energetic model of Russell and colleagues (Reference Russell, Oades, Tannock, Killeen, Auerbach, Johansen and Sagvolden2006) predicts increased response variability with compromised white matter, congenital or acquired. Children with SBM or ALL have little increased variability on sustained attention tasks despite impaired white matter, so our data provide no support for this prediction.

Temporal Processing and the Cerebellum

Temporal processing has been proposed as a key deficit in P-ADHD (e.g., Barkley et al., Reference Barkley, Koplowitz, Anderson and McMurray1997), with a central importance being given to cerebellar abnormalities (Berquin et al., Reference Berquin, Giedd, Jacobsen, Hamburger, Krain, Rapoport and Castellanos1998). The cerebellar abnormalities in P-ADHD are minor compared to the massive cerebellar compromise in SBM, which is associated with abnormalities (in 98%) and volume reductions in the lateral cerebellum (Fletcher et al., Reference Fletcher, Copeland, Frederick, Blaser, Kramer, Northrup, Hannay, Brandt, Francis, Villarreal, Drake, Laurent, Townsend, Inwood, Boudousquie and Dennis2005) and with upward and downward displacement of the cerebellar vermis (Salman et al., Reference Salman, Blaser, Sharpe and Dennis2006a). Children with S-ADHD exhibit the typical P-ADHD attention profile, and are less likely than children with SBM to have cerebellar damage.

Perception of brief time intervals (around 400 ms) is consistently impaired in childhood cerebellar disease (SBM, Dennis et al., Reference Dennis, Edelstein, Hetherington, Copeland, Frederick, Blaser, Kramer, Drake, Brandt and Fletcher2004), adolescents with cerebellar degenerative disease (ataxia-telangiactiasia, Mostofsky et al., Reference Mostofsky, Kunze, Cutting, Lederman and Denckla2000), and adult survivors of childhood cerebellar tumors (Hetherington et al., Reference Hetherington, Dennis and Spiegler2000). Temporal estimation tasks, involving cognitive estimations of longer durations ranging from 4 minutes to a half hour, is intact in adult survivors of childhood cerebellar tumors (Hetherington et al., Reference Hetherington, Dennis and Spiegler2000). Children with P-ADHD cannot estimate long durations, around 4 sec, although they accurately perceive brief durations (Radonovich & Mostofsky, Reference Radonovich and Mostofsky2004), suggesting that the temporal impairment in P-ADHD involves failure to monitor temporal information in working memory rather than a cerebellar central timing deficit (Mahone et al., Reference Mahone, Prahme, Ruble, Mostofsky and Schwartz2007).

Our data temper the view that the cerebellar temporal processing is of primary importance in P-ADHD. Not only is the degree of cerebellar damage unrelated to attention profiles, but children with P-ADHD have temporal estimation rather than timing deficits.

Can Puppets as Well as Actors be Candidate Endophenotypes?

Endophenotypes are hypothetical constructs intervening between genes and symptoms (Almasy & Blangero, Reference Almasy and Blangero2001). Endophenotypes were originally proposed in the context of psychiatric disorders (Gottesman & Gould, Reference Gottesman and Gould2003), but have more recently been used in neurodevelopmental disorders such as ADHD (Aron & Poldrack, Reference Aron and Poldrack2005). Endophenotypes have more explanatory power than the cognitive phenotypes italicized in Figure 1, so we consider whether two of our cognitive phenotypes, response inhibition and IOR, might be considered as candidate endophenotypes. Crosbie et al. (Reference Crosbie, Pérusse, Barr and Schachar2008) examined the theoretical rationale and a priori criteria for validating an endophenotype in P-ADHD and, with Biederman et al. (Reference Biederman, Faraone, Mick, Spencer, Wilens, Kiely, Guite, Ablon, Reed and Warburton1995), propose that a candidate endophenotype should be common in affected individuals (sensitive), relatively unique to the disorder (specific), and relatively uncommon in the general population; they suggest, further, that a powerful way to establish endophenotype status would be to identify markers in cases with genetic, but not acquired, ADHD.

Response inhibition is a candidate endophenotype for P-ADHD (Aron & Poldrack, Reference Aron and Poldrack2005; Crosbie et al., Reference Crosbie, Pérusse, Barr and Schachar2008). While response inhibition deficits are common in P-ADHD, but not in SBM or ALL, and are relatively uncommon in the general population, they also occur in S-ADHD, an acquired condition. A convincing non-genetic etiology for acquired conditions is difficult to demonstrate (Crosbie et al., Reference Crosbie, Pérusse, Barr and Schachar2008), and children with S-ADHD, considered as a group, have elevated rates of P-ADHD. Informative comparisons for invalidating response inhibition as a putative endophenotype would be a study of response inhibition in mild TBI, and a comparison of response inhibition deficits in children with TBI and a de novo S-ADHD diagnosis and those with TBI and preexisting P-ADHD.

Endophenotypes should be state-independent (i.e., should not vary with disease progression or treatment, Crosbie et al., Reference Crosbie, Pérusse, Barr and Schachar2008). Both acquired conditions, TBI and ALL, show cognitive phenotypes that fluctuate with disease characteristics, time since diagnosis, or treatment. Attention is worsened by severe injury in TBI and by adjuvant CRT treatment in ALL, in contrast to the relatively stable patterns of congenital conditions over the lifespan (in P-ADHD and, possibly, in SBM). Cognitive phenotypes in acquired conditions are perhaps less likely than those in congenital conditions to be endophenotypes marking genetic risk.

IOR may be a candidate endophenotype. Children of mothers with a genetic mutation in the folate metabolic pathway share the genetic mutation, have the upper spinal cord lesions (Volcik et al., Reference Volcik, Blanton, Tyerman, Jong, Rott, Page, Romaine and Northrup2000) associated with tectal beaking (Fletcher et al., Reference Fletcher, Copeland, Frederick, Blaser, Kramer, Northrup, Hannay, Brandt, Francis, Villarreal, Drake, Laurent, Townsend, Inwood, Boudousquie and Dennis2005), and have IOR deficits primarily when they have tectal beaking (Dennis et al., Reference Dennis, Edelstein, Copeland, Frederick, Francis, Hetherington, Blaser, Kramer, Drake, Brandt and Fletcher2005b). Children with ALL have a dual compromise of folate metabolism. Part of their treatment-related delayed neurotoxicity is a pharmacologic disruption of CNS folate physiology (Cole & Kamen, Reference Cole and Kamen2006), and they have a genotype involving a folate metabolic mutation linked to inattentive symptoms (Krull et al., Reference Krull, Brouwers, Jain, Zhang, Bomgaars, Dreyer, Mahoney, Bottomley and Okcu2008). While it is not clear that the identical mutations are involved (the C677T methylenetetrahydrofolate is the risk factor for upper spinal lesion level deficits in SBM, Volcik et al., Reference Volcik, Blanton, Tyerman, Jong, Rott, Page, Romaine and Northrup2000, the A1298C methylenetetrahydrofolate genotype is the predominant link to inattention in ALL, Krull et al., Reference Krull, Brouwers, Jain, Zhang, Bomgaars, Dreyer, Mahoney, Bottomley and Okcu2008), there is evidence for a link between folate mutations and inattention. More broadly, candidate endophenotypes for attention disorders might exist, not only in the actor and critic, but also in the puppet and robot.

CONCLUSIONS

Taxonomies are useful to the extent that they organize what is known and direct the search for the unknown. Our taxonomy describes attention within and across childhood attention disorders, is congruent with known neurobiology of attention, and predicts treatment responsiveness. It facilitates critical evaluation of some theoretical positions on attention and predicts specific attention deficits in clinical conditions not yet studied.

ACKNOWLEDGMENTS

The authors' studies in this article were supported by grants from the US National Institutes of Health Program Project Grant P01 HD35946 (JMF, MD), National Institute of Neurological Diseases and Stroke Grant 2R011NS 21889-16 (MD), and grants from The Ontario Mental Health Foundation and The Physicians' Services Research Institute Foundation (MD), and Canadian Institutes of Health Research, MOP 44070, 64277, 74699 and 82796 (RS). No financial conflicts of interest exist with respect to this manuscript. The information in this manuscript and the manuscript itself is an original work that is not currently under review elsewhere and has not been previously published in any form. We thank Brenda J. Spiegler, Ph.D., Arturo Hernandez, Ph.D., and the three JINS reviewers for helpful comments on the manuscript.

References

REFERENCES

Aase, H., Meyer, A., & Sagvolden, T. (2006). Moment-to-moment dynamics of ADHD behaviour in South African children. Behavioral and Brain Functions, 2, 11.CrossRefGoogle ScholarPubMed
Aase, H. & Sagvolden, T. (2005). Moment-to-moment dynamics of ADHD behaviour. Behavioral and Brain Functions, 1, 12.CrossRefGoogle ScholarPubMed
Alderson, R.M., Rapport, M.D., & Kofler, M.J. (2007). Attention-deficit/hyperactivity disorder and behavioral inhibition: A meta-analytic review of the stop-signal paradigm. Journal of Abnormal Child Psychology, 35, 745758.CrossRefGoogle ScholarPubMed
Alexander, G.E., DeLong, M.R., & Strick, P.L. (1986). Parallel organization of functionally segregated circuits linking basal ganglia and cortex. Annual Review of Neuroscience, 9, 357381.CrossRefGoogle ScholarPubMed
Almasy, L. & Blangero, J. (2001). Endophenotypes as quantitative risk factors for psychiatric disease: Rationale and study design. American Journal of Medical Genetics, 105, 4244.3.0.CO;2-9>CrossRefGoogle ScholarPubMed
Ammerman, R.T., Kane, V.R., Slomka, G.T., Reigel, D.H., Franzen, M.D., & Gadow, K.D. (1998). Psychiatric symptomalogy and family functioning in children with spina bifida. Journal of Clinical Psychology in Medical Settings, 5, 449465.CrossRefGoogle Scholar
Anderson, V., Anderson, D., & Anderson, P. (2006). Comparing attentional skills in children with acquired and developmental central nervous system disorders. Journal of the International Neuropsychological Society, 12, 519531.CrossRefGoogle ScholarPubMed
Aron, A.R. & Poldrack, R.A. (2005). The cognitive neuroscience of response inhibition: Relevance for genetic research in attention-deficit/hyperactivity disorder. Biological Psychiatry, 57, 12851292.CrossRefGoogle ScholarPubMed
Atallah, H.E., Lopez-Paniagua, D., Rudy, J.W., & O'Reilly, R.C. (2007). Separate neural substrates for skill learning and performance in the ventral and dorsal striatum. Nature Neuroscience, 10, 126131.CrossRefGoogle ScholarPubMed
Axelrod, S., Leiber, L., & Noonan, M. (1978). Classification of random forms and distortions presented to the left or right visual field. Perceptual and Motor Skills, 47, 615621.CrossRefGoogle ScholarPubMed
Barkley, R.A. (1997). Behavioral inhibition, sustained attention, and executive functions: Constructing a unifying theory of ADHD. Psychological Bulletin, 121, 6594.CrossRefGoogle ScholarPubMed
Barkley, R.A. (2004). Driving impairments in teens and adults with attention-deficit/hyperactivity disorder. The Psychiatric Clinics of North America, 27, 233260.CrossRefGoogle ScholarPubMed
Barkley, R.A., Koplowitz, S., Anderson, T., & McMurray, M.B. (1997). Sense of time in children with ADHD: Effects of duration, distraction, and stimulant medication. Journal of the International Neuropsychological Society, 3, 359369CrossRefGoogle ScholarPubMed
Barkley, R.A., Murphy, K.R., & Fischer, M. (2008). ADHD in Adults: What the Science Says. New York: Guilford Press.Google Scholar
Barkovich, A.J., Kuzniecky, R.I., Jackson, G.D., Guerrini, R., & Dobyns, W.B. (2005). A developmental and genetic classification for malformations of cortical development. Neurology, 65, 18731887.CrossRefGoogle ScholarPubMed
Baron, I.S., Fennell, E.B., & Voeller, K.K. (1995). Pediatric neuropsychology in the medical setting. New York: Oxford University Press.Google Scholar
Bate, A.J., Mathias, J.L., & Crawford, J.R. (2001). The covert orienting of visual attention following severe traumatic brain injury. Journal of Clinical and Experimental Neuropsychology, 23, 386398.CrossRefGoogle ScholarPubMed
Berquin, P.C., Giedd, J.N., Jacobsen, L.K., Hamburger, S.D., Krain, A.L., Rapoport, J.L., & Castellanos, F.X. (1998). Cerebellum in attention-deficit hyperactivity disorder: A morphometric MRI study. Neurology, 50, 10871093.CrossRefGoogle ScholarPubMed
Biederman, J., Faraone, S.V., Mick, E., Spencer, T., Wilens, T., Kiely, K., Guite, J., Ablon, J.S., Reed, E., & Warburton, R. (1995). High risk for attention deficit hyperactivity disorder among children of parents with childhood onset of the disorder: A pilot study. American Journal of Psychiatry, 152, 431435.Google ScholarPubMed
Biederman, J., Mick, E., & Faraone, S.V. (2000). Age-dependent decline of symptoms of attention deficit hyperactivity disorder: Impact of remission definition and symptom type. American Journal of Psychiatry, 157, 816818.CrossRefGoogle ScholarPubMed
Brass, M. & Haggard, P. (2007). To do or not to do: The neural signature of self-control. The Journal of Neuroscience, 27, 91419145.CrossRefGoogle Scholar
Brewer, V.R., Fletcher, J.M., Hiscock, M., & Davidson, K.C. (2001). Attention processes in children with shunted hydrocephalus versus attention deficit-hyperactivity disorder. Neuropsychology, 15, 185198.CrossRefGoogle ScholarPubMed
Buizer, A.I., de Sonneville, L.M., van den Heuvel-Eibrink, M.M., & Veerman, A.J. (2005). Chemotherapy and attentional dysfunction in survivors of childhood acute lymphoblastic leukemia: Effect of treatment intensity. Pediatric Blood & Cancer, 45, 281290.CrossRefGoogle ScholarPubMed
Bunge, S.A., Ochsner, K.N., Desmond, J.E., Glover, G.H., & Gabrieli, J.D. (2001). Prefrontal regions involved in keeping information in and out of mind. Brain, 124, 20742086.CrossRefGoogle Scholar
Burmeister, R., Hannay, H.J., Copeland, K., Fletcher, J.M., Boudousquie, A., & Dennis, M. (2005). Attention problems and executive functions in children with spina bifida and hydrocephalus. Child Neuropsychology, 11, 265283.CrossRefGoogle ScholarPubMed
Bush, G., Frazier, J.A., Rauch, S.L., Seidman, L.J., Whalen, P.J., Jenike, M.A., Rosen, B.R., & Biederman, J. (1999). Anterior cingulate cortex dysfunction in attention-deficit/hyperactivity disorder revealed by fMRI and the Counting Stroop. Biological Psychiatry, 45, 15421552.CrossRefGoogle ScholarPubMed
Bush, G., Luu, P., & Posner, M.I. (2000). Cognitive and emotional influences in anterior cingulate cortex. Trends in Cognitive Science, 4, 214222.CrossRefGoogle ScholarPubMed
Bush, G., Valera, E.M., & Seidman, L.J. (2005). Functional neuroimaging of attention-deficit/hyperactivity disorder: A review and suggested future directions. Biological Psychiatry, 57, 12731284.CrossRefGoogle ScholarPubMed
Castellanos, F.X., Giedd, J.N., Marsh, W.L., Hamburger, S.D., Vaituzis, A.C., Dickstein, D.P., Sarfatti, S.E., Vauss, Y.C., Snell, J.W., Lange, N., Kaysen, D., Krain, A.L., Ritchie, G.F., Rajapakse, J.C., & Rapoport, J.L. (1996). Quantitative brain magnetic resonance imaging in attention-deficit hyperactivity disorder. Archives of General Psychiatry, 53, 607616.CrossRefGoogle ScholarPubMed
Castellanos, F.X., Lee, P.P., Sharp, W., Jeffries, N.O., Greenstein, D.K., Clasen, L.S., Blumenthal, J.D., James, R.S., Ebens, C.L., Walter, J.M., Zijdenbos, A., Evans, A.C., Giedd, J.N., & Rapoport, J.L. (2002). Developmental trajectories of brain volume abnormalities in children and adolescents with attention-deficit/hyperactivity disorder. The Journal of the American Medical Association, 288, 17401748.CrossRefGoogle ScholarPubMed
Catroppa, C., Anderson, V.A., Morse, S.A., Haritou, F., & Rosenfeld, J.V. (2007). Children's attentional skills 5 years post-TBI. Journal of Pediatric Psychology, 32, 354369.CrossRefGoogle ScholarPubMed
Chadwick, O., Rutter, M., Shaffer, D., & Shrout, P.E. (1981). A prospective study of children with head injuries: IV specific cognitive deficits. Journal of Clinical Neuropsychology, 3, 101120.CrossRefGoogle ScholarPubMed
Chevrier, A.D., Noseworthy, M.D., & Schachar, R. (2007). Dissociation of response inhibition and performance monitoring in the stop signal task using event-related fMRI. Human Brain Mapping, 28, 13471358.CrossRefGoogle ScholarPubMed
Christie, D., Leiper, A.D., Chessells, J.M., & Vargha-Khadem, F. (1995). Intellectual performance after presymptomatic cranial radiotherapy for leukaemia: Effects of age and sex. Archives of Disease in Childhood, 73, 136140.CrossRefGoogle ScholarPubMed
Cole, P.D. & Kamen, B.A. (2006). Delayed neurotoxicity associated with therapy for children with acute lymphoblastic leukemia. Mental Retardation and Developmental Disabilities Research Reviews, 12, 174183.CrossRefGoogle ScholarPubMed
Colvin, A.N., Yeates, K.O., Enrile, B.G., & Coury, D.L. (2003). Motor adaptation in children with myelomeningocele: Comparison to children with ADHD and healthy siblings. Journal of the International Neuropsychological Society, 9, 642652.CrossRefGoogle ScholarPubMed
Conklin, H.M., Khan, R.B., Reddick, W.E., Helton, S., Brown, R., Howard, S.C., Bonner, M., Christensen, R., Wu, S., Xiong, X., & Mulhern, R.K. (2007). Acute neurocognitive response to methylphenidate among survivors of childhood cancer: A randomized, double-blind, cross-over trial. Journal of Pediatric Psychology, 32, 11271139.CrossRefGoogle ScholarPubMed
Cortes, J.E. & Kantarjian, H.M. (1995). Acute lymphoblastic leukemia: A comprehensive review with emphasis on biology and therapy. Cancer, 76, 23932417.3.0.CO;2-P>CrossRefGoogle Scholar
Cousens, P., Waters, B., Said, J., & Stevens, M. (1988). Cognitive effects of cranial irradiation in leukaemia: A survey and meta-analysis. Journal of Child Psychology and Psychiatry, and Allied Disciplines, 29, 839852.CrossRefGoogle ScholarPubMed
Critchley, H.D. (2005). Neural mechanisms of autonomic, affective, and cognitive integration. Journal of Comparative Neurology, 493, 154166.CrossRefGoogle ScholarPubMed
Crosbie, J., Pérusse, S., Barr, C.L., & Schachar, R.J. (2008). Validating psychiatric endophenotypes: Inhibitory control and attention deficit hyperactivity disorder. Neuroscience and Biobehavioural Reviews, 32, 4055.CrossRefGoogle ScholarPubMed
Davidovitch, M., Manning-Courtney, P., Hartmann, L.A., Watson, J., Lutkenhoff, M., & Oppenheimer, S. (1999). The prevalence of attentional problems and the effect of methylphenidate in children with myelomenigocele. Pediatric Rehabilitation, 3, 2935.Google ScholarPubMed
Davidson, M.C., Amso, D., Anderson, L.C., & Diamond, A. (2006). Development of cognitive control and executive functions from 4 to 13 years: Evidence from manipulations of memory, inhibition, and task switching. Neuropsychologia, 44, 20372078.CrossRefGoogle ScholarPubMed
Dayan, P. & Balleine, B.W. (2002). Reward, motivation, and reinforcement learning. Neuron, 36, 285298.CrossRefGoogle ScholarPubMed
de Boer, L., Roder, I., & Wit, J.M. (2006). Psychosocial, cognitive, and motor functioning in patients with suspected Sotos syndrome: A comparison between patients with and without NSD1 gene alterations. Developmental Medicine and Child Neurology, 48, 582588.CrossRefGoogle ScholarPubMed
Dennis, M. (2006). Prefrontal cortex: Typical and atypical development. In Risberg, J. & Grafman, J. (Eds.), The frontal lobes: Development, function and pathology (pp. 128162). New York: Cambridge University Press.CrossRefGoogle Scholar
Dennis, M., Edelstein, K., Copeland, K., Frederick, J., Francis, D.J., Hetherington, R., Blaser, S., Kramer, L.A., Drake, J.M., Brandt, M.E., & Fletcher, J.M. (2005a). Covert orienting to exogenous and endogenous cues in children with spina bifida. Neuropsychologia, 43, 976987.CrossRefGoogle ScholarPubMed
Dennis, M., Edelstein, K., Copeland, K., Frederick, J.A., Francis, D.J., Hetherington, R., Blaser, S., Kramer, L.A., Drake, J.M., Brandt, M.E. & Fletcher, J.M. (2005b). Space-based inhibition of return in children with spina bifida. Neuropsychology, 19, 456465.CrossRefGoogle ScholarPubMed
Dennis, M., Edelstein, K., Hetherington, R., Copeland, K., Frederick, J., Blaser, S.E., Kramer, L.A., Drake, J.M., Brandt, M., & Fletcher, J.M. (2004). Neurobiology of perceptual and motor timing in children with spina bifida in relation to cerebellar volume. Brain, 127, 12921301.CrossRefGoogle ScholarPubMed
Dennis, M., Fitz, C.R., Netley, C.T., Sugar, J., Harwood-Nash, D.C., Hendrick, E.B., Hoffman, H.J., & Humphreys, R.P. (1981). The intelligence of hydrocephalic children. Archives of Neurology, 38, 607615.CrossRefGoogle ScholarPubMed
Dennis, M., Hetherington, C.R., & Spiegler, B.J. (1998). Memory and attention after childhood brain tumors. Medical and Pediatric Oncology, Suppl 1, 2533.3.0.CO;2-A>CrossRefGoogle ScholarPubMed
Dennis, M., Jewell, D., Edelstein, K., Brandt, M.E., Hetherington, R., Blaser, S.E., & Fletcher, J.M. (2006). Motor learning in children with spina bifida: Intact learning and performance on a ballistic task. Journal of the International Neuropsychological Society, 12, 598608.CrossRefGoogle ScholarPubMed
Dennis, M., Wilkinson, M., Koski, L., & Humphreys, R. (1995). Attention deficits in the long term after childhood head injury. In Broman, S. & Michel, M.E. (Eds.), Traumatic head injury in children (pp. 165187). New York: Oxford University Press.Google Scholar
Detrait, E.R., George, T.M., Etchevers, H.C., Gilbert, J.R., Vekemans, M., & Speer, M.C. (2005). Human neural tube defects: Developmental biology, epidemiology, and genetics. Neurotoxicology and Teratology, 27, 515524.CrossRefGoogle ScholarPubMed
Diamond, A. (2005). Attention-deficit disorder (attention-deficit/hyperactivity disorder without hyperactivity): A neurobiologically and behaviorally distinct disorder from attention-deficit/hyperactivity disorder (with hyperactivity). Development and Psychopathology, 17, 807825.CrossRefGoogle ScholarPubMed
Dias, R. & Aggleton, J.P. (2000). Effects of selective excitotoxic prefrontal lesions on acquisition of nonmatching- and matching-to-place in the T-maze in the rat: Differential involvement of the prelimbic-infralimbic and anterior cingulate cortices in providing behavioural flexibility. The European Journal of Neuroscience, 12, 44574466.CrossRefGoogle ScholarPubMed
Di Chiara, G. (1998). A motivational learning hypothesis of the role of mesolimbic dopamine in compulsive drug use. Journal of Psychopharmacology, 12, 5467.CrossRefGoogle ScholarPubMed
Douglas, V.I. (1999). Cognitive control processes in attention-deficit/hyperactivity disorder. In Quay, H.C. & Hogan, A.E. (Eds.), Handbook of disruptive behavior disorders (pp. 105138). New York: Plenum.CrossRefGoogle Scholar
Dresel, S., Krause, J., Krause, K.H., LaFougere, C., Brinkbaumer, K., Kung, H.F., Hahn, K., & Tatsch, K. (2000). Attention deficit hyperactivity disorder: Binding of [99mTc]TRODAT-1 to the dopamine transporter before and after methylphenidate treatment. European Journal of Nuclear Medicine, 27, 15181524.CrossRefGoogle Scholar
Durston, S., Fossella, J.A., Casey, B.J., Hulshoff Pol, H.E., Galvan, A., Schnack, H.G., Steenhuis, M.P., Minderaa, R.B., Buitelaar, J.K., Kahn, R.S., & van Engeland, H. (2005). Differential effects of DRD4 and DAT1 genotype on fronto-striatal gray matter volumes in a sample of subjects with attention deficit hyperactivity disorder, their unaffected siblings, and controls. Molecular Psychiatry, 10, 678685.CrossRefGoogle Scholar
Durston, S., Hulshoff Pol, H.E., Schnack, H.G., Buitelaar, J.K., Steenhuis, M.P., Minderaa, R.B., Kahn, R.S., & van Engeland, H. (2004). Magnetic resonance imaging of boys with attention-deficit/hyperactivity disorder and their unaffected siblings. Journal of the American Academy of Child and Adolescent Psychiatry, 43, 332340.CrossRefGoogle ScholarPubMed
Durston, S., Tottenham, N.T., Thomas, K.M., Davidson, M.C., Eigsti, I.M., Yang, Y., Ulug, A.M., & Casey, B.J. (2003). Differential patterns of striatal activation in young children with and without ADHD. Biological Psychiatry, 53, 871878.CrossRefGoogle ScholarPubMed
Ernst, M., Zametkin, A.J., Matochik, J.A., Pascualvaca, D., Jons, P.H., & Cohen, R.M. (1999). High midbrain [18F]DOPA accumulation in children with attention deficit hyperactivity disorder. The American Journal of Psychiatry, 156, 12091215.CrossRefGoogle ScholarPubMed
Filipek, P.A., Semrud-Clikeman, M., Steingard, R.J., Renshaw, P.F., Kennedy, D.N., & Biederman, J. (1997). Volumetric MRI analysis comparing subjects having attention-deficit hyperactivity disorder with normal controls. Neurology, 48, 589601.CrossRefGoogle ScholarPubMed
Fletcher, J.M., Brookshire, B.L., Landry, S.H., Bohan, T.P., Davidson, K.C., Francis, D.J., Levin, H.S., Brandt, M.E., Kramer, L.A., & Morris, R.D. (1996a). Attentional skills and executive functions in children with early hydrocephalus. Developmental Neuropsychology, 12, 5376.CrossRefGoogle Scholar
Fletcher, J.M. & Copeland, D.R. (1988). Neurobehavioral effects of central nervous system prophylactic treatment of cancer in children. Journal of Clinical and Experimental Neuropsychology, 10, 495537.CrossRefGoogle ScholarPubMed
Fletcher, J.M., Copeland, K., Frederick, J.A., Blaser, S.E., Kramer, L.A., Northrup, H., Hannay, H.J., Brandt, M.E., Francis, D.J., Villarreal, G., Drake, J.M., Laurent, J.P., Townsend, I., Inwood, S., Boudousquie, A., & Dennis, M. (2005). Spinal lesion level in spina bifida: A source of neural and cognitive heterogeneity. Journal of Neurosurgery, 102, 268279.Google ScholarPubMed
Fletcher, J.M., McCauley, S.R., Brandt, M.E., Bohan, T.P., Kramer, L.A., Francis, D.J., Thorstad, K., & Brookshire, B.L. (1996b). Regional brain tissue composition in children with hydrocephalus. relationships with cognitive development. Archives of Neurology, 53, 549557.CrossRefGoogle ScholarPubMed
Gentilini, M., De Renzi, E., & Crisi, G. (1987). Bilateral paramedian thalamic artery infarcts: Report of eight cases. Journal of Neurology, Neurosurgery, and Psychiatry, 50, 900909.CrossRefGoogle ScholarPubMed
Gerring, J., Brady, K., Chen, A., Quinn, C., Herskovits, E., Bandeen-Roche, K., Denckla, M.B., Bryan, R.N. (2000). Neuroimaging variables related to development of secondary attention deficit hyperactivity disorder after closed head injury in children and adolescents. Brain Injury, 14, 205218.Google ScholarPubMed
Gerring, J.P., Brady, K.D., Chen, A., Vasa, R., Grados, M., Bandeen-Roche, K.J., Bryan, R.N., & Denckla, M.B. (1998). Premorbid prevalence of ADHD and development of secondary ADHD after closed head injury. Journal of the American Academy of Child and Adolescent Psychiatry, 37, 647654.CrossRefGoogle ScholarPubMed
Gerstadt, C.L., Hong, Y.J., & Diamond, A. (1994). The relationship between cognition and action: Performance of children 3.5–7 years old on a Stroop-like day-night test. Cognition, 53, 129153.CrossRefGoogle Scholar
Goff, J.R., Anderson, H.R. Jr., & Cooper, P.F. (1980). Distractibility and memory deficits in long-term survivors of acute lymphoblastic leukemia. Journal of Developmental and Behavioral Pediatrics, 1, 158163.CrossRefGoogle ScholarPubMed
Goldman, L.S., Genel, M., Bezman, R.J., & Slanetz, P.J. (1998). Diagnosis and treatment of attention-deficit/hyperactivity disorder in children and adolescents. The Journal of the American Medical Association, 279, 11001107.CrossRefGoogle ScholarPubMed
Gordon, M. (1983). The Gordon diagnostic system. De Witt, NY: Gordon Systems.Google Scholar
Gottesman, I.I. & Gould, T.D. (2003). The endophenotype concept in psychiatry: Etymology and strategic intentions. The American Journal of Psychiatry, 160, 636645.CrossRefGoogle ScholarPubMed
Grande, L.J., Crosson, B., Heilman, K.M., Bauer, R.M., Kilduff, P., & McGlinchey, R.E. (2006). Visual selective attention in Parkinson's disease: Dissociation of exogenous and endogenous inhibition. Neuropsychology, 20, 370382.CrossRefGoogle ScholarPubMed
Greenhill, L.L. (2002). Stimulant medication treatment of children with attention deficit hyperactivity disorder. In Jensen, P.S. & Cooper, J.R. (Eds.), Attention deficit hyperactivity disorder: State of science best practices (pp. 927). Kingston, NJ: Civic Research Institute.Google Scholar
Hasan, K.M., Eluvathingal, T.J., Kramer, L.A., Ewing-Cobbs, L., Dennis, M., & Fletcher, J.M. (2008a). White matter microstructural abnormalities in children with spina bifida myelomeningocele and hydrocephalus: A diffusion tensor tractography study of the association pathways. Journal of Magnetic Resonance Imaging, 27, 700709.CrossRefGoogle ScholarPubMed
Hasan, K.M., Sankar, A., Halphen, C., Kramer, L.A., Ewing-Cobbs, L., Dennis, M., & Fletcher, J.M. (2008b). Quantitative diffusion tensor imaging and intellectual outcomes in spina bifida. Journal of Neurosurgery: Pediatrics, 2, 7582.Google ScholarPubMed
Herskovits, E.H., Megalooikonomou, V., Davatzikos, C., Chen, A., Bryan, R.N., & Gerring, J.P. (1999). Is the spatial distribution of brain lesions associated with closed-head injury predictive of subsequent development of attention-deficit/hyperactivity disorder? Analysis with brain-image database. Radiology, 213, 389394.CrossRefGoogle ScholarPubMed
Hertzberg, H., Huk, W.J., Ueberall, M.A., Langer, T., Meier, W., Dopfer, R., Skalej, M., Lackner, H., Bode, U., Janssen, G., Zintl, F., & Beck, J.D. (1997). CNS late effects after ALL therapy in childhood. Part I: Neuroradiological findings in long-term survivors of childhood ALL–an evaluation of the interferences between morphology and neuropsychological performance. The German late effects working group. Medical and Pediatric Oncology, 28, 387400.3.0.CO;2-C>CrossRefGoogle ScholarPubMed
Hervey, A.S., Epstein, J.N., & Curry, J.F. (2004). Neuropsychology of adults with attention-deficit/hyperactivity disorder: A meta-analytic review. Neuropsychology, 18, 485503.CrossRefGoogle ScholarPubMed
Hervey, A.S., Epstein, J.N., Curry, J.F., Tonev, S., Eugene, A.L., Keith, C.C., Hinshaw, S.P., Swanson, J.M., & Hechtman, L. (2006). Reaction time distribution analysis of neuropsychological performance in an ADHD sample. Child Neuropsychology, 12, 125140.CrossRefGoogle Scholar
Hetherington, R., Dennis, M., & Spiegler, B. (2000). Perception and estimation of time in long-term survivors of posterior fossa tumors. Journal of the International Neuropsycholgical Society, 6, 682692.CrossRefGoogle ScholarPubMed
Holroyd, C.B. & Coles, M.G. (2002). The neural basis of human error processing: Reinforcement learning, dopamine, and the error-related negativity. Psychological Review, 109, 679709.CrossRefGoogle ScholarPubMed
Holroyd, C.B., Nieuwenhuis, S., Yeung, N., Nystrom, L., Mars, R.B., Coles, M.G., & Cohen, J.D. (2004). Dorsal anterior cingulate cortex shows fMRI response to internal and external error signals. Nature Neuroscience, 7, 497498.CrossRefGoogle ScholarPubMed
Huang-Pollock, C.L. & Nigg, J.T. (2003). Searching for the attention deficit in attention deficit hyperactivity disorder: The case of visuospatial orienting. Clinical Psychology Review, 23, 801830.CrossRefGoogle ScholarPubMed
Ivanoff, J. & Taylor, T. (2006). Inhibition of return promotes stop-signal inhibition by delaying responses. Visual Cognition, 13, 503512.CrossRefGoogle Scholar
James, W. (1890). Principles of psychology. New York: Holt.Google Scholar
Jankovic, M., Brouwers, P., Valsecchi, M.G., Van Veldhuizen, A., Huisman, J., Kamphuis, R., Kingma, A., Mor, W., Van Dongen-Melman, J., Ferronato, L., Mancini, M.A., Spinetta, J.J., & Masera, G. (1994). Association of 1800 cGy cranial irradiation with intellectual function in children with acute lymphoblastic leukaemia. ISPACC. International study group on psychosocial aspects of childhood cancer. Lancet, 344, 224227.CrossRefGoogle Scholar
Jensen, P.S., Kettle, L., Roper, M.T., Sloan, M.T., Dulcan, M.K., Hoven, C., Bird, H.R., Bauermeister, J.J., & Payne, J.D. (1999). Are stimulants overprescribed? Treatment of ADHD in four U.S. communities. Journal of the American Academy of Child and Adolescent Psychiatry, 38, 797804.CrossRefGoogle ScholarPubMed
Jin, C. & Schachar, R. (2004). Methylphenidate treatment of attention-deficit/hyperactivity disorder secondary to traumatic brain injury: A critical appraisal of treatment studies. CNS Spectrums, 9, 217226.CrossRefGoogle ScholarPubMed
Johnson, K.A., Barry, E., Bellgrove, M.A., Cox, M., Kelly, S.P., Dáibhis, A., Daly, M., Keavey, M., Watchorn, A., Fitzgerald, M., McNicholas, F., Kirley, A., Robertson, I.H., & Gill, M. (2008). Dissociation in response to methylphenidate on response variability in a group of medication naïve children with ADHD. Neuropsychologia, 46, 15321541.CrossRefGoogle Scholar
Juranek, J., Fletcher, J.M, Hasan, K.M., Breier, J.I., Cirino, P.T., Alvarez, P.P., Diaz, J.D., Ewing-Cobbs, L., Dennis, M., & Papanicolaou, A. (2008). Neocortical reorganization in spina bifida. Neuroimage, 40, 15161522.CrossRefGoogle ScholarPubMed
Klein, C., Wendling, K., Huettner, P., Ruder, H., & Peper, M. (2006). Intra-subject variability in attention-deficit hyperactivity disorder. Biological Psychiatry, 60, 10881097.CrossRefGoogle ScholarPubMed
Klein, R.M. (2000). Inhibition of return. Trends in Cognitive Sciences, 4, 138147.CrossRefGoogle ScholarPubMed
Knudsen, E.I. (2007). Fundamental components of attention. Annual Review of Neuroscience, 30, 5778.CrossRefGoogle ScholarPubMed
Konrad, K., Gauggel, S., Manz, A., & Scholl, M. (2000a). Inhibitory control in children with traumatic brain injury (TBI) and children with attention deficit/hyperactivity disorder (ADHD). Brain Injury, 14, 859875.Google ScholarPubMed
Konrad, K., Gauggel, S., Manz, A., & Scholl, M. (2000b). Lack of inhibition: A motivational deficit in children with attention deficit/hyperactivity disorder and children with traumatic brain injury. Child Neuropsychology, 6, 286296.CrossRefGoogle ScholarPubMed
Kraus, J.F. & McArthur, D.L. (1996). Epidemiologic aspects of brain injury. Neurologic Clinics, 14, 435450.CrossRefGoogle ScholarPubMed
Kraus, J.F., Rock, A., & Hemyari, P. (1990). Brain injuries among infants, children, adolescents, and young adults. American Journal of Diseases of Children, 144, 684691.Google ScholarPubMed
Krull, K.R., Brouwers, P., Jain, N., Zhang, L., Bomgaars, L., Dreyer, Z., Mahoney, D., Bottomley, S., & Okcu, M.F. (2008). Folate pathway genetic polymorphisms are related to attention disorders in childhood leukemia survivors. Journal of Pediatrics, 152, 101105.CrossRefGoogle ScholarPubMed
Kuntsi, J., Oosterlaan, J., & Stevenson, J. (2001). Psychological mechanisms in hyperactivity: I. Response inhibition deficit, working memory impairment, delay aversion, or something else? Journal of Child Psychology and Psychiatry, and Allied Disciplines, 42, 199210.CrossRefGoogle ScholarPubMed
Kurotaki, N., Imaizumi, K., Harada, N., Masuno, M., Kondoh, T., Nagai, T., Ohashi, H., Naritomi, K., Tsukahara, M., Makita, Y., Sugimoto, T., Sonoda, T., Hasegawa, T., Chinen, Y., Tomita Ha, H.A., Kinoshita, A., Mizuguchi, T., Yoshiura Ki, K., Ohta, T., Kishino, T., Fukushima, Y., Niikawa, N., & Matsumoto, N. (2002). Haploinsufficiency of NSD1 causes Sotos syndrome. Nature Genetics, 30, 365366.CrossRefGoogle ScholarPubMed
Lahteenmaki, P.M., Holopainen, I., Krause, C.M., Helenius, H., Salmi, T.T., & Heikki, L.A. (2001). Cognitive functions of adolescent childhood cancer survivors assessed by event-related potentials. Medical and Pediatric Oncology, 36, 442450.CrossRefGoogle ScholarPubMed
Lansbergen, M., Kenemans, J.L., & van Engeland, H. (2007). Stroop interference and attention/deficit disorder: A review and meta-analysis. Neuropsychology, 21, 251262.CrossRefGoogle ScholarPubMed
Larson, C.L., Aronoff, J., & Stearns, J.J. (2007). The shape of threat: Simple geometric forms evoke rapid and sustained capture of attention. Emotion, 7, 526534.CrossRefGoogle ScholarPubMed
Leblanc, N., Chen, S., Swank, P.R., Ewing-Cobbs, L., Barnes, M., Dennis, M., Max, J., Levin, H., & Schachar, R. (2005). Response inhibition after traumatic brain injury (TBI) in children: Impairment and recovery. Developmental Neuropsychology, 28, 829848.CrossRefGoogle ScholarPubMed
Leth-Steensen, C., Elbaz, Z.K., & Douglas, V.I. (2000). Mean response times, variability, and skew in the responding of ADHD children: A response time distributional approach. Acta Psychologica, 104, 167190.CrossRefGoogle ScholarPubMed
Levin, H.S., Benavidez, D.A., Verger-Maestre, K., Perachio, N., Song, J., Mendelsohn, D.B., & Fletcher, J.M. (2000). Reduction of corpus callosum growth after severe traumatic brain injury in children. Neurology, 54, 647653.CrossRefGoogle ScholarPubMed
Levin, H.S., Culhane, K.A., Mendelsohn, D., Lilly, M.A., Bruce, D., Fletcher, J.M., Chapman, S.B., Harward, H., & Eisenberg, H.M. (1993). Cognition in relation to magnetic resonance imaging in head-injured children and adolescents. Archives of Neurology, 50, 897905.CrossRefGoogle ScholarPubMed
Levin, H.S., Fletcher, J.M., Kusnerik, L., Kufera, J.A., Lilly, M.A., Duffy, F.F., Chapman, S., Mendelsohn, D., & Bruce, D. (1996). Semantic memory following pediatric head injury: Relationship to age, severity of injury, and MRI. Cortex, 32, 461478.CrossRefGoogle ScholarPubMed
Levin, H.S., Hanten, G., Max, J., Li, X., Swank, P., Ewing-Cobbs, L., Dennis, M., Menefee, D.S., & Schachar, R. (2007). Symptoms of attention-deficit/hyperactivity disorder following traumatic brain injury in children. Journal of Developmental and Behavioral Pediatrics, 28, 108118.CrossRefGoogle ScholarPubMed
Levin, H.S., Hanten, G., Roberson, G., Li, X., Ewing-Cobbs, L., Dennis, M., Chapman, S., Max, J., Hunter, J., Schachar, R., Luerssen, T.G., & Swank, P. (2008). Abnormal CT after mild traumatic brain injury predicts cognitive sequelae in school aged children. Journal of Neurosurgery. Pediatrics, 1, 461470.Google Scholar
Levin, H.S., Hanten, G., Zhang, L., Swank, P.R., & Hunter, J. (2004). Selective impairment of inhibition after TBI in children. Journal of Clinical and Experimental Neuropsychology, 26, 589597.CrossRefGoogle ScholarPubMed
Li, C.S., Chang, H.L., & Lin, S.C. (2003). Inhibition of return in children with attention deficit hyperactivity disorder. Experimental Brain Research, 149, 125130.CrossRefGoogle ScholarPubMed
Li, C.S., Yan, P., Bergquist, K.L., & Sinha, R. (2007). Greater activation of the “default” brain regions predicts stop signal errors. Neuroimage, 38, 640648.CrossRefGoogle ScholarPubMed
Lockwood, K.A., Bell, T.S., & Colegrove, R.W. Jr. (1999). Long-term effects of cranial radiation therapy on attention functioning in survivors of childhood leukemia. Journal of Pediatric Psychology, 24, 5566.CrossRefGoogle Scholar
Logan, G.D. (1994). On the ability to inhibit thought and action: A users' guide to the stop signal paradigm. In Dagenbach, D. & Carr, T.H. (Eds.), Inhibitory processes in attention, memory, and language (pp. 189240). San Diego: Academic Press.Google Scholar
Mahalick, D.M., Carmel, P.W., Greenberg, J.P., Molofsky, W., Brown, J.A., Heary, R.F., Marks, D., Zampella, E., Hodosh, R., & von der Schmidt, E. 3rd (1998). Psychopharmacologic treatment of acquired attention disorders in children with brain injury. Pediatric Neurosurgery, 29, 121126.CrossRefGoogle ScholarPubMed
Mahone, E.M., Prahme, M.C., Ruble, K., Mostofsky, S.H., & Schwartz, C.L. (2007). Motor and perceptual timing deficits among survivors of childhood leukemia. Journal of Pediatric Psychology, 32, 918925.CrossRefGoogle ScholarPubMed
Makris, N., Biederman, J., Valera, E.M., Bush, G., Kaiser, K., Kennedy, D.N., Caviness, V.S., Faraone, S.V., & Seidman, L.J. (2007). Cortical thinning of the attention and executive function networks in adults with attention-deficit/hyperactivity disorder. Cerebral Cortex, 17, 13641375.CrossRefGoogle ScholarPubMed
Manly, T., Robertson, I.H., Anderson, V., & Nimmo-Smith, I. (1999). Test of everyday attention for children. Bury St. Edmonds, UK: Thames Valley.Google Scholar
Maria, B.L., Dennis, M., & Obonsawin, M. (1993). Severe permanent encephalopathy in acute lymphoblastic leukemia. The Canadian Journal of Neurological Sciences, 20, 199205.Google ScholarPubMed
Martin, J.A., Hamilton, B.E., Sutton, P.D., Ventura, S.J., Menacker, F., & Kirmeyer, S. (2006, September 29). Births: Final data for 2004. National Vital Statistics Report, 55, Number 1.Google ScholarPubMed
Max, J.E., Lansing, A.E., Koele, S.L., Castillo, C.S., Bokura, H., Schachar, R., Collings, N., & Williams, K.E. (2004). Attention deficit hyperactivity disorder in children and adolescents following traumatic brain injury. Developmental Neuropsychology, 25, 159177.CrossRefGoogle ScholarPubMed
Max, J.E., Lindgren, S.D., Knutson, C., Pearson, C.S., Ihrig, D., & Welborn, A. (1998). Child and adolescent traumatic brain injury: Correlates of disruptive behaviour disorders. Brain Injury, 12, 4152.Google ScholarPubMed
Max, J.E., Manes, F.F., Robertson, B.A., Mathews, K., Fox, P.T., & Lancaster, J. (2005a). Prefrontal and executive attention network lesions and the development of attention-deficit/hyperactivity symptomatology. Journal of the American Academy of Child and Adolescent Psychiatry, 44, 443450.CrossRefGoogle ScholarPubMed
Max, J.E., Schachar, R.J., Levin, H.S., Ewing-Cobbs, L., Chapman, S.B., Dennis, M., Saunders, A., & Landis, J. (2005b). Predictors of attention-deficit/hyperactivity disorder within 6 months after pediatric traumatic brain injury. Journal of the American Academy of Child and Adolescent Psychiatry, 44, 10321040.CrossRefGoogle ScholarPubMed
Max, J.E., Schachar, RJ., Levin, H.S., Ewing-Cobbs, L., Chapman, S.B., Dennis, M., Saunders, A., & Landis, J. (2005c). Predictors of secondary attention-deficit/hyperactivity disorder in children and adolescents 6 to 24 months after traumatic brain injury. Journal of the American Academy of Child and Adolescent Psychiatry, 44, 10411049.CrossRefGoogle ScholarPubMed
Mayes, S.D., Crites, D.L., Bixler, E.O., Humphrey, F.J. 2nd, & Mattison, R.E. (1994). Methylphenidate and ADHD: Influence of age, IQ and neurodevelopmental status. Developmental Medicine and Child Neurology, 36, 10991107.CrossRefGoogle ScholarPubMed
McLean, A., Dowson, J., Toone, B., Young, S., Bazanis, E., Robbins, T.W., & Sahakian, B.J. (2004). Characteristic neurocognitive profile associated with adult attention-deficit/hyperactivity disorder. Psychological Medicine, 34, 681692.CrossRefGoogle ScholarPubMed
McLone, D.G. & Knepper, P.A. (1989). The cause of the Chiari II malformation: A unified theory. Pediatric Neuroscience, 15, 112.CrossRefGoogle ScholarPubMed
Mennes, M., Stiers, P., Vandenbussche, E., Vercruysse, G., Uyttebroeck, A., De Meyer, G., & Van Cool, S.W. (2005). Attention and information processing in survivors of childhood acute lymphoblastic leukemia treated with chemotherapy only. Pediatric Blood and Cancer, 44, 478486.CrossRefGoogle ScholarPubMed
Mesulam, M-M. (1990). Large-scale neurocognitive networks and distributed processing for attention, language, and memory. Annals of Neurology, 28, 597613.CrossRefGoogle ScholarPubMed
Miller, E., Widjaja, E., Blaser, S., Dennis, M., & Raybaud, C. (2008). The old and the new: Supratentorial MR findings in Chiari II malformation. Child's Nervous System, 24, 563575.CrossRefGoogle ScholarPubMed
Mirsky, A.F., Anthony, B.J., Duncan, C.C., Ahearn, M.B., & Kellam, S.G. (1991). Analysis of the elements of attention: A neuropsychological approach. Neuropsychology Review, 2, 109145.CrossRefGoogle ScholarPubMed
Mizuno, T. & Sugishita, M. (2007). Neural correlates underlying perception of tonality-related emotional contents. Neuroreport, 18, 16511655.CrossRefGoogle ScholarPubMed
Moore, B.D. 3rd. (2005). Neurocognitive outcomes in survivors of childhood cancer. Journal of Pediatric Psychology, 30, 5163.CrossRefGoogle ScholarPubMed
Morgan, A.E., Hynd, G.W., Riccio, C.A., & Hall, J. (1996). Validity of DSM-IV ADHD predominantly inattentive and combined types: Relationship to previous DSM diagnoses/subtype differences. Journal of the American Academy of Child and Adolescent Psychiatry, 35, 325333.CrossRefGoogle ScholarPubMed
Mostofsky, S.H., Kunze, J.C., Cutting, L.E., Lederman, H.M., & Denckla, M.B. (2000). Judgment of duration in individuals with ataxia-telangiectasia. Developmental Neuropsychology, 17, 6374.CrossRefGoogle ScholarPubMed
Mulhern, R.K., Khan, R.B., Kaplan, S., Helton, S., Christensen, R., Bonner, M., Brown, R., Xiong, X., Wu, S., Gururangan, S., & Reddick, W.E. (2004). Short-term efficacy of methylphenidate: A randomized, double-blind, placebo-controlled trial among survivors of childhood cancer. Journal of Clinical Oncology, 22, 47954803.CrossRefGoogle ScholarPubMed
Neef, N.A., Bicard, D.F., & Endo, S. (2001). Assessment of impulsivity and the development of self-control in students with attention deficit hyperactivity disorder. Journal of Applied Behavior Analysis, 34, 397408.CrossRefGoogle ScholarPubMed
Nigg, J.T. (2003). Response inhibition and disruptive behaviors: Toward a multiprocess conception of etiological heterogeneity for ADHD combined type and conduct disorder early-onset type. Annals of the New York Academy of Sciences, 1008, 170182.CrossRefGoogle Scholar
Nigg, J.T., Butler, K.M., Huang-Pollock, C.L., & Henderson, J.M. (2002). Inhibitory processes in adults with persistent childhood onset ADHD. Journal of Consulting and Clinical Psychology, 70, 153157.CrossRefGoogle ScholarPubMed
Nigg, J.T., Willcutt, E.G., Doyle, A.E., & Sonuga-Barke, E.J. (2005). Causal heterogeneity in attention-deficit/hyperactivity disorder: Do we need neuropsychologically impaired subtypes? Biological Psychiatry, 57, 12241230.CrossRefGoogle ScholarPubMed
Nolan, P. & Mathieu, F. (2000). Deficits de l'attention et de la vitesse du traitement de l'information chez des enfants ayant subi un traumatisme craniocerebral leger. Annales de Réadaptation et de Médecine Physique, 43, 236245.CrossRefGoogle Scholar
O'Reilly, R.C. & Frank, M.J. (2006). Making working memory work: A computational model of learning in the prefrontal cortex and basal ganglia. Neural Computation, 18, 283328.CrossRefGoogle Scholar
Ornstein, T.J., Levin, H.S., Chen, C., Hanten, G., Ewing-Cobbs, L., Dennis, M., Max, J., Logan, G.D., & Schachar, R. (in press). Performance monitoring in children following traumatic brain injury. Journal of Child Psychology and Psychiatry.Google Scholar
Parker, S.L., Tong, T., Bolden, S., & Wingo, P.A. (1997). Cancer statistics, 1997. CA: A Cancer Journal for Clinicians, 47, 527.Google ScholarPubMed
Pasini, A., Paloscia, C., Alessandrelli, R., Porfirio, M.C., & Curatolo, P. (2007). Attention and executive functions profile in drug naive ADHD subtypes. Brain and Development, 29, 400408.CrossRefGoogle ScholarPubMed
Paternite, C.E., Loney, J., & Roberts, M.A. (1995). External validation of oppositional disorder and attention deficit disorder with hyperactivity. Journal of Abnormal Child Psychology, 23, 453471.CrossRefGoogle ScholarPubMed
Pennington, B.F. & Ozonoff, S. (1996). Executive functions and developmental psychopathology. Journal of Child Psychology and Psychiatry, and Allied Disciplines, 37, 5187.CrossRefGoogle ScholarPubMed
Piek, J.P., Dyck, M.J., Francis, M., & Conwell, A. (2007). Working memory, processing speed, and set-shifting in children with developmental coordination disorder and attention-deficit-hyperactivity disorder. Developmental Medicine and Child Neurology, 49, 678683.CrossRefGoogle ScholarPubMed
Posner, M.I. & Peterson, S.E. (1990). The attention system of the human brain. Annual Review of Neuroscience, 13, 2542.CrossRefGoogle ScholarPubMed
Posner, M.I., Walker, J.A., Friedrich, F.J., & Rafal, R.D. (1984). Effects of parietal injury on covert orienting of attention. The Journal of Neuroscience, 4, 18631874.CrossRefGoogle ScholarPubMed
Pritchard, V.E., Neumann, E., & Rucklidge, J.J. (2007). Interference and negative priming effects in adolescents with attention deficit hyperactivity disorder. The American Journal of Psychology, 120, 91122.CrossRefGoogle ScholarPubMed
Radonovich, K.J. & Mostofsky, S.H. (2004). Duration judgments in children with ADHD suggest deficient utilization of temporal information rather than general impairment in timing. Child Neuropsychology, 10, 162172.CrossRefGoogle ScholarPubMed
Rafal, R.D., Calabresi, P.A., Brennan, C.W., & Sciolto, T.K. (1989). Saccade preparation inhibits reorienting to recently attended locations. Journal of Experimental Psychology, 15, 673685.Google ScholarPubMed
Rafal, R.D. & Grimm, R.J. (1981). Progressive supranuclear palsy: Functional analysis of the response to methysergide and antiparkinsonian agents. Neurology, 31, 15071518.CrossRefGoogle ScholarPubMed
Rafal, R.D., Henik, A., & Smith, J. (1991). Extrageniculate contribution to reflex visual orienting in normal humans: A temporal hemifield advantage. Journal of Cognitive Neuroscience, 3, 351358.CrossRefGoogle ScholarPubMed
Rafal, R.D., Posner, M.I., Friedman, J.H., Inhoff, A.W., & Bernstein, E. (1988). Orienting of visual attention in progressive supranuclear palsy. Brain, 111, 267280.CrossRefGoogle ScholarPubMed
Rhodes, S.M., Coghill, D.R., & Matthews, K. (2005). Neuropsychological functioning in stimulant-naive boys with hyperkinetic disorder. Psychological Medicine, 35, 11091120.CrossRefGoogle ScholarPubMed
Riccio, C.A., Homack, S., Jarratt, K.P., & Wolfe, M.E. (2006). Differences in academic and executive function domains among children with ADHD predominantly inattentive and combined types. Archives of Clinical Neuropsychology, 21, 657667.CrossRefGoogle ScholarPubMed
Ries, M. & Marks, W. (2005). Selective attention deficits following severe closed head injury: The role of inhibitory processes. Neuropsychology, 19, 476483.CrossRefGoogle ScholarPubMed
Rodgers, J., Marckus, R., Kearns, P., & Windebank, K. (2003). Attentional ability among survivors of leukaemia treated without cranial irradiation. Archives of Disease in Childhood, 88, 147150.CrossRefGoogle ScholarPubMed
Rose, B.M. & Holmbeck, G.N. (2007). Attention and executive functions in adolescents with spina bifida. Journal of Pediatric Psychology, 32, 983994.CrossRefGoogle ScholarPubMed
Rubia, K., Overmeyer, S., Taylor, E., Brammer, M., Williams, S.C., Simmons, A., & Bullmore, E.T. (1999). Hypofrontality in attention deficit hyperactivity disorder during higher-order motor control: A study with functional MRI. The American Journal of Psychiatry, 156, 891896.CrossRefGoogle ScholarPubMed
Rubia, K., Russell, T., Overmeyer, S., Brammer, M.J., Bullmore, E.T., Sharma, T., Simmons, A., Williams, S.C., Giampietro, V., Andrew, C.M., & Taylor, E. (2001). Mapping motor inhibition: Conjunctive brain activations across different versions of go/no-go and stop tasks. Neuroimage, 13, 250261.CrossRefGoogle ScholarPubMed
Rubia, K., Smith, A.B., Woolley, J., Nosarti, C., Heyman, I., Taylor, E., & Brammer, M. (2006). Progressive increase of frontostriatal brain activation from childhood to adulthood during event-related tasks of cognitive control. Human Brain Mapping, 27, 973993.CrossRefGoogle ScholarPubMed
Russell, V.A., Oades, R.D., Tannock, R., Killeen, P.R., Auerbach, J.G., Johansen, E.B., & Sagvolden, T. (2006). Response variability in attention-deficit/hyperactivity disorder: A neuronal and glial energetics hypothesis. Behavioral and Brain Functions, 2, 3054.CrossRefGoogle ScholarPubMed
Sagvolden, T., Aase, H., Zeiner, P., & Berger, D. (1998). Altered reinforcement mechanisms in attention-deficit/hyperactivity disorder. Behavioural Brain Research, 94, 6171.CrossRefGoogle ScholarPubMed
Salman, M.S., Blaser, S.E., Sharpe, J.A., & Dennis, M. (2006a). Cerebellar vermis morphology in children with spina bifida and Chiari Type II malformation. Child's Nervous System, 22, 385393.CrossRefGoogle ScholarPubMed
Salman, M.S., Sharpe, J.A., Eizenman, M., Lillakas, L., To, T., Westall, C., Steinbach, M., & Dennis, M. (2006b). Saccadic adaptation in Chiari Type II malformation. Canadian Journal of Neurological Sciences, 33, 372378.CrossRefGoogle ScholarPubMed
Sapir, A., Soroker, N., Berger, A., & Henik, A. (1999). Inhibition of return in spatial attention: Direct evidence for collicular generation. Nature Neuroscience, 2, 10531054.CrossRefGoogle ScholarPubMed
Schachar, R., Levin, H.S., Max, J.E., Purvis, K., & Chen, S. (2004a). Attention deficit hyperactivity disorder symptoms and response inhibition after closed head injury in children: Do preinjury behavior and injury severity predict outcome? Developmental Neuropsychology, 25, 179198.CrossRefGoogle ScholarPubMed
Schachar, R., Logan, G.D., Robaey, P., Chen, S., Ickowicz, A., & Barr, C. (2007). Restraint and cancellation: Multiple inhibition deficits in attention deficit hyperactivity disorder. Journal of Abnormal Child Psychology, 35, 229238.CrossRefGoogle ScholarPubMed
Schachar, R., Tannock, R., Marriott, M., & Logan, G. (1995). Deficient inhibitory control in attention deficit hyperactivity disorder. Journal of Abnormal Child Psychology, 23, 411437.CrossRefGoogle ScholarPubMed
Schachar, R.J., Chen, S., Logan, G.D., Ornstein, T.J., Crosbie, J., Ickowicz, A., & Pakulak, A. (2004b). Evidence for an error monitoring deficit in attention deficit hyperactivity disorder. Journal of Abnormal Child Psychology, 32, 285293.CrossRefGoogle ScholarPubMed
Schatz, J., Kramer, J.H., Ablin, A.R., & Matthay, K.K. (2004). Visual attention in long-term survivors of leukemia receiving cranial radiation therapy. Journal of the International Neuropsychological Society, 10, 211220.CrossRefGoogle ScholarPubMed
Schmitter-Edgecombe, M. & Langill, M. (2006). Costs of a predictable switch between simple cognitive tasks following severe closed-head injury. Neuropsychology, 20, 675684.CrossRefGoogle ScholarPubMed
Schweitzer, J.B. & Sulzer-Azaroff, B. (1995). Self-control in boys with attention deficit hyperactivity disorder: Effects of added stimulation and time. Journal of Child Psychology and Psychiatry, and Allied Disciplines, 36, 671686.Google ScholarPubMed
Seidel, W.T. & Joschko, M. (1990). Evidence of difficulties in sustained attention in children with ADHD. Journal of Abnormal Child Psychology, 18, 217229.CrossRefGoogle Scholar
Seidman, L.J., Valera, E.M., & Makris, N. (2005). Structural brain imaging of attention-deficit/hyperactivity disorder. Biological Psychiatry, 57, 12631272.CrossRefGoogle ScholarPubMed
Seidman, L., Valera, E., Makris, N., Monuteaux, D., Boriel, D., Kelkar, K., Kennedy, S.N., Caviness, V.S., Bush, G., Aleardi, M., Faraone, S.V., & Biederman, J. (2006). Dorsolateral prefrontal and anterior cingulate cortex volumetric abnormalities in adults with attention-deficit/hyperactivity disorder identified by magnetic resonance imaging. Biological Psychiatry, 60, 10711080.CrossRefGoogle ScholarPubMed
Simpson, A. & Schmitter-Edgecombe, M. (2000). Intactness of inhibitory attentional mechanisms following severe closed-head injury. Neuropsychology, 14, 310319.CrossRefGoogle ScholarPubMed
Slomine, B.S., Salorio, C.F., Grados, M.A., Vasa, R.A., Christensen, J.R., & Gerring, J.P. (2005). Differences in attention, executive functioning, and memory in children with and without ADHD after severe traumatic brain injury. Journal of the International Neuropsychological Society, 11, 645653.CrossRefGoogle ScholarPubMed
Soeda, A., Nakashima, T., Okumura, A., Kuwata, K., Shinoda, J., & Iwama, T. (2005). Cognitive impairment after traumatic brain injury: A functional magnetic resonance imaging study using the Stroop task. Neuroradiology, 47, 501506.CrossRefGoogle ScholarPubMed
Solanto, M.V., Abikoff, H., Sonuga-Barke, E., Schachar, R., Logan, G.D., Wigal, T., Hechtman, L., Hinshaw, S., & Turkel, E. (2001). The ecological validity of delay aversion and response inhibition as measures of impulsivity in AD/HD: A supplement to the NIMH multimodal treatment study of AD/HD. Journal of Abnormal Child Psychology, 29, 215228.CrossRefGoogle Scholar
Sonuga-Barke, E.J. (1994). On dysfunction and function in psychological theories of childhood disorder. Journal of Child Psychology and Psychiatry, and Allied Disciplines, 35, 801815.CrossRefGoogle ScholarPubMed
Sonuga-Barke, E.J., Houlberg, K., & Hall, M. (1994). When is “impulsiveness” not impulsive? The case of hyperactive children's cognitive style. Journal of Child Psychology and Psychiatry, and Allied Disciplines, 35, 12471253.CrossRefGoogle Scholar
Sonuga-Barke, E.J., Williams, E., Hall, M., & Saxton, T. (1996). Hyperactivity and delay aversion. III: The effect on cognitive style of imposing delay after errors. Journal of Child Psychology and Psychiatry, and Allied Disciplines, 37, 189194.CrossRefGoogle ScholarPubMed
Sowell, E.R., Thompson, P.M., Welcome, S.E., Henkenius, A.L., Toga, A.W., & Peterson, B.S. (2003). Cortical abnormalities in children and adolescents with attention-deficit hyperactivity disorder. Lancet, 362, 16991707.CrossRefGoogle ScholarPubMed
Spanos, G.K., Wilde, E.A., Bigler, E.D., Cleavinger, H.B., Fearing, M.A., Levin, H.S., Li, X., & Hunter, J.V. (2007). Cerebellar atrophy after moderate-to-severe pediatric traumatic brain injury. American Journal of Neuroradiology, 28, 537542.Google ScholarPubMed
Spencer, T.J., Biederman, J., & Mick, E. (2007). Attention-deficit/hyperactivity disorder: Diagnosis, lifespan, comorbidities, and neurobiology. Journal of Pediatric Psychology, 32, 631642.CrossRefGoogle ScholarPubMed
Spiegler, B.J., Kennedy, K., Maze, R., Greenberg, M.L., Weitzman, S., Hitzler, J.K., Nathan, P.C. (2006). Comparison of long-term neurocognitive outcomes in young children with acute lymphoblastic leukemia treated with cranial radiation or high-dose or very high-dose intravenous methotrexate. Journal of Clinical Oncology, 24, 38583864.CrossRefGoogle ScholarPubMed
Stroop, J.R. (1935). Studies of interference in serial verbal reactions. Journal of Experimental Psychology, 18, 643662.CrossRefGoogle Scholar
Swartwout, M.D., Cirino, P.T., Hampson, A.W., Fletcher, J.M., Brandt, M.E., & Dennis, M. (in press). Sustained attention in children with two etiologies of early hydrocephalus. Neuropsychology.Google Scholar
Szatmari, P. (1992). The epidemiology of attention-deficit hyperactivity disorders. In Weiss, G. (Ed.), Attention-deficit hyperactivity disorder, Vol 1 (pp. 361371). Philadelphia: Saunders.Google Scholar
Tamm, L., Menon, V., Ringel, J., & Reiss, A.L. (2004). Event-related FMRI evidence of frontotemporal involvement in aberrant response inhibition and task switching in attention-deficit/hyperactivity disorder. Journal of the American Academy of Child and Adolescent Psychiatry, 43, 14301440.CrossRefGoogle ScholarPubMed
Teicher, M.H., Lowen, S.B., Polcari, A., Foley, M., & McGreenery, C.E. (2004). Novel strategy for the analysis of CPT data provides new insight into the effects of methylphenidate on attentional states in children with ADHD. Journal of Child and Adolescent Psychopharmacology, 14, 219232.CrossRefGoogle ScholarPubMed
Tipper, S.P. (1992). Selection for action: The role of inhibitory mechanisms. Current Directions in Psychological Science, 1, 14.CrossRefGoogle Scholar
Treue, S. (2003). Visual attention: The where, what, how and why of saliency. Current Opinion in Neurobiology, 13, 428432.CrossRefGoogle ScholarPubMed
Tripp, G. & Alsop, B. (2001). Sensitivity to reward delay in children with attention deficit hyperactivity disorder (ADHD). Journal of Child Psychology and Psychiatry, and Allied Disciplines, 42, 691698.CrossRefGoogle ScholarPubMed
Tucha, O., Walitza, S., Mecklinger, L., Sontag, T.A., Kubber, S., Linder, M., & Lange, K.W. (2006). Attentional functioning in children with ADHD-predominantly hyperactive-impulsive type and children with ADHD-combined type. Journal of Neural Transmission, 113, 19431953.CrossRefGoogle ScholarPubMed
Vachha, B. & Adams, R. (2005). Myelomeningocele, temperament patterns, and parental perceptions. Pediatrics, 115, 5863.CrossRefGoogle ScholarPubMed
Vaidya, C.J., Austin, G., Kirkorian, G., Ridlehuber, H.W., Desmond, J.E., Glover, G.H., & Gabrieli, J.D. (1998). Selective effects of methylphenidate in attention deficit hyperactivity disorder: A functional magnetic resonance study. Proceedings of the National Academy of Sciences of the United States of America, 95, 1449414499.CrossRefGoogle ScholarPubMed
Vaidya, C.J., Bunge, S.A., Dudukovic, N.M., Zalecki, C.A., Elliott, G.R., & Gabrieli, J.D. (2005). Altered neural substrates of cognitive control in childhood ADHD: Evidence from functional magnetic resonance imaging. American Journal of Psychiatry, 162, 16051613.CrossRefGoogle ScholarPubMed
Visser, S.N., Lesesne, C.A., & Perou, R. (2007). National estimates and factors associated with medication treatment for childhood attention-deficit/hyperactivity disorder. Pediatrics, 119, S99106.CrossRefGoogle ScholarPubMed
Volcik, K.A., Blanton, S.H., Tyerman, G.H., Jong, T.S., Rott, E.J., Page, T.Z., Romaine, N.K., & Northrup, H. (2000). Methylenetetrahydrofolate reductase and spina bifida: Evaluation of level of defect and maternal genotypic risk in Hispanics. American Journal of Medical Genetics, 95, 2127.3.0.CO;2-M>CrossRefGoogle ScholarPubMed
Ward, H., Shum, D., McKinlay, L., Baker, S., & Wallace, G. (2006). Prospective memory and pediatric traumatic brain injury: Effects of cognitive demand. Child Neuropsychology, 13, 219239.CrossRefGoogle Scholar
Westerberg, H., Hirvikoski, T., Forssberg, H., & Klingberg, T. (2004). Visuo-spatial working memory span: A sensitive measure of cognitive deficits in children with ADHD. Child Neuropsychology, 10, 155161.CrossRefGoogle Scholar
Wilde, E.A., Hunter, J.V., Newsome, M.R., Scheibel, R.S., Bigler, E.D., Johnson, J.L., Fearing, M.A., Cleavinger, H.B., Li, X., Swank, P.R., Pedroza, C., Roberson, G.S., Bachevalier, J., & Levin, H.S. (2005). Frontal and temporal morphometric findings on MRI in children after moderate to severe traumatic brain injury. Journal of Neurotrauma, 22, 333344.CrossRefGoogle ScholarPubMed
Willcutt, E.G., Doyle, A.E., Nigg, J.T., Faraone, S.V., & Pennington, B.F. (2005). Validity of the executive function theory of attention-deficit/hyperactivity disorder: A meta-analytic review. Biological Psychiatry, 57, 13361346.CrossRefGoogle ScholarPubMed
Wolraich, M.L., Hannah, J.N., Pinnock, T.Y., Baumgaertel, A., & Brown, J. (1996). Comparison of diagnostic criteria for attention-deficit hyperactivity disorder in a county-wide sample. Journal of the American Academy of Child and Adolescent Psychiatry, 35, 319324.CrossRefGoogle Scholar
Woodward, T.S., Metzak, P.D., Meier, B., & Holroyd, C.B. (2008). Anterior cingulate cortex signals the requirement to break inertia when switching tasks: A study of the bivalency effect. Neuroimage, 40, 13111318.CrossRefGoogle ScholarPubMed
Yeates, K.O. (2000). Closed-head injury. In Yeates, K.O., Taylor, H.G., & Ris, M.D. (Eds.), Pediatric neuropsychology: Research, theory, and practice (pp. 92116). New York: Guilford Press.Google Scholar
Yeates, K.O., Armstrong, K., Janusz, J., Taylor, H.G., Wade, S., Stancin, T., & Drotar, D. (2005). Long-term attention problems in children with traumatic brain injury. Journal of the American Academy of Child and Adolescent Psychiatry, 44, 574584.CrossRefGoogle ScholarPubMed
Zametkin, A.J. & Rapoport, J.L. (1987). Neurobiology of attention deficit disorder with hyperactivity: Where have we come in 50 years? Journal of the American Academy of Child and Adolescent Psychiatry, 26, 676686.CrossRefGoogle ScholarPubMed
Zhu, W., Zhao, L., Zhang, J., Ding, X., Liu, H., Ni, E., Ma, Y., & Zhou, C. (2008). The influence of Mozart's sonata K.448 on visual attention: An ERPs study. Neuroscience Letters, 434, 3540.CrossRefGoogle ScholarPubMed
Figure 0

Fig. 1. Attention taxonomy.

Figure 1

Fig. 2. Covert stimulus orienting paradigms. In exogenous orienting (left), the participant maintains central fixation and then an exogenous cue, such as a luminance change, appears to one side of fixation, followed by a target, to which the participant must respond. In this example, the brightness cue will facilitate target detection because it draws attention to the side on which the target will appear (a misleading cue would have appeared on the side opposite to the upcoming target). In endogenous orienting (right), the participant maintains central fixation, which is then replaced by a central endogenous cue, such as an arrow, followed by a target, to which the participant must respond. In this example, the arrow cue will facilitate target detection because it draws attention to the side on which the target will appear (a misleading arrow would have directed attention to the side opposite to the upcoming target).

Figure 2

Fig. 3. Stop signal paradigm. The participant fixates a central dot and then a go stimulus appears, either an X indicating a left hand response (shown in figure) or an O indicating a right hand response. One-third of the trials involve a stop signal (a background color change) following the go signal to indicate that the participant should not respond. Because of the adaptively manipulated delay interval between go and stop signals, each participant will fail to stop on half of the stop trials. Failed stop trials activate the error detection system, so that go trials that follow a failed stop trial (circled in figure) will be slower than go trials that do not follow failures to stop.

Figure 3

Table 1. Robots, puppets, critics, and actors: The fractionation of attention in developmental disorders