Brain and Cognition 83 (2013) 10–20

Contents lists available at SciVerse ScienceDirect

Brain and Cognition

journal homepage: www.elsevier .com/locate /b&c

Emotional distraction in boys with ADHD: Neural and behavioralcorrelates

0278-2626/$ - see front matter � 2013 Elsevier Inc. All rights reserved.http://dx.doi.org/10.1016/j.bandc.2013.06.004

⇑ Corresponding author. Fax: +34 91 497 52 15.E-mail address: sara.lopez@uam.es (S. López-Martín).

Sara López-Martín a,⇑, Jacobo Albert b, Alberto Fernández-Jaén c, Luis Carretié a

a Departamento de Psicología Biológica y de la Salud, Facultad de Psicología, Universidad Autónoma de Madrid, 28049 Madrid, Spainb Unidad de Cartografía Cerebral, Instituto Pluridisciplinar, Universidad Complutense de Madrid, 28040 Madrid, Spainc Unidad de Neurología Infantil, Hospital Quirón, 28223 Madrid, Spain

a r t i c l e i n f o

Article history:Accepted 17 June 2013Available online 16 July 2013

Keywords:ADHDDistractionEmotionERPs

a b s t r a c t

Although, in everyday life, patients with attention deficit hyperactivity disorder (ADHD) are frequentlydistracted by goal-irrelevant affective stimuli, little is known about the neural and behavioral substratesunderlying this emotional distractibility. Because some of the most important brain responses associatedwith the sudden onset of an emotional distracter are characterized by their early latency onset and shortduration, we addressed this issue by using a temporally agile neural signal capable of detecting and dis-tinguishing them. Specifically, scalp event-related potentials (ERPs) were recorded while 20 boys withADHD combined type and 20 healthy comparison subjects performed a digit categorization task duringthe presentation of three types of irrelevant, distracting stimuli: arousing negative (A�), neutral (N)and arousing positive (A+). Behavioral data showed that emotional distracters (both A� and A+) wereassociated with longer reaction times than neutral ones in the ADHD group, whereas no differences werefound in the control group. ERP data revealed that, compared with control subjects, boys with ADHDshowed larger anterior N2 amplitudes for emotional than for neutral distracters. Furthermore, regressionanalyses between ERP data and subjects’ emotional ratings of distracting stimuli showed that only in theADHD group, emotional arousal (ranging from calming to arousing) was associated with anterior N2: itsamplitude increased as the arousal content of the visual distracter increased. These results suggest thatboys with ADHD are more vulnerable to the distracting effects of irrelevant emotional stimuli than con-trol subjects. The present study provides first data on the neural substrates underlying emotional dis-tractibility in ADHD.

� 2013 Elsevier Inc. All rights reserved.

1. Introduction

The ability to remain goal oriented in the face of irrelevant dis-tracting stimuli is crucial for successful adaptive functioning. Thisability is thought to depend on two closely interrelated and mutu-ally dependent attentional mechanisms (Corbetta, Patel, & Shul-man, 2008; Corbetta & Shulman, 2002). On the one hand,voluntary top-down processes are triggered and developed byknowledge, expectation and current goals (e.g., read a book foran exam). On the other hand, involuntary bottom-up processesare driven by stimulus features such as novelty or significance(e.g. a wasp that appears suddenly while reading the book). Inter-estingly, emotional stimuli, salient and signal events by definition,have been shown to be prominent distracters that can efficientlycapture attention in a bottom-up fashion, thereby disrupting thefocus on goal-relevant information (Carretié, Hinojosa, Martin-Loe-ches, Mercado, & Tapia, 2004; Carretié, Hinojosa, Mercado, & Tapia,

2005; Vuilleumier & Schwartz, 2001; Öhman, Flykt, & Esteves,2001).

An increased susceptibility to distraction is currently one of thebehavioral diagnostic criteria of attention-deficit/hyperactivity dis-order (ADHD; American Psychiatric Association, 2000). Indeed, thepresence of heightened levels of distraction in ADHD is believed tobe associated with broad impairment across multiple domains,including cognitive functioning (e.g., disrupting the ability tomaintain information in working memory: Higginbotham & Bar-tling, 1993; Marx et al., 2011), interpersonal relationships (e.g.,making difficult to follow the sequence of rules in social activities:Maedgen & Carlson, 2000), academic or work performance (e.g.making careless mistakes in school or job activities: Shifrin, Proc-tor, & Prevatt, 2010), and health (e.g., increasing distraction-relatedaccidents and associated injuries: Barkley & Cox, 2007). However,experimental evidence of enhanced distractibility in ADHD isequivocal. Whereas some behavioral and electrophysiological datasuggest that individuals with ADHD are more distractible thanhealthy comparison subjects (Gumenyuk et al., 2005; Mason,Humphreys, & Kent, 2005; Radosh & Gittelman, 1981; Rosenthal

S. López-Martín et al. / Brain and Cognition 83 (2013) 10–20 11

& Allen, 1980), others have reported that patients with this disor-der are not affected by irrelevant distracting stimuli to a greaterextent than controls (Booth et al., 2005; Huang-Pollock, Nigg, &Carr, 2005; Jonkman et al., 2000; Meere & Sergeant, 1988). A recentstudy has even shown that, in certain circumstances, the presenceof auditory distracters could improve the performance of childrenwith ADHD (van Mourik, Oosterlaan, Heslenfeld, Konig, & Sergeant,2007). In any case, it should be mentioned that research on this to-pic is scarce, particularly in comparison with the large body of dataon the neural mechanisms underlying the reduced top-downinhibitory control in ADHD (Albrecht et al., 2008; Dimoska, John-stone, Barry, & Clarke, 2003; Liotti, Pliszka, Perez, Kothmann, &Woldorff, 2005; Pliszka, Liotti, & Woldorff, 2000; Rubia et al.,1999), which has been traditionally proposed as the core deficitof this disorder (Barkley, 1997). However, growing evidence indi-cates that this deficit in inhibitory control is not present amongall patients with ADHD and, in some cases, is preceded and causedby other processing deficits (Banaschewski et al., 2004; Brandeiset al., 1998; McLoughlin et al., 2010; Willcutt, Doyle, Nigg, Faraone,& Pennigton, 2005). This evidence has led to question whetherinhibition is the central deficit in ADHD and to look for the involve-ment of other psychopathological processes, including bottom-upand affective mechanisms (Castellanos, Sonuga-Barke, Milham, &Tannock, 2006; Nigg & Casey, 2005; Sergeant, 2005; Sonuga-Barke,2002).

It should be also noted that previous studies on attentional def-icits in ADHD have relied heavily on emotionally neutral visualdistracters, such as letters, numbers and geometric shapes (Boothet al., 2005; Huang-Pollock et al., 2005; Jonkman et al., 2000; Ma-son et al., 2005). In real social situations, however, maintaininggoal-directed attention in the face of salient affective distractersis often needed. Convergent evidence from hemodynamic and elec-trophysiological studies suggests enhanced neural responses toemotional stimuli relative to neutral ones, even when these stimuliare not consciously perceived (Carretié et al., 2005; Vuilleumier &Schwartz, 2001; Whalen et al., 1998). For example, a number ofinvestigations have reported amplified responses to emotional vi-sual events, involving structures such as the amygdala and theextrastriate visual cortex as well as early and late electrophysiolog-ical responses such as N2 and P3 (see reviews by Olofsson, Nordin,Sequeira, & Polich, 2008; Vuilleumier, 2005). Therefore, employingemotional stimuli may help to evoke clearer distraction effects inconditions simulating real social environments. Furthermore, theidea of incorporating emotional stimuli in the characterization ofADHD fits well with current models that emphasize that multiplepsychopathological processes and neural pathways are implicatedin this disorder, including cognitive (e.g., attention, inhibition andworking memory) and affective (emotion and motivation) pro-cesses as well as top-down (voluntary) and bottom-up (involun-tary) mechanisms (Castellanos et al., 2006; Nigg & Casey, 2005;Sergeant, 2005; Sonuga-Barke, 2002; see also Sonuga-Barke, DeHouwer, De Ruiter, Ajzenstzen, & Holland, 2004). From this per-spective, the poor ability of ADHD patients to remain focused ona task in the presence of irrelevant emotional distracters couldarise not only from a hypofunction of the brain processes associ-ated with cognitive control of distraction, but also from a hyper-function of brain processes related to the bottom-up response toaffectively laden stimuli. In support of this, a recent fMRI studyhas shown that adolescents with ADHD displayed amygdalarhyperactivity during subliminal presentation of fearful faces (Pos-ner et al., 2011b). However, to the best of our knowledge, no studyhas yet addressed the effect of emotional irrelevant stimuli onongoing cognitive processes in children with ADHD.

Due to their high temporal resolution that allows neural pro-cesses to be tracked in milliseconds, event-related potentials(ERPs) are particularly useful for elucidating the neural basis

underlying emotional distraction in ADHD. The main reason forthis is that some of the most important brain responses associatedwith the sudden onset of an emotional distracter are characterizedby their rapidity (early latency onset) and brevity (short duration),and thereby can only be detected by using a temporally agile phys-iological signal such as electroencephalography (EEG). One ERPcomponent that seems particularly well suited for studying emo-tional distractibility in the visual modality is the anterior N2, abrain electrical response occurring between 200 and 400 ms afterstimulus onset that presents its maximum amplitude over frontalscalp regions. Numerous studies have shown this component tobe enhanced for unfamiliar, novel visual stimuli as well as forhighly emotional events (Carretié et al., 2004; Chong et al., 2008;Daffner et al., 2000; Kenemans, Verbaten, Melis, & Slangen, 1992;Liddell, Williams, Rathjen, Shevrin, & Gordon, 2004; Rozenkrants& Polich, 2008). Remarkably, it has recently been reported that, un-like subsequent positive components, the amplitude of the anteriorN2 to this type of stimuli is neither modulated by the degree oftask-relevance of the eliciting stimulus nor by the direction of sub-jects’ controlled attention (Chong et al., 2008; Tarbi, Sun, Holcomb,& Daffner, 2011; see also Carretié et al., 2004 and Liddell et al.,2004). Therefore, this component responds to novel and emotionalevents even when they are not relevant for the task and occur out-side the focus of attention. In light of this evidence, this anteriorN2, which is thought to be functionally distinct from the frontocen-trally distributed control-related N2 mainly elicited by executivecontrol paradigms (see Folstein & Van Petten, 2008 for a reviewon this issue), seems to reflect automatic detection of highly signif-icant stimuli (Chong et al., 2008; Daffner et al., 2000; Liddell et al.,2004; Tarbi et al., 2011). To our knowledge, no study has examinedit in ADHD.

Following the anterior N2, a large positive deflection over cen-tro-parietal regions is often observed. This posteriorly distributedpositivity has been variously called P3, P3b, LPP or LPC, and hasgenerally been associated with more controlled stages of process-ing (Chong et al., 2008; Kenemans et al., 1992; Liddell et al., 2004).For instance, P3b is thought to reflect the processing of task-rele-vant events, including stimulus categorization/evaluation andmemory updating (Donchin, 1981; Kok, 2001; Polich, 2007; Verler-ger, 1998). ERP studies of patients with ADHD have frequentlyshown a reduction in the amplitude of P3b to task-relevant stimuli(Barry, Johnstone, & Clarke, 2003; Brandeis et al., 2002; Jonkmanet al., 2000). Within the context of emotion research, this compo-nent (often termed LPP) has been shown to be sensitive to manip-ulations requiring voluntary control processes. Indeed, it has beenbeen proposed as a neural marker of top-down emotion regulationin both adults and children (Dennis & Hajcak, 2009; Moser, Hajcak,Bukay, & Simons, 2006). Interestingly, a reduced amplitude of LPPhas recently been found in patients with ADHD when they asked toinhibit their responses to negative emotions (Köchel, Leutgeb, &Schienle, 2012). Hereafter, we will use the term late positive com-plex (LPC) to describe this family of posteriorly distributed positiv-ities associated to a greater extent than previous components withcontrolled and conscious processes.

The present study aimed at elucidating the neural and behav-ioral mechanisms underlying emotional distraction in childrenwith ADHD. To this end, ERP and behavioral data were recordedfrom boys with ADHD combined type and healthy comparison con-trols while they performed a digit categorization task while threetypes of irrelevant, distracting stimuli were presented: arousingnegative (A�), neutral (N) and arousing positive (A+). Specifically,behavioral measures consisted of reaction times (RTs) and errorrates in the cognitive task. Distraction caused by the irrelevantemotional stimuli would be mirrored in an impoverishment of cur-rent task performance (i.e., longer RTs and/or higher error rates foremotional versus neutral distracters). Neural measures consisted

Table 1Demographic data and clinical characteristics.

ADHD group mean (SD) Control group mean (SD) t Testa (df = 38) p

No 20 20 na naMale (%) 100 100 na naAge (years) 11.35 (1.42) 10.65 (1.27) ±1.642 nsIQ estimate (WISC-IV) 113.1 (12.04) 116.95 (11.81) �1.021 nsADHD RS-IVTotal 41.65 (4.04) 7.3 (4.86) ±24.31 p < 0.001Inattention 21.25 (2.59) 3.8 (2.97) ±19.81 p < 0.001Hyperactivity/impulsivity 20.4 (3.05) 3.5 (2.63) ±18.78 p < 0.001

Abbreviations: No, number of subjects; ADHD, attention-deficit/hyperactivity disorder; IQ, intelligence quotient; ADHD RS-IV, ADHD Rating Scale-IV (DuPaul et al., 1998); df,degree of freedom, ns, non significant; na, not applicable.

a Group differences were tested by means of two-sample t tests (alpha = 0.05).

12 S. López-Martín et al. / Brain and Cognition 83 (2013) 10–20

of scalp ERP analyses of N2 and LPC. In this case, emotional distrac-tion would be reflected in alterations of one or both of these com-ponents. An enhancement in the anterior N2 would suggest thatdistraction is primarily related to an exaggerated bottom-up re-sponse to the saliency of distracters, whereas a reduction in theLPC would indicate that distraction is associated with deficits ina later, more controlled stage of processing. On the basis of evi-dence showing heightened distractibility in children and adoles-cents with ADHD when they are in real social situations (Barkley& Cox, 2007; Lawrence et al., 2002; Lorch et al., 2000), we hypoth-esized that boys with ADHD may show enhanced susceptibility toemotional distraction as compared to matched control subjects,both at the behavioral and electrophysiological levels.

2. Methods

2.1. Participants

Patients were 20 boys between 8 and 13 years recruited fromthe Child Neurology Unit of the Hospital Quirón, Madrid. They allhad a formal diagnosis of ADHD combined type by a multidisci-plinary team according to DSM-IV-TR criteria (American Psychiat-ric Association, 2000). The clinical diagnoses were then confirmedby administrating the Kiddie Schedule for Affective Disorders andSchizophrenia for School-Aged Children–Present and Lifetime Ver-sions (K-SADS-PL; Kaufman et al., 1997; Ulloa et al., 2006). Threepatients had an additional diagnosis of oppositional defiant disor-der (ODD).1 ODD is a common comorbid psychiatric condition inADHD (Jensen et al., 2001). No other psychiatric or neurological dis-orders were present in any of the children. Moreover, parents com-pleted the ADHD Rating Scale-IV (ADHD-RS-IV; DuPaul, Power,Anastopoulos, & Reid, 1998) in order to obtain additional informa-tion on the current severity of their son’s ADHD symptoms. All chil-dren scored above the 93th percentile on the total scale as well as onthe inattention and hyperactivity-impulsivity subscales of theADHD-RS-IV. The patients were either medication naïve (N = 4) ormedication free for at least 36 h prior to recording. All medicated pa-tients (N = 16) were receiving extended-release methylphenidate.

Control subjects were 20 healthy boys between 8 and 13 years,recruited from different local community schools. None of themhad a history of neurological or psychiatric disorders or was takingmedication. They scored below threshold on the ADHD-RS-IV in to-tal score and the subscales of inattention and impulsivity/hyperac-tivity (DuPaul et al., 1998). Specifically, eighteen control subjectsscored at or below the 50th percentile on all ADHD RS-IV subscales,whereas the remaining two subjects scored below the 80th percen-tile. Absence of ADHD or other comorbid psychiatric disorders was

1 All results described in this article remained the same when boys with ADHD plusODD were excluded from the analyses.

confirmed with a semi-structured clinical interview (Ulloa et al.,2006).

The ADHD and control groups were matched on average ageand estimated IQ (see Table 1 for means, standard deviations andstatistical test results). By contrast, both groups differed in theADHD RS-IV scores, with ADHD patients showing significantlygreater inattention and hyperactivity-impulsivity scores than con-trol subjects (Table 1). All children had an estimated IQ above 85 asmeasured by two WISC-IV subtests: Vocabulary and Block Design.These subtests both have shown to have an excellent reliability andcorrelate highly with the full-scale intelligence quotient (Sattler,2001). Concretely, the estimated reliability of the WISC-IV subtestsfor our sample of children was 0.88, as determined by using theGuilford-Frutcher formula (p. 420, Guilford & Fruchter, 1973). Allparticipants were right-handed, as determined by asking the childto demonstrate with which hand they perform each of the follow-ing activities: write, throw a ball, brush teeth, and eat soup with aspoon. Written informed consent was obtained from parents, withthe child giving assent. Parents and children were informed thatthey could withdraw from the study at any time without conse-quences. Children received incentives for participation (a gift vou-cher of €15 and a small bag of sweets). The study had beenapproved by the Research Ethics Committee of the UniversidadAutónoma de Madrid, where the experiment took place.

2.2. Stimuli and procedure

Stimuli consisted of 8 centrally presented digits (‘‘1’’ to ‘‘9’’, ex-cept ‘‘5’’) and 45 background pictures used as distracters (15 A�,15 N, and 15 A+; each of them was presented four times, as ex-plained below). Angle of vision for digits was 4.93� (height) andfor images 75.17�. Digits were colored in yellow and outlined in so-lid black so they clearly highlighted from the pictures, on whichthey were superimposed. Pictures were taken from the Interna-tional Affective Picture System (N = 4; Lang, Bradley, & Cuthbert,2005) and from our own emotional picture database (N = 41;http://www.uam.es/CEACO/EmoMadrid.htm). These images wereselected on the basis of their scores in arousal (calming vs. arous-ing) and valence (positive vs. negative) taking into account our pre-vious experience with Spanish children samples. Both affectivedimensions are widely considered to explain the principal varianceof emotional meaning (Lang, Greenwald, Bradley, & Hamm, 1993;Russell 1980). Moreover, each child filled out a bidimensional scal-ing test of each picture after the recording sessions, assessing itsvalence (1 [negative] to 5 [positive] being the extremes of thisaffective dimension) and arousal (1 [calming] to 5[arousing]) lev-els. As explained later (results section), statistical analyses werecarried out on these ratings to confirm, first, that the pictures’affective valence was as assumed a priori, and second, that positiveand negative pictures were balanced with respect to their arousallevels. Furthermore, these analyses were applied to assess possible

Fig. 1. Schematic illustration of the experimental paradigm. An animation reproducing several trials of this paradigm as well as their temporal characteristics can be seen athttp://www.uam.es/CEACO/sup/ADHD_ED12.htm.

S. López-Martín et al. / Brain and Cognition 83 (2013) 10–20 13

differences between groups in the subjective feeling of valence andarousal caused by each distracter type. The complete set of stimuliused in the present study may be seen at http://www.uam.es/CEACO/sup/ADHD_ED12.htm.

The cognitive task concerned the digit presented in the center ofthe background picture: children had to press, as fast and accurateas possible, one response button with the thumb of their righthand for odd numbers and another button with the thumb of theirleft hand for even numbers. The same combination of digits was re-peated across conditions in order to ensure that task difficulty wasthe same for A�, N, and A+. Stimuli were presented in semi-ran-dom order in such a way that there were never more than threeconsecutive trials for the same emotional or numerical category.As illustrated in Fig. 1, each trial began with the presentation ofthe digit superimposed on the center of the picture (300 ms), fol-lowed by a white fixation cross on a dark background (1700 ms),so that the resulting onset asynchrony (SOA) was 2000 ms. An ani-mation reproducing several trials of the experimental task as wellas their temporal characteristics can be seen at http://www.uam.es/CEACO/sup/ADHD_ED12.htm. The experiment con-sisted of 60 trials per experimental condition (60 A�, 60 N, and60 A+), which were divided into two blocks of 90 trials each. Thus,each picture used as distracter was repeated four times.

Before the beginning of the experiment, subjects completed apractice block of 16 trials, with neutral pictures as backgrounddistracters to ensure that task instructions were understood. Theywere asked to look continuously at the center of the screen and torefrain from blinking, as much as possible, during block runs in or-der to minimize eye–movement interference. The task was pro-grammed using Inquisit Millisecond software (MillisecondSoftware, 2006) and presented through a RGB projector on a back-projection screen (48.8 � 65.6 cm). Participants were seated100 cm from this screen in an electrically shielded, sound-attenu-ated, and video-monitored room.

2.3. EEG recording and preprocessing

EEG activity was recorded using an electrode cap (ElectroCapInternational) with tin electrodes. Thirty electrodes were placedon the scalp in an extended 10–20 configuration: Fp1, Fpz, Fp2,AFz, F7, F3, Fz, F4, F8, FC5, FC1, FC2, FC6, T7, C3, Cz, C4, T8, CP5,CP3, CP2, CP6, P7, P3, Pz, P4, P8, O1, Oz, O2. All scalp electrodeswere referenced to the nose tip. Electrooculographic (EOG) datawere recorded supra- and infraorbitally (vertical EOG), as well asfrom the left versus right orbital rim (horizontal EOG). Electrodeimpedances were kept below 5 kO. An online bandpass filter of0.3–40 Hz was applied. Recordings were continuously digitized ata sampling rate of 210 Hz for the entire duration of the recordingsession. The continuous recording was divided into 1000-msepochs for each trial, beginning 200 ms before stimulus onset. Tri-als for which participants responded erroneously or did not re-

spond were eliminated. Epochs containing eye movements orblinks over 100 lV in amplitude were deleted. For the rest ofepochs, the EOG-artifact removal procedure described by Gratton,Coles, and Donchin (1983) was applied whenever EOG activity wasobserved. This artefact and error rejection procedure led to theaverage admission of 36.65 ± 9.33 (mean ± standard deviation)A� trials, 37.4 ± 8.68 N and 35.15 ± 9.75 A+ in the ADHD group,and 37.45 ± 7.72 A�, 37.55 ± 8.2 N and 37.50 ± 7.5 A+ in the Con-trol group. The number of valid trials did not differ between groups(F(1, 38) = 0.2, p = 0.67) or experimental conditions (i.e., distractertypes; F(2, 76) = 1.2, p = 0.31), and there was no group x conditioninteraction (F(2, 76) = 1.1, p = 0.33). The minimum number of trialsaccepted for averaging was 20 per subject and condition. Behav-ioral performance was recorded through a two-button keypadwhose electrical output was continuously digitized at a samplingrate of 840 Hz.

2.4. Data analysis

All statistical analyses described below were carried out usingthe SPSS software package (Version 15.0; SPSS Inc, Chicago, USA).Repeated-measures ANOVAs including Group (two levels: ADHDand Control) as between subjects factor and Distracter type (threelevels: A�, N, and A+) as within subjects factor were performed forbehavioral and ERP data. Contrasts especially relevant for our pur-poses were those showing a significant interaction between Groupand Distracter type. Significant interactions were further evaluatedusing simple effects with Bonferroni correction for multiple com-parisons. For all ANOVAs, the Greenhouse-Geisser epsilon (e) cor-rection was applied to within-subjects measures. Uncorrecteddegrees of freedom, corrected p values, and Greenhouse–Geissere values are provided, as recommended (Picton et al., 2000). Effectsizes are reported as partial eta-square (g2

p) for all significant ef-fects. Although age differences between groups were not signifi-cant, children with ADHD were somewhat older than controlsubjects (Table 1). For this reason, significant ANOVA results wereconfirmed using age as a covariate. All dependent variables, excepterror rates, were normally distributed, as assessed by Shapiro–Wil-ks W tests. Error rates were square root transformed before analy-sis to achieve a normal distribution.

2.4.1. Behavioral analysisPerformance in the digit categorization task was analyzed. To

that aim, mean RTs (to correct trials only) and square root trans-formed error rates (i.e., non-responses -omissions- and incorrectbutton presses) were submitted to repeated-measures ANOVAswith Group and Distracter type as factors. In the case of RTs, outli-ers, defined as responses above 2000 ms or below 200 ms, wereomitted in the analyses. As mentioned above, the RTs in the digitcategorization task to each distracter type were normally distrib-uted both in the ADHD and Control groups (A�: W = 0.93,

14 S. López-Martín et al. / Brain and Cognition 83 (2013) 10–20

p = 0.12; N: W = 0.94, p = 0.25; A+: W = 0.94, p = 0.25 for the ADHDgroup; A�: W = 0.91, p = 0.08; N: W = 0.92, p = 0.13; A+: W = 0.92,p = 0.09 for the Control group).

2.4.2. ERP analysisWith the aim of reliably testing whether N2 and LPC were pres-

ent in the ERPs, components explaining most of the variance in thetemporal domain were detected and quantified through a covari-ance-matrix-based temporal principal component analysis (tPCA).tPCA constitutes a useful data-driven method to distinguish com-ponents along time, thus ruling out the potentials confounds whendefining time windows of interest based on visual inspection ofgrand averages. Another advantage of tPCA is that it presents eachERP component with its ‘clean’ shape, extracting and quantifying itfree of the influences of adjacent or latent components. Indeed, thewaveform recorded at a site on the head over a period of severalhundreds of milliseconds represents a complex superposition ofdifferent overlapping electrical potentials. Such recordings can sty-mie visual inspection (see e.g., Albert, López-Martín, Hinojosa, &Carretié, 2013; Carretié et al., 2004; Spencer, Dien, & Donchin,2001). In brief, tPCA computes the covariance between all ERP timepoints, which tends to be high between those time points involvedin the same component and low between those belonging to differ-ent components (for further details see Dien & Frishkoff, 2005). Thesolution is therefore a set of factors made up of highly covaryingtime points, which ideally correspond to ERP components. Tempo-ral factor score, the tPCA-derived parameter in which extractedtemporal factors may be quantified, is linearly related toamplitude.

In the present study, tPCA was computed for 210 digitized volt-age points (from �200 to 800 ms) as data matrix variables and3600 cases resulting from the product of participants (40), condi-tions (3) and scalp electrodes (30). The decision on the numberof factors to select was based on the Parallel Analysis (Horn,1965; see also Dien, 2012 and Garrido, Abad, & Ponsoda, 2012).Briefly, PA compares eigenvalues extracted from our real datasetwith those extracted from a random matrix having the same num-ber of variables and cases. The number of factors retained wasdetermined as the number of real eigenvalues that were greaterthan the corresponding expected from the random matrix. In thepresent study, the 95th percentile average eigenvalues of 100 ran-dom covariance matrices were compared with the eigenvalues ob-tained from the real covariance matrix. The PA was implementedin the R statistical computing language (http://www.r-project.org).Retained factors were then quantified through a covariance-matrixand submitted to Promax rotation with a kappa value of 3, as rec-ommended (Dien, 2010; Dien, Khoe, & Mangun, 2007).

Signal overlapping may also occur at the space domain. At anygiven time point, several neural processes (and hence, several elec-trical signals) may concur, and the recording at any scalp locationat that moment is the electrical balance of these different neuralprocesses. While temporal PCA distinguish between ERP compo-nents along time, spatial PCA (sPCA) disentangles ERP componentsalong space, each spatial factor ideally reflecting one of the concur-rent neural processes underlying each temporal factor. Addition-ally, sPCA provides a reliable division of scalp into differentrecording regions, an advisable strategy prior to statistical con-trasts, since ERP components frequently behave differently in somescalp areas than in others (e.g., they present opposite polarity or re-act differently to experimental manipulations). Basically, each re-gion or spatial factor is formed with the scalp points whererecordings tend to covary. As a result, the shape of the sPCA-config-ured regions is functionally based. Moreover, each spatial factorcan be quantified through the spatial factor score, a single param-eter that reflects the amplitude of the whole spatial factor. In thecase of sPCA, which is applied to each temporal factor extracted

in the previous step, variables were temporal factor scores at eachelectrode (30) and cases were participants (40) � conditions (3).The decision on the number of factors to retain was also basedon the PA, and extracted factors were submitted to Promax rota-tion with a kappa value of 3 as well.

Finally, repeated-measures ANOVAs on N2 and LPC spatial fac-tor scores (linearly related to amplitudes) were performed withGroup as between subjects factor and Distracter type as withinsubjects factor.

3. Results

3.1. Emotional assessments

Table 2 shows the means and standard deviations of valenceand arousal for each group and each type of distracter. As previ-ously described, ANOVAs were computed for both emotionaldimensions, using Group as between-subjects factor and Distractertype as within-subjects factor. The main effect of Distracter typewas significant both for valence (F(2, 76) = 634.5, p = 0.000,e = 0.82, g2

p ¼ 0:94) and arousal dimensions (F(2, 76) = 257.6,p = 0.000, e = 0.94, g2

p ¼ 0:87). Bonferroni post hoc contrasts indi-cated that A� and A+ showed different valences (p = 0.000) butnot different arousal levels (p = 0.091). Moreover, both A+ andA� differed from N in arousal (A+ vs. N, p = 0.000; A� vs. N,p = 0.000) and valence (A+ vs. N, p = 0.000; A� vs. N, p = 0.000).The main effect of Distracter type remained significant after statis-tically controlling for age, both for valence (F(2, 74) = 13.4,p = 0.000, e = 0.82) and arousal (F(2, 74) = 7.6, p = 0.001, e = 0.94).Present results therefore confirm that the affective valence of eachdistracter type was as assumed a priori, and that negative and po-sitive distracters were balanced with respect to their arousal levels.Importantly, the interaction between Group and Distracter typewere not significant neither for valence (F(2, 76) = 0.7, p = 0.466,e = 0.82) nor for arousal (F(2, 76) = 1.3, p = 0.283, e = 0.94). Thesefindings indicate that there were no differences between ADHDand healthy control groups in the subjective feeling of valenceand arousal caused by each distracter type.

3.2. Behavioral data

Performance in the digit categorization task is shown in Table 2.Repeated-measures ANOVAs on RTs and error rates were per-formed using Group and Distracter type as factors. The main effectof Group was not significant for error rates (F(1, 38) = 0.8,p = 0.381). In the case of RTs, the main effect of Group was margin-ally significant (F(1, 38) = 4.2, p = 0.047, g2

p ¼ 0:1), showing thatRTs were shorter in the ADHD than in the control group (meansand standard errors: 689.72 ± 37.37 and 798.2 ± 37.37, respec-tively). The interaction of Group and Distracter type was not signif-icant in the case of error rates (F(2, 76) = 0.2, p = 0.789, e = 0.9), butproduced significant effects in RTs (F(2, 76) = 4.4, p = 0.021,e = 0.85, g2

p ¼ 0:1). Post hoc tests of simple effects with Bonferronicorrection for multiple comparisons showed that emotionaldistracters (both A+ and A�) were associated with longer RTs thanneutral distracters in the ADHD group (A� vs. N, p = 0.000; A+ vs.N, p = 0.000; A� vs. A+, p = 0.717), whereas no differences amongdistracters were observed in the Control group (A� vs. N,p = 0.195, A+ vs. N, p = 1, A+ vs. A�, p = 0.220). This interaction re-mained significant after controlling for age (F(2, 74) = 4.8,p = 0.015, e = 0.86, g2

p ¼ 0:11). Age was significant as a covariate(F(1, 37) = 20.1, p = 0.000, g2

p ¼ 0:35). Specifically, RTs decreasedlinearly with age (r = �0.64, p = 0.000). Group effects, however,were no longer significant when age was added as a covariate(means and standard errors for ADHD and Control groups:

Table 2Group means and standard deviations on subjective emotional ratings as well as on behavioral and electrophysiological (anterior N2) measures for each distracter type (A�,arousing negative; N, neutral; A+, arousing positive).

ADHD group Control group

A� N A+ A� N A+

Valencea 1.95 (0.41) 3.09 (0.14) 4.43 (0.28) 1.74 (0.31) 3.05 (0.18) 4.3 (0.39)Arousalb 4.09 (0.42) 2.95 (0.14) 4.36 (0.25) 4.19 (0.35) 2.96 (0.17) 4.24 (0.4)RTsc 704.5 (175.45) 668.36 (155.59) 696.29 (164.31) 807.26 (170.76) 792.71 (172.02) 794.62 (169.21)Error ratesd 0.13 (0.1) 0.13 (0.1) 0.15 (0.12) 0.1 (0.08) 0.09 (0.09) 0.1 (0.06)Anterior N2 factor scoree �0.43 (0.78) 0.36 (0.81) �0.65 (0.95) 0.22 (1.02) 0.43 (0.77) 0.07 (1.19)Anterior N2 amplitudef �4.19 (2.39) �2.21 (2.26) �4.9 (2.77) �2.73 (2.68) �2.32 (2.09) �3.09 (3.28)

a Valence: subjects’ valence ratings of distracting stimuli (from 1, negative, to 5, positive).b Arousal: subjects’ arousal ratings of distracting stimuli (from 1, negative, to 5, positive).c RTs: reaction times (in ms).d Error rates: omissions and incorrect button presses, divided by the number of trials.e Anterior N2 factor score: as explained in detail in the text, a single parameter that reflects the mean amplitude of the whole spatial factor. Negative values respresent

higher amplitudes.f Anterior N2 amplitude: average voltage (in lV) occurring in the 200–400 ms time interval across six frontocentral electrodes (see Supplementary Fig. 1).

Fig. 2. Grand average ERP response to each distracter type (A�, Arousing negative; N, neutral; A+, Arousing positive) for the ADHD and control groups. Grand averagewaveforms are shown at frontal and centroparietal electrodes, where N2 and LPC were more prominent, respectively.

Fig. 3. Topographic maps of the voltage distribution of N2 and LPC (collapsingacross distracter types) for the ADHD and control groups. Red represents positivevalues and blue represents negative values (lV). Because N2 is a negative wave,blue indicates larger N2 amplitudes. (For interpretation of the references to color inthis figure legend, the reader is referred to the web version of this article.).

S. López-Martín et al. / Brain and Cognition 83 (2013) 10–20 15

715.46 ± 31.02 and 772.46 ± .31.02, respectively; F(1, 37) = 1.6,p = 0.209). Therefore, although age differences between groupswere not significant (Table 1), the fact that the children with ADHDwere somewhat older than control children seems to be the reasonfor the group differences in RTs.

3.3. ERP data

Fig. 2 shows a selection of grand averages once the baseline va-lue (pre-stimulus recording) had been subtracted from each ERP.Two main deflections were noticeable. The first was a negativecomponent with an onset around 280 ms after distracter presenta-tion (N2). This component shows its maximum amplitude overfrontal and frontocentral electrode locations. The second deflectionwas a late positivity peaking around 585 ms after distracter onset(LPC). The largest amplitude of this positivity was observed at cent-roparietal locations. Fig. 3 represents the distribution of voltages ofthese components in the form of scalp maps for the ADHD andControl groups.

3.3.1. Temporospatial PCAAs a consequence of the application of the tPCA using the PA as

criterion of the number of factor to retain (Fig. 4A), five compo-nents were extracted from the ERPs (Fig. 5). Factor peak latencyand topography characteristics associate Factor 1 (peaking at280.95 ms) with the wave labeled N2 in grand averages and Factor2 (peaking at 585.71) with that labelled LPC. These labels will be

employed hereafter to make the results easier to understand. ThesPCA subsequently applied to N2 and LPC temporal factor scoresextracted three spatial factors for N2 and two for LPC (Fig. 6).

Fig. 4. Parallel Analysis to determine the number of factors to retain in tPCA (A) and sPCAs (B): Plots of eigenvalues from the real and random datasets. Only those factorsfrom the real datasets that explained more variance (i.e., had greater eigenvalues) than corresponding factors in the simulated random datasets were retained.

Fig. 5. Temporal principal component analysis (tPCA): factor loadings after Promax rotation. Temporal factors 1 (66.14% explained variance) and 2 (16.52% explainedvariance) are drawn in black. As mentioned in the text, only temporal factor 1 (N2) was sensitive to experimental manipulations.

Fig. 6. Spatial factors extracted for N2 (A) and LPC (B) through spatial principalcomponent analysis (sPCA). An asterisk signals the spatial factor sensitive to theexperimental manipulations (anterior N2). This spatial factor accounted for 54.79%of the variance of N2.

16 S. López-Martín et al. / Brain and Cognition 83 (2013) 10–20

The decision on the number of spatial factors to select for thesetwo ERP components was also based on the PA (Fig. 4B)

Repeated-measures ANOVAs on N2 and LPC spatial factor scores(directly related to amplitudes, as previously indicated) were then

carried out for Group and Distracter type factors. The main effect ofGroup was not significant in any of the N2 spatial factors. In otherwords, amplitudes did not differ between groups in the anterior N2(F(1, 38) = 3.3, p = 0.079), centroparietal N2 (F(1, 38) = 0.06,p = 0.803) or occipitally distributed N2 (F(1, 38) = 0.05, p = 0.821).However, a significant effect of the interaction of Group and Dis-tracter type was obtained in the anterior spatial factor of N2(F(2, 76) = 5.7, p = 0.006, e = 0.91, g2

p ¼ 0:13). Specifically, post hoctests of simple effects with Bonferroni correction for multiple com-parisons showed that anterior N2 amplitudes were larger (morenegative) for emotional distracters (both A+ and A�) than for neu-tral distracters in the ADHD group (A� vs. N, p = 0.000; A+ vs. N,p = 0.000; A+ vs. A�, p = 0.324), whereas no differences were ob-served in the Control group (A� vs. N, p = 0.407, A+ vs. N,p = 0.124, A+ vs. A�, p = 0.853). This interaction remained signifi-cant after controlling for age (F(2, 74) = 6.9, p = 0.002, e = 0.92,g2

p ¼ 0:16). Age was significant as a covariate (F(1, 37) = 5.3,p = 0.027, g2

p ¼ 0:12). Concretely, the amplitude of the anteriorN2 decreased linearly with age (r = 0.21, p = 0.022), which is con-sistent with previous studies showing age-related changes in theanterior N2 (Riis et al., 2009; Van Strien, Glimmerveen, Franken,Martens, & de Bruin, 2011). Neither the main effect of Group northe interaction of Group and Distracter type was significant in

Table 3Correlations between variables included in the regression model for the ADHD and control groups (dependent variable: anterior N2 amplitudes; independent variables: subjectivevalence and arousal ratings).

ADHD group Control group

Anterior N2 spatial score Valence Arousal Anterior N2 spatial score Valence Arousal

Anterior N2 spatial scorea – –Valenceb rp = �0.1 – rp = �0.06 –

p = 0.47 p = 0.66Arousalc rp = �0.4 r = 0.14 – rp = �0.08 r = 0.04 –

p = 0.002 p = 0.28 p = 0.53 p = 0.78

r = Pearson correlation; rp = Partial Pearson correlation, controlling for valence/arousal.a Anterior N2 factor score: a single parameter that reflects the mean amplitude of the whole spatial factor.b Valence: subjects’ valence ratings of distracting stimuli (from 1, negative, to 5, positive).c Arousal: subjects’ arousal ratings of distracting stimuli (from 1, calming, to 5, arousing).

S. López-Martín et al. / Brain and Cognition 83 (2013) 10–20 17

the centroparietally distributed LPC (Group: F(1, 38) = 0.7,p = 0.395; Group x Distracter type: F(2, 76) = 0.3, p = 0.754,e = 0.99) or the anteriorly distributed LPC (Group: F(1, 38) = 0.2,p = 0.695; Group x Distracter type: F(2, 76) = 0.7, p = 0.516,e = 0.98).

3.3.2. Conventional ERP analysisIn order to compare results from temporospatial PCA with tra-

ditional ERP waveform analysis, we also assessed the N2 and LPCas mean voltage amplitudes within the 200–400 ms and 500–700 ms intervals, respectively. Amplitudes were measured with re-spect to the average of the 200 ms pre-stimulus baseline. Scalp re-gions of interest were defined, and the average amplitude recordedby those electrodes forming each of these regions was computed.Time windows and scalp regions of interest were determinedbased on previous research as well as on visual inspection of grandaverages and topographic map of the voltage distribution of eachcomponent (Figs. 2 and 3). For N2, a frontocentral region compris-ing six electrodes (AFz, F3, Fz, F4, FC1, and FC2) was selected. ForLPC, a centroparietal region comprising five electrodes (CP1, CP2,P3, Pz, and P4) was chosen. Supplementary Fig. 1 shows the se-lected electrode region for each component.

Repeated-measures ANOVAs on these two regions were thencarried out for Group and Distracter type factors. Results were sim-ilar to those obtained using temporospatial PCA. For anterior N2,the main effect of Group was not significant (F(1, 38) = 2.1,p = 0.152). However, it was sensitive to the interaction of Groupand Distracter type (F(2, 76) = 4.4, p = 0.016, e = 0.97, g2

p ¼ 0:1).Bonferroni post hoc tests of simple effects showed that anteriorN2 amplitudes were larger for emotional (both A� and A+) thanfor neutral distracters in the ADHD group (A� vs. N, p = 0.000; A+vs. N, p = 0.000; A+ vs. A�, p = 0.441), but not in the Control group(A� vs. N, p = 1; A+ vs. N, p = 0.447; A+ vs. A�, p = 1). This interac-tion remained significant after controlling for age (F(2, 74) = 5.9,p = 0.005, e = 0.98, g2

p ¼ 0:14). Neither the main effect of Group(F(1, 38) = 0.01, p = 0.902) nor the interaction of Group and Dis-tracter type (F(2, 76) = 0.5, p = 0.621, e = 0.87) was significant inthe centroparietally distributed LPC.

3.4. Relationship between emotional assessments and ERP data

Although it is reasonable to deduce from previous analyses thatarousal more than valence explains results concerning the anteriorN2 component in the ADHD group, since differences between emo-tional (both A+ and A�) and neutral distracters are clear, this trendrequired statistical confirmation. To this end, the associations be-tween anterior N2 factor scores (equivalent to traditional ampli-tudes, as mentioned before) and subjects’ emotional ratings ofdistracting stimuli were analyzed via multiple regressions (entermethod) in both groups. Anterior N2 amplitude was the dependent

variable, and independent variables were valence and arousal rat-ings. In the ADHD group, arousal associated significantly with ante-rior N2 (F(2, 57) = 6.02, p = 0.004; b = �0.4, p = 0.002), whilevalence did not (b = �0.09, p = 0.475). Concretely, the linear associ-ation pattern between anterior N2 amplitudes and arousal pre-sented a negative slope: the larger -more negative- the former,the greater the latter. By contrast, neither valence nor arousalwas associated with anterior N2 amplitude in the control group(F(2, 57) = 0.3, p = 0.735; b = �0.06, p = 0.657 and b = �0.08,p = 0.531, respectively). Table 3 shows, for each group, the correla-tions between the independent variables, and between each inde-pendent variable and the dependent variable. The inclusion ofage as an additional predictor variable did not alter the results ofthe regression analyses, neither for the ADHD nor for the controlgroup.

4. Discussion

This is the first study, to our knowledge, to examine the effect ofirrelevant emotional distracters on goal-directed processing inchildren with ADHD. Both behavioral and neural data indicate thatboys with ADHD show enhanced susceptibility to emotional dis-traction with respect to typically developing healthy comparisonsubjects. At the behavioral level, we found that, in the ADHD group,emotional distracters were associated with longer RTs in the digitcategorization task than neutral distracters. By contrast, no behav-ioral differences among distracters were found in the controlgroup. At the electrophysiological level, we found that anteriorN2 amplitudes were greater for emotional than for neutraldistracters in ADHD children, whereas no differences were ob-served in healthy comparison subjects. Moreover, regression anal-yses between anterior N2 amplitudes and subjects’ emotionalratings of distracting stimuli showed that only in the ADHD group,arousal ratings were associated with anterior N2: its amplitude in-creased as the arousal content of the visual distracter increased.These data, therefore, suggest that boys with ADHD are more vul-nerable to the distracting effects of task-irrelevant high-arousingemotional stimuli than healthy comparison subjects. This conclu-sion is in line with the fact that enhanced distractibility is observedin ADHD children when they are in real social contexts, such asschool and home, where distracters are often affectively loaded.Likewise, present results provide further empirical support forthe current inclusion of distractibility as one of the behavioraldiagnostic criteria of ADHD (American Psychiatric Association,2000).

The results of the current study suggest that anterior N2 is auseful neural index of emotional distraction in ADHD. Althoughthe complete functional dissociation of frontally distributed N2components is probably difficult to achieve (Albert et al., 2013;Kropotov, Ponomarev, Hollup, & Mueller, 2011), it has been

18 S. López-Martín et al. / Brain and Cognition 83 (2013) 10–20

suggested that anterior N2 should be divided into, at least, the con-trol-related N2 and the novelty/mismatch N2 (for a review see Fol-stein & Van Petten, 2008; see also Kropotov et al., 2011). Theformer is primarily elicited by executive control paradigms, suchas the go/nogo, stop-signal and especially Eriksen flanker tasks(Buss, Dennis, Brooker, & Sippel, 2011; Donkers & Van Boxtel,2004; Enriquez-Geppert et al., 2010; Nieuwenhuis et al., 2003;Ran-dall & Smith, 2011; Van Veen & Carter, 2002). This anterior N2 isthought to index top-down control processing such as conflictmonitoring (Donkers & Van Boxtel, 2004; Enriquez-Geppert et al.,2010;Randall & Smith, 2011). The latter has been consistently asso-ciated with the rapid detection of novelty and significance usingdifferent distraction and oddball paradigms (Carretié et al., 2004;Chong et al., 2008; Daffner et al., 2000; Kenemans et al., 1992;Rozenkrants & Polich, 2008; Tarbi et al., 2011). Notably, as in thepresent study, some of these investigations have shown largeranterior N2 amplitudes in response to novel and emotional stimulieven when attention was not engaged and directed to them (Car-retié et al., 2004; Tarbi et al., 2011), suggesting that this N2 compo-nent is related to stimulus-driven attentional processes. Theanterior N2 elicited by our experimental paradigm seems to be pri-marily related to bottom-up attentional mechanisms. Indeed, bothcategorical and dimensional analyses indicated that, in patientswith ADHD, the amplitude of the anterior N2 was associated withthe emotional content of distracters, suggesting that it was auto-matically driven by the salience of these task-irrelevant stimuli.

As indicated by the lack of a main effect of group, boys withADHD showed similar N2 amplitudes to controls in response todistracters when emotional conditions were not taken into ac-count. However, they diverged from controls in anterior N2 ampli-tudes associated with emotional compared to neutral distracters.These results highlight the importance of incorporating emotionalstimuli into distraction paradigms in order to enhance the interfer-ence of task-irrelevant distracters on goal-directed behavior,reflecting what actually occurs in many real social situations. Asmentioned before, only affectively neutral visual stimuli have beenused previously in studies examining the neural substrates ofattention functioning in ADHD (e.g., Booth et al., 2005; Huang-Pol-lock et al., 2005; Jonkman et al., 2000; Meere & Sergeant, 1988). Onthe other hand, the results of the present study suggest that the en-hanced emotional distractibility seen in ADHD children seems tobe more related to an exaggerated bottom-up response to the sal-iency of distracters rather than to a failure to implement top-downcontrol processes to avoid distraction. In this vein, it should bepointed out that children with ADHD did not differ from controlswith respect to LPC. In the present study, this component seemsto reflect a more controlled stage of processing triggered by previ-ous automatic processing (N2-associated), which would be in linewith some previous studies on novelty/significance processing(Chong et al., 2008; Kenemans et al., 1992; Liddell et al., 2004).Centroparietally distributed late positivities, such as P3b, are ofteninterpreted as reflecting limited-resource processing of task-rele-vant information, such as stimulus categorization and allocationof attention resources for memory updating (Donchin, 1981; Kok,2001; Polich, 2007; Verlerger, 1998). In the context of emotion re-search, increasing evidence suggests that the LPC is sensitive totop-down manipulations of attention. Indeed, it has been proposedas a neural correlate of top-down emotion regulation, both inadults and children (Dennis & Hajcak, 2009; Moser et al., 2006).Thus, one of these studies has found that the amplitude of the cent-roparietal LPC decreased when subjects were asked to intention-ally suppress their affective responses to high arousing emotionalstimuli (Moser et al., 2006). Taking into consideration the resultsof these studies, current results with respect to LPC may indicatethat the enhanced levels of emotional distraction observed in ourpatients with ADHD were not related to deficits in more controlled

and conscious stages of emotional/cognitive processing. Thesefindings are of critical relevance for the current debate regardingthe nature (top-down vs. bottom-up) and extent (present or not)of attentional deficits in ADHD (Friedman-Hill et al., 2010; Gumen-yuk et al., 2005; Huang-Pollock et al., 2005; Sonuga-Barke et al.,2004).

Dysfunction of top-down inhibitory control has long been theo-rized to be the central feature of ADHD (Barkley, 1997). Convergentdata for impaired inhibitory control in ADHD have been found instudies using functional brain measures (Albrecht et al., 2008;Dimoska et al., 2003; Liotti et al., 2007; Pliszka et al., 2000; Rubiaet al., 1999). These studies have generally reported decreased acti-vation of fronto-striatal brain regions and reduced amplitudes ofthe frontally distributed N2 related to top-down processing (i.e.,the N2 primarily associated with conflict monitoring) while ADHDpatients were engaged in non-emotional executive tasks such asthe go/nogo or stop-signal tasks. Considering this strong evidence,impairments in top-down cognitive processing and its neurobio-logical basis were thought to be the cause of distractibility inADHD (Barkley, 1997). Thus, from this perspective, theenhanced distractibility in patients with ADHD would be associ-ated with impairments in the ability to monitor and resolve con-flict evoked by distracter stimuli, by incapacity either to enhancetask-relevant representations or to inhibit task-irrelevant informa-tion. It should be noted, however, that the deficit in top-downinhibitory control is not present among all patients with ADHDand cannot explain alone the great heterogeneity of the disorder(Banaschewski et al., 2004; Castellanos et al., 2006; Sonuga-Barke,2002; Willcutt et al., 2005). Abnormalities in other brain regionsbeyond the fronto-striatal circuit (including mesolimbic and visualnetworks: Ahrendts et al., 2011; Castellanos & Proal, 2012; Vaidya& Stollstorff, 2008) and impairments in other psychological pro-cesses beyond inhibitory control (including bottom-up and affec-tive mechanisms: Brotman et al., 2010; Herrmann et al., 2011;Plichta et al., 2009; Posner et al., 2011b) are also present among pa-tients with ADHD. Interestingly, some of these studies have foundamygdalar hyperactivation in patients with ADHD during delayedreward and emotion processing (Brotman et al., 2010; Maieret al., 2013; Plichta et al., 2009; Posner et al., 2011b), even whenthe emotional stimulation was presented subliminally (Posneret al., 2011b). The amygdala seems to play a crucial role in the bot-tom-up or involuntary response to emotional stimuli (Vuilleumier,2005; Vuilleumier & Schwartz, 2001; Whalen et al., 1998). In lightof this recent evidence and as suggested by present results, we pro-pose that distractibility in ADHD might also arise from an abnor-mal involuntary response to affective stimuli.

The results of the present study should be interpreted in light ofseveral limitations. Firstly, the clinical group was restricted to boyswith a clinical diagnosis of ADHD combined subtype. Furtherinvestigations should include girls and other subtypes to deter-mine whether the findings of the current experiment can be gener-alized across different populations with ADHD. Secondly, most ofthe patients of the present study were not medication-naïve (onlyfour of the boys with ADHD had no prior history of any medicationuse). It would be interesting to replicate this study in medication-naïve patients as well as to examine the effect of medication onneural and behavioral mechanisms underlying emotional distrac-tion in ADHD. Interestingly, some recent evidence suggests thatstimulant medication normalizes emotional processing in individ-uals with ADHD by attenuating abnormal activity within affectivebrain mechanisms (Posner et al., 2011a, 2011b). Therefore, the ef-fects observed in the present study would probably be intensifiedrather than attenuated when investigated on a medication-naïvesample. Finally, this study exclusively explored the timing andtopographic characteristics of the neural processes underlyingemotional distractibility in ADHD. Future studies examining the

S. López-Martín et al. / Brain and Cognition 83 (2013) 10–20 19

origin of these neural processes within the brain are needed to pro-vide a more complete picture of the neural substrates underlyingemotional distraction in ADHD.

Notwithstanding its limitations, the present study represents animportant new step toward the integration of cognitive and affec-tive neuroscience to obtain a comprehensive understanding ofneurobiological basis of ADHD. By capitalizing on the high tempo-ral resolution of the ERPs, the results of the present experimentprovide insight into the timing of the neural processes underlyingemotional distractibility in ADHD. Firstly, we found that, in com-parison with healthy controls, boys with ADHD showed an in-creased susceptibility to emotional distraction. Secondly, weobserved that the poor ability of ADHD children to remain goal ori-ented in the face of distracting irrelevant stimuli seems to be morerelated to an excessive bottom-up response to emotionally ladendistracters than to the hypofunction of top-down brain mecha-nisms. These results emphasize the view of ADHD as a complexdisorder in which top-down and bottom-up mechanisms as wellas cognitive and affective processes are involved.

Acknowledgments

This work was supported by the Obra Social and Cultural de Caj-aSegovia and the Grants PSI2008-03688 and PSI2011-26314 fromthe Ministerio de Economía y Competitividad (MINECO) of Spain.MINECO also supports Jacobo Albert through a Juan de la CiervaGrant (JCI-2010-07766). The authors wish to thank Dr. V. Ponsoda,Department of Social Psychology and Methodology at the Univers-idad Autónoma de Madrid, for his help with programming thecovariance-based Parallel Analysis in R statistical computinglanguage.

Appendix A. Supplementary material

Supplementary data associated with this article can be found, inthe online version, at http://dx.doi.org/10.1016/j.bandc.2013.06.004.

References

Ahrendts, J., Rüsh, N., Wilke, M., Philipsen, A., Eickhoff, S. B., Glauche, V., et al.(2011). Visual cortex abnormalities in adults with ADHD: A structural MRIstudy. World Journal of Biological Psychiatry, 12, 260–270.

Albert, J., López-Martín, S., Hinojosa, J. A., & Carretié, L. (2013). Spatiotemporalcharacterization of response inhibition. NeuroImage, 76, 272–281.

Albrecht, B., Brandeis, D., Uebel, H., Heinrich, H., Mueller, U. C., Hasselhorn, M., et al.(2008). Action monitoring in boys with attention-deficit/hyperactivity disorder,their nonaffected siblings, and normal control subjects: Evidence for anendophenotype. Biological Psychiatry, 64, 615–625.

American Psychiatric Association (2000). Diagnostic and Statistical Manual of MentalDisorders: DSM-IV-TR. Washington, DC: American Psychiatric Association.

Banaschewski, T., Brandeis, D., Heinrich, H., Albrecht, B., Bruner, E., & Rothenberger,A. (2004). Questioning inhibitory control as the specific deficit of ADHD:Evidence from brain electrical activity. Journal of Neural Transmission, 111,841–864.

Barkley, R. A. (1997). Behavioral inhibition, sustained attention, and executivefunctions: Constructing a unifying theory of ADHD. Psychological Bulletin, 121,65–94.

Barkley, R. A., & Cox, D. (2007). A review of driving risks and impairments associatedwith attention-deficit/hyperactivity disorder and the effects of stimulantmedication on driving performance. Journal of Safety Research, 38, 113–128.

Barry, R. J., Johnstone, S. J., & Clarke, A. R. (2003). A review of electrophysiology inattention-deficit/hyperactivity disorder: II. Event-related potentials. ClinicalNeurophysiology, 114, 184–198.

Booth, J. R., Burman, D. D., Meyer, J. R., Lei, Z., Trommer, B. L., Davenport, N. D., et al.(2005). Larger deficits in brain networks for response inhibition than for visualselective attention in attention deficit hyperactivity disorder (ADHD). Journal ofChild Psychology and Psychiatry, 46, 94–111.

Brandeis, D., Banascheswski, T., Baving, L., Georgiewa, P., Blanz, B., Schmidt, M. H.,et al. (2002). Multicenter P300 brain mapping of impaired attention to cues inhyperkinetic children. Journal of the American Academy of Child and AdolescentPsychiatry, 41, 990–998.

Brandeis, D., van Leeuwen, T. H., Rubia, K., Vitacco, D., Steger, J., Pascual-Marqui, R.D., et al. (1998). Neuroelectric mapping reveals precursor of stop failures inchildren with attention deficits. Behavioural Brain Research, 94, 111–125.

Brotman, M. A., Rich, B. A., Guyer, A. E., Lunsford, J. R., Horsey, S. E., Reising, M. M.,et al. (2010). Amygdala activation during emotion processing of neutral faces inchildren with severe mood dysregulation versus ADHD or bipolar disorder.American Journal of Psychiatry, 167, 61–69.

Buss, K. A., Dennis, T. A., Brooker, R. J., & Sippel, L. M. (2011). An ERP study of conflictmonitoring in 4–8-year old children: Associations with temperament.Developmental Cognitive Neuroscience, 1, 131–140.

Carretié, L., Hinojosa, J. A., Martin-Loeches, M., Mercado, F., & Tapia, M. (2004).Automatic attention to emotional stimuli: Neural correlates. Human BrainMapping, 22, 290–299.

Carretié, L., Hinojosa, J. A., Mercado, F., & Tapia, M. (2005). Cortical response tosubjectively unconscious danger. Neuroimage, 24, 615–623.

Castellanos, F. X., & Proal, E. (2012). Large-scale brain systems in ADHD: Beyond theprefrontal–striatal model. Trends in Cognitive Sciences, 16, 17–26.

Castellanos, F. X., Sonuga-Barke, E. J., Milham, M. P., & Tannock, R. (2006).Characterizing cognition in ADHD: Beyond executive dysfunction. Trends inCognitive Sciences, 10, 117–123.

Chong, H., Riis, J. L., McGinnis, S. M., Williams, D. M., Holcomb, P. J., & Daffner, K. R.(2008). To ignore or explore: Top–down modulation of novelty processing.Journal of Cognitive Neuroscience, 20, 120–134.

Corbetta, M., Patel, G., & Shulman, G. L. (2008). The reorienting system of the humanbrain: From environment to theory of mind. Neuron, 58, 306–324.

Corbetta, M., & Shulman, G. L. (2002). Control of goal-directed and stimulus-drivenattention in the brain. Nature Reviews Neuroscience, 3, 201–215.

Daffner, K. R., Mesulam, M., Scinto, L. F. M., Calvo, V., Faust, R., & Holcomb, P. J.(2000). An electrophysiological index of stimulus unfamiliarity.Psychophysiology, 37, 737–747.

Dennis, T. A., & Hajcak, G. (2009). The late positive potential: A neurophysiologicalmarker for emotion regulation in children. Journal of Child Psychology andPsychiatry, 50, 1373–1383.

Dien, J. (2010). Evaluating two-step PCA of ERP data with geomin, infomax, oblimin,promax, and varimax rotations. Psychophysiology, 47, 170–183.

Dien, J. (2012). Applying principal components analysis to event-related potentials:A tutorial. Developmental Neuropsychology, 37, 497–517.

Dien, J., & Frishkoff, G. A. (2005). Principal components analysis of event relatedpotential datasets. In T. Handy (Ed.), Event-related potentials: A methodshandbook (pp. 189–208). Cambridge, MA: MIT Press.

Dien, J., Khoe, W., & Mangun, G. R. (2007). Evaluation of PCA and ICA of simulatedERPs: Promax Vs. Infomax rotations. Human Brain Mapping, 28, 742–763.

Dimoska, A., Johnstone, S. J., Barry, R. J., & Clarke, A. R. (2003). Inhibitory motorcontrol in children with attention-deficit/hyperactivity disorder: Event-relatedpotentials in the stop-signal paradigm. Biological Psychiatry, 54, 1345–1354.

Donchin, E. (1981). Surprise!. . .surprise? Psychophysiology, 18, 493–513.Donkers, F. C., & van Boxtel, G. J. (2004). The N2 in go/no-go tasks reflects conflict

monitoring not response inhibition. Brain and cognition, 56, 165–176.DuPaul, G. J., Power, T. J., Anastopoulos, A. D., & Reid, R. (1998). ADHD rating Scale—

IV: Checklists, norms, and clinical interpretation. New York: Guilford Press.Enriquez-Geppert, S., Konrad, C., Pantev, C., & Huster, R. J. (2010). Conflict and

inhibition differentially affect the N200/P300 complex in a combined go/nogoand stop-signal task. Neuroimage, 51, 877–887.

Folstein, J. R., & Van Petten, C. (2008). Influence of cognitive control and mismatchon the N2 component of the ERP: A review. Psychophysiology, 45, 152–170.

Friedman-Hill, S. R., Wagman, M. R., Gex, S. E., Pine, D. S., Leibenluft, E., &Ungerleider, L. G. (2010). What does distractibility in ADHD reveal aboutmechanisms for top-down attentional control? Cognition, 115, 93–103.

Garrido, L. E., Abad, F. J., & Ponsoda, V. (2012). A new look at Horn’s parallel analysiswith ordinal variables. Psychological Methods. http://dx.doi.org/10.1037/a0030005.

Gratton, G., Coles, M. G., & Donchin, E. (1983). A new method for off-line removal ofocular artifact. Electroencephalography and Clinical Neurophysiology, 55,468–484.

Guilford, J. P., & Fruchter, B. (1973). Fundamental statistics in psychology andeducation. New York: McGraw-Hill.

Gumenyuk, V., Korzyukov, O., Escera, C., Hamalainen, M., Huotilainen, M., Hayrinen,T., et al. (2005). Electrophysiological evidence of enhance distractibility inADHD children. Neuroscience Letters, 374, 212–217.

Herrmann, M. J., Schreppel, T., Biehl, S. C., Jacob, C., Heine, M., Boreatti-Hummer, A.,et al. (2011). Emotional deficits in adult ADHD patients: An ERP study. SocialCognitive and Affective Neuroscience, 4, 340–345.

Higginbotham, P., & Bartling, C. (1993). The effects of sensory distractions onshort-term recall of children with attention deficit-hyperactivity disorderversus normally achieving children. Bulletin of the Psychonomic Society, 31,507–510.

Horn, J. L. (1965). A rationale and test for the number of factors in factor analysis.Psychometrika, 30, 179–185.

Huang-Pollock, C. L., Nigg, J. T., & Carr, T. H. (2005). Deficient attention is hard tofind: Applying the perceptual load model of selective attention to attentiondeficit hyperactivity disorder subtypes. Journal of Child Psychology andPsychiatry, 46, 1211–1218.

Jensen, P. S., Hinshaw, S. P., Kraemer, H. C., Lenora, N., Newcorn, J. H., Abikoff, H. B.,et al. (2001). ADHD comorbidity findings from the MTA study: Comparingcomorbid subgroups. Journal of the American Academy of Child and AdolescentPsychiatry, 40, 147–158.

20 S. López-Martín et al. / Brain and Cognition 83 (2013) 10–20

Jonkman, L. M., Kemner, C., Verbaten, M. N., Van Engeland, H. V., Camfferman, G.,Buitelaar, J. K., et al. (2000). Attentional capacity, a probe ERP study: Differencesbetween children with attention-deficit hyperactivity disorder and normalcontrol children and effects of methylphenidate. Psychophysiology, 37, 334–346.

Kaufman, J., Birmaher, B., Brent, D., Rao, U., Flynn, C., Moreci, P., et al. (1997).Schedule for affective disorders and schizophrenia for school-age children-present and lifetime version (K-SADS-PL): Initial reliability and validity data.Journal of the American Academy of Child and Adolescent Psychiatry, 36, 980–988.

Kenemans, J., Verbaten, M., Melis, C., & Slangen, J. (1992). Visual stimulus changeand the orienting reaction: Event-related potential evidence for a two-stageprocess. Biological Psychology, 33, 97–114.

Köchel, A., Leutgeb, V., & Schienle, A. (2012). Affective inhibitory control in adultswith attention deficit hyperactivity disorder: Abnormalities in electrocorticallate positivity. Neuroscience Letters, 530, 47–52.

Kok, A. (2001). On the utility of P3 amplitude as a measure of processing capacity.Psychophysiology, 38, 557–577.

Kropotov, J. D., Ponomarev, V. A., Hollup, S., & Mueller, A. (2011). Dissociating actioninhibition, conflict monitoring and sensory mismatch into independentcomponents of event related potentials in go/nogo task. Neuroimage, 57,565–575.

Lang, P. J., Bradley, M. M., & Cuthbert, B. N. (2005). International affective picturesystem (IAPS): Affective ratings of pictures and instruction manual. Technicalreport A-6. Gainesville, FL: University of Florida.

Lang, P. J., Greenwald, M. K., Bradley, M. M., & Hamm, A. O. (1993). Looking atpictures: Affective, facial, visceral, and behavioral reactions. Psychophysiology,30, 261–273.

Lawrence, V., Houghton, S., Tannock, R., Douglas, G., Durkin, K., & Whiting, K. (2002).ADHD outside the laboratory: Boys’ executive function performance on tasks invideogame play and on a visit to the zoo. Journal of Abnormal Child Psychology,30, 447–462.

Liddell, B. J., Williams, L. M., Rathjen, J., Shevrin, H., & Gordon, E. (2004). A temporaldissociation of subliminal versus supraliminal fear perception: An event-relatedpotential study. Journal of Cognitive Neuroscience, 16, 479–486.

Liotti, M., Pliszka, S. R., Perez, R., Kothmann, D., & Woldorff, M. G. (2005). Abnormalbrain activity related to performance monitoring and error detection in childrenwith ADHD. Cortex, 41, 377–388.

Liotti, M., Pliszka, S. R., Perez, R., Luus, B., Glahn, D., & Semrud-Clikeman, M. (2007).Electrophysiological correlates of response inhibition in children andadolescents with ADHD: Influence of gender, age, and previous treatmenthistory. Psychophysiology, 44, 936–948.

Lorch, E. P., Milich, R., Sanchez, R. P., van den Broek, P., Baer, S., Hooks, K., et al.(2000). Comprehension of televised stories in boys with attention deficit/hyperactivity disorder and nonreferred boys. Journal of Abnormal Psychology,109, 321–330.

Maedgen, J. W., & Carlson, C. L. (2000). Social functioning and emotional regulationin the attention deficit hyperactivity disorder subtypes. Journal of Clinical ChildPsychology, 29, 30–42.

Maier, S. J., Szalkowski, A., Kamphausen, S., Feige, B., Perlov, E., Kalisch, R., et al.(2013). Altered cingulate and amygdala response towards threat and safe cuesin attention deficit hyperactivity disorder. Psychological Medicine. http://dx.doi.org/10.1017/S0033291713000469.

Marx, I., Domes, G., Havenstein, C., Berger, C., Schulze, L., & Herpertz, S. C. (2011).Enhanced emotional interference on working memory performance in adultswith ADHD. World Journal of Biological Psychiatry, 12, 70–75.

Mason, D. J., Humphreys, G. W., & Kent, L. (2005). Insights into the control ofattentional set in ADHD using the attentional blink paradigm. Journal of ChildPsychology and Psychiatry, 46, 1345–1353.

McLoughlin, G., Albrech, B., Banaschewski, T., Rothenberger, A., Brandeis, D.,Asherson, P., et al. (2010). Electrophysiological evidence for abnormalpreparatory states and inhibitory processing in adult ADHD. Behavioral andBrain Functions, 6, 66.

Meere, J., & Sergeant, J. (1988). Focused attention in pervasively hyperactivechildren. Journal of Abnormal Child Psychology, 16, 627–639.

Millisecond Software (2006). Inquisit 2.0.60616. Millisecond Software, Seattle, WA[Computer software].

Moser, J. S., Hajcak, G., Bukay, E., & Simons, R. F. (2006). Intentional modulation ofemotional responding to unpleasant pictures: An ERP study. Psychophysiology,43, 292–296.

Nieuwenhuis, S., Yeung, N., Van Den Wildenberg, W., & Ridderinkhof, K. R. (2003).Electrophysiological correlates of anterior cingulate function in a go/no-go task:effects of response conflict and trial type frequency. Cognitive, Affective, &Behavioral Neuroscience, 3, 17–26.

Nigg, J. T., & Casey, B. J. (2005). An integrative theory of attention-deficit/hyperactivity disorder based on the cognitive and affective neurosciences.Development and Psychopathology, 17, 785–806.

Öhman, A., Flykt, A., & Esteves, F. (2001). Emotion drives attention: Detecting thesnake in the grass. Journal of Experimental Psychology, 130, 466.

Olofsson, J. K., Nordin, S., Sequeira, H., & Polich, J. (2008). Affective pictureprocessing: An integrative review of ERP findings. Biological Psychology, 77,247–265.

Picton, T. W., Bentin, S., Berg, P., Donchin, E., Hillyard, S. A., & Johnson, R. Jr., (2000).Guidelines for using human event-related potentials to study cognition:Recording standards and publication criteria. Psychophysiology, 37, 127–152.

Plichta, M. M., Vasic, N., Wolf, R. C., Lesch, K. P., Brummer, D., Jacob, C., et al. (2009).Neural hyporesponsiveness and hyperresponsiveness during immediate and

delayed reward processing in adult attention-deficit/hyperactivity disorder.Biological Psychiatry, 65, 7–14.

Pliszka, S. R., Liotti, M., & Woldorff, M. G. (2000). Inhibitory control in children withattention-deficit/hyperactivity disorder: Event-related potentials identify theprocessing component and timing of an impaired right-frontal response-inhibition mechanism. Biological Psychiatry, 48, 238–246.

Polich, J. (2007). Updating P300: An integrative theory of P3a and P3b. ClinicalNeurophysiology, 118, 2128.

Posner, J., Maia, T. V., Fair, D., Peterson, B. S., Sonuga-Barke, E. J., & Nagel, B. J.(2011a). The attenuation of dysfunctional emotional processing with stimulantmedication: An fMRI study of adolescents with ADHD. Psychiatry Research-Neuroimaging Section, 193, 151–160.

Posner, J., Nagel, B. J., Maia, T. V., Mechling, A., Oh, M., Wang, Z., et al. (2011b).Abnormal amygdalar activation and connectivity in adolescents with attention-deficit/hyperactivity disorder. Journal of the American Academy of Child andAdolescent Psychiatry, 50, 828–837.

Radosh, A., & Gittelman, R. (1981). The effect of appealing distractors on theperformance of hyperactive children. Journal of Abnormal Child Psychology, 9,179–189.

Randall, W. M., & Smith, J. L. (2011). Conflict and inhibition in the cued-Go/NoGotask. Clinical Neurophysiology, 122, 2400–2407.

Riis, J. L., Chong, H., McGinnnis, S., Tarbi, E., Sun, X., Holcomb, P. J., et al. (2009). Age-related changes in early novelty processing as measured by ERPs. BiologicalPsychology, 82, 33–44.

Rosenthal, R. H., & Allen, T. W. (1980). Intratask distractibility in hyperkineticand nonhyperkinetic children. Journal of Abnormal Child Psychology, 8,175–187.

Rozenkrants, B., & Polich, J. (2008). Affective ERP processing in a visual oddball task:Arousal, valence, and gender. Clinical Neurophysiology, 119, 2260–2265.

Rubia, K., Overmeyer, S., Taylor, E., Brammer, M., Williams, S. C., Simmons, A., et al.(1999). Hypofrontality in attention deficit hyperactivity disorder during higher-order motor control: A study with functional MRI. American Journal ofPsychiatry, 156, 891–896.

Russell, J. A. (1980). A circumplex model of affect. Journal of Personality and SocialPsychology, 39, 1161–1178.

Sattler, J. (2001). Assessment of children: Cognitive applications. La Mesa, CA: JeromeM. Sattler, Publisher.

Sergeant, J. A. (2005). Modeling attention-deficit/hyperactivity disorder: Acritical appraisal of the cognitive-energetic model. Biological Psychiatry, 57,1248–1255.

Shifrin, J. G., Proctor, B. E., & Prevatt, F. F. (2010). Work performance differencesbetween college students with and without ADHD. Journal of AttentionDisorders, 13, 489–496.

Sonuga-Barke, E. J. S. (2002). Psychological heterogeneity in AD/HD—a dualpathway model of behaviour and cognition. Behavioural Brain Research, 130,29–36.

Sonuga-Barke, E. J. S., De Houwer, J., De Ruiter, K., Ajzenstzen, M., & Holland, S.(2004). AD/HD and the capture of attention by briefly exposed delay-relatedcues: Evidence from a conditioning paradigm. Journal of Child Psychology andPsychiatry, 45, 274–283.

Spencer, K. M., Dien, J., & Donchin, E. (2001). Spatiotemporal analysis of the late ERPresponses to deviant stimuli. Psychophysiology, 38, 343–358.

Tarbi, E. C., Sun, X., Holcomb, P. J., & Daffner, K. R. (2011). Surprise? Early visualnovelty processing is not modulated by attention. Psychophysiology, 48,624–632.

Ulloa, R. E., Ortiz, S., Higuera, F., Nogales, I., Fresan, A., Apiquian, R., et al. (2006).Interrater reliability of the spanish version of schedule for affective disordersand schizophrenia for school-age children–present and lifetime version (K-SADS-PL). Actas Españolas De Psiquiatria, 34, 36–40.

Vaidya, C. J., & Stollstorff, M. (2008). Cognitive neuroscience of attention deficithyperactivity disorder: Current status and working hypotheses. DevelopmentalDisabilities Research Reviews, 14, 261–267.

van Mourik, R., Oosterlaan, J., Heslenfeld, D. J., Konig, C. E., & Sergeant, J. A. (2007).When distraction is not distracting: A behavioral and ERP study on distractionin ADHD. Clinical Neurophysiology, 118, 1855–1865.

Van Strien, J. W., Glimmerveen, J. C., Franken, I. H., Martens, V. E., & de Bruin, E. A.(2011). Age-related differences in brain electrical activity during extendedcontinuous face recognition in younger children, older children and adults.Developmental Science, 14, 1107–1118.

van Veen, V., & Carter, C. S. (2002). The timing of action-monitoring processes in theanterior cingulate cortex. Journal of Cognitive Neuroscience, 14, 593–602.

Verlerger, R. (1998). Event-related potentials and cognition: A critique of thecontext updating hypothesis and an alternative interpretation of P3. BehavioralBrain Science, 11, 343–356.

Vuilleumier, P. (2005). How brains beware: Neural mechanisms of emotionalattention. Trends in Cognitive Sciences, 9, 585–594.

Vuilleumier, P., & Schwartz, S. (2001). Emotional facial expressions captureattention. Neurology, 56, 153–158.

Whalen, P. J., Rauch, S. L., Etcoff, N. L., McInerney, S. C., Lee, M. B., & Jenike, M. A.(1998). Masked presentations of emotional facial expressions modulateamygdala activity without explicit knowledge. Journal of Neuroscience, 18,411–418.

Willcutt, E. G., Doyle, A. E., Nigg, J. T., Faraone, S. V., & Pennigton, B. F. (2005).Validity of the executive function theory of attention deficit/hyperactivitydisorder: A meta-analytic review. Biological Psychiatry, 57, 1336–1346.