Neuroscience 241 (2013) 135146EEG ANOMALIES IN ADULT ADHD SUBJECTS PERFORMINGA WORKING MEMORY TASKP. MISSONNIER, a,b* R. HASLER, c N. PERROUD, d

F. R. HERRMANN, e P. MILLET, a J. RICHIARDI, f,g

A. MALAFOSSE, c,d P. GIANNAKOPOULOS b ANDP. BAUD b

aClinical Neurophysiology and Neuroimaging Unit, Division of

Neuropsychiatry, Department of Psychiatry, University Hospitals

of Geneva, Geneva, Switzerland

bDivision of General Psychiatry, Department of Mental Health

and Psychiatry, University Hospitals of Geneva, Geneva, Switzerland

cDepartment of Genetics and Laboratory, University Hospitals

of Geneva, Geneva, Switzerland

dDepartment of Psychiatry, School of Medicine, University

of Geneva, Geneva, Switzerland

eDepartment of Internal Medicine, Rehabilitation and

Geriatrics, University Hospitals of Geneva, Geneva, Switzerland

fMedical Image Processing Lab, Ecole Polytechnique Federale

de Lausanne, SwitzerlandgMedical Image Processing Lab, University of Geneva, SwitzerlandAbstractFunctional imaging studies have revealed differ-

ential brain activation patterns in attention deficit hyperac-

tivity disorder (ADHD) adult patients performing working

memory (WM) tasks. The existence of alterations in WM-

related cortical circuits during childhood may precede exec-

utive dysfunctions in this disorder in adults. To date, there

is no study exploring the electrophysiological activation of

WM-related neural networks in ADHD. To address this issue,

we carried out an electroencephalographic (EEG) activation

study associated with timefrequency (TF) analysis in 15

adults with ADHD and 15 controls performing two visual

N-back WM tasks, as well as oddball detection and passive

fixation tasks. Frontal transient (phasic) theta event-related

synchronization (ERS, 0500 msec) was significantly

reduced in ADHD as compared to control subjects. Such

reduction was equally present in a task-independent man-

ner. In contrast, the power of the later sustained (5001200 msec) theta ERS for all tasks was comparable in ADHD

and control groups. In active WM tasks, ADHD patients dis-

played lower alpha event-related desynchronization (ERD,

200900 msec) and higher subsequent alpha ERS (9002400 msec) compared to controls. The time course of alpha

ERD/ERS cycle was modified in ADHD patients compared to

controls, suggesting that they are able to use late compen-0306-4522/13 $36.00 2013 IBRO. Published by Elsevier Ltd. All rights reservehttp://dx.doi.org/10.1016/j.neuroscience.2013.03.011

*Corresponding author. Address: Department of Medicine, Ch. duMusee 5, CH-1700 Fribourg, Switzerland. Tel: +41-026-300-94-32;fax: +41-26-300-97-31.

E-mail address: Pascal.missonnier@unifr.ch (P. Missonnier).Abbreviations: ADHD, attention deficit hyperactivity disorder; EF,executive functions; ERD, event-related desynchronization; ERP,event-related potentials; ERS, event-related synchronization; ERSP,event-related spectral perturbations; fMRI, functional magneticresonance imaging; MMSE, Mini Mental State Examination; RT,reaction time; TF, timefrequency; WM, working memory.

135satory mechanisms in order to perform this WM task. These

findings support the idea of an ADHD-related dysfunction of

neural generators sub-serving attention directed to the

incoming visual information. ADHD cases may successfully

face WM needs depending on the preservation of sustained

theta ERS and prolonged increase of alpha ERS at later

post-stimulus time points. 2013 IBRO. Published by Else-vier Ltd. All rights reserved.

Key words: attention deficit hyperactivity disorder, electro-

encephalography, event-related potential, event-related spec-

tral changes or perturbations.

INTRODUCTION

Attention deficit hyperactivity disorder (ADHD) is aneuropsychiatric condition emerging during childhoodand often persisting into adulthood. Its prevalence ingeneral adult populations has been estimated between3.4% and 4.4% (Kessler et al., 2006; Fayyad et al.,2007). In adults, the disorder is characterized by avariety of symptoms encompassing distractibility anddifficulties sustaining attention, impulsiveness, andhyperactivity often experienced as a subjective feelingof inner restlessness.

Adults diagnosed with ADHD commonly exhibit a widerange of neuropsychological deficits, with impairments insustained attention, behavioral inhibition and workingmemory (WM) being particularly salient (Hervey et al.,2004; Seidman, 2006). A meta-analysis of differentmeasures of executive functions (EF) in children withADHD found that response inhibition, vigilance, WM andplanning were mostly impaired (Willcutt et al., 2005).Moreover, verbal and visuo-spatial WM deficits havebeen shown to confer higher risks of occupational andacademic underachievement in adults with ADHD(Biederman et al., 2006; Marchetta et al., 2008; Barkley,2010). Interestingly, three functional imaging studieshave revealed differential activation of WM-related brainareas in ADHD patients even in the presence ofpreserved WM performances. A functional magneticresonance imaging (fMRI) study found different patternsof neural activity in the cerebellar and occipital regions,and to a lesser extent in the prefrontal cortex, of ADHDand control adults performing a 2-back verbal WM task,despite comparable behavioral results (Valera et al.,2005). Investigation with an optical imaging methodrevealed reduced activation of the ventrolateral-prefrontal cortex during performance of a WM (N-back)paradigm in adult ADHD patients (Ehlis et al., 2008). Ind.

http://dx.doi.org/10.1016/j.neuroscience.2013.03.011mailto:Pascal.missonnier@unifr.chhttp://dx.doi.org/10.1016/j.neuroscience.2013.03.011

Table 1B. Clinical characteristics of patients with attention-deficit/

hyperactivity disorder (N = 15)

ADHD Subtypesa

Inattentive 5/15

Hyperactive/impulsive 1/15

Combined 9/15

Symptom score, mean

WURS, total sum meanb 41.9 (6.7)

ASRS, total sum meanc 49.1 (6.9)

136 P. Missonnier et al. / Neuroscience 241 (2013) 135146the same line, a recent fMRI study suggested that WMability in young adults with ADHD might be related tothe attentional modulation of the left dorsolateralprefrontal cortex (Burgess et al., 2010). These firstobservations suggest the existence of early alterationsin WM-related cortical circuits that may precedeexecutive dysfunction and represent trait markers of thedisease.

Despite its excellent spatial resolution, fMRI cannotexplore with a sufficient temporal resolution brainactivation patterns during sensory and cognitiveprocesses occurring in short time ranges (hundreds ofmilliseconds). Electrophysiological approaches thatmake it possible to investigate the rapid recruitment ofneural generators remain the more sensitive method inthis respect. Recent studies described several changesof endogenous event-related potentials (ERPs) during aclassical N-back verbal WM task (McEvoy et al., 1998,2001; Missonnier et al., 2003). Particularly, in younghealthy individuals, these investigations led to theidentification of a new ERP component mainly locatedon the parietal cortex. Physiologically, this load-dependent component generates a shift in the latenciesof P200 and N200 components that represents earlyencoding and retrieval phases of WM processingfollowing pure sensory driven processes. This latteroccurs in the 0150 ms after stimulus onset and isreflected by a series of exogenous (i.e., related tophysical characteristics of stimulus) ERP components(such as the P1 and the N1; Cowan 1984, 1995) mainlypredominant in occipital areas for visual stimuli. In termsof brain rhythms, WM load-related increase in frontaltheta amplitude has been reported using task-relatedpower or timefrequency (TF) analyses (see for areview Mitchell et al., 2008). The temporal dynamics oftheta and alpha activity during WM N-back tasks werealso examined by applying the event-relatedsynchronization (ERS) and desynchronization (ERD)analysis procedure (Pfurtscheller, 1992, 2001). A largetheta ERS amplitude was observed over frontal siteswith the highest WM task (2-back), suggesting thatsustained frontal theta synchronization could be anindex of the late phase of WM processes. In contrast,alpha activity was mainly related to early attentionprocesses (Klimesch et al., 2007).

To date, no study examined theelectroencephalography (EEG) patterns associated withWM activation in adult ADHD. In particular, it is unclearwhether early deficits of neural generators related toTable 1A. Demographic characteristics of controls (N= 15) and

patients with attention-deficit/hyperactivity disorder (N = 15)

Variable Controls Patients

Age (years) 32.3 (6.0) 34.3 (5.8)

Gender (f/m) 6/9 3/12

Exclusionsa 2 4

Data are presented as mean (SD).a Major artifacts related to muscular activity and/or eye movements (n= 2),

skin impedance above 5 KOhms (n= 3) and EEG signal contamination from

sector (n= 1) were present. The excluded subjects were not included in the final

sample (n= 30) analyzed in the present study.sensory driven process, attentional control and pureWM processing may be detected in these patients. Toaddress this issue we carried out an EEG activationstudy associated with TF analysis in adult ADHDpatients and healthy controls successfully performing aN-back WM task.EXPERIMENTAL PROCEDURES

Participants

Fifteen adult ADHD patients (3 women, 12 men; mean age 34.3(5.8 SD) years, age-range 2640) were recruited in thespecialized program for adult ADHD of the Department ofMental Health and Psychiatry of the University Hospitals ofGeneva, Geneva, Switzerland (Table 1A). At inclusion, allsubjects were diagnosed as ADHD based on the clinicalevaluation made independently by two trained psychiatrists.The presence of other DSM-IV Axis I diagnoses was assessedusing the French version of the Diagnostic Interview for GeneticStudies (DIGS), a semi-structured interview including a detailedinvestigation of childhood ADHD (age at onset, DSM-IV criteriafor inattention and hyperactivityimpulsivity) and its persistenceinto adulthood (Preisig et al., 1999). All diagnoses wereconfirmed by a best estimate procedure. Clinical historyrevealed that all of the patients included in the study had a fullADHD syndrome present since childhood. Some of them hadalso lifetime psychiatric comorbidities (Table 1B). However,none of them presented with acute symptoms of DSM-IV Axis Iconditions at the time of the EEG investigation (see Table 1B).All subjects also filled out the Adult Self-Report Scale symptomchecklist (ASRS-1.1) (Adler et al., 2006), which consists of 18items exploring present ADHD symptoms, and the Frenchversion of the Wender Utah Rating Scale (Bayle et al., 2003), a61-items questionnaire aiming at retrospectively establishingthe childhood diagnosis of ADHD. Subjects performed anadditional battery of ADHD-oriented neuropsychological tests(Table 2A) including Digit Span Forward (Wechsler, 1955) andBuschke Double Memory 48 items (Buschke et al., 1997) formemory, Trail Making Test part A and B (Reitan, 1958),Wisconsin card sorting (Heaton, 1981) and the adapted(Strauss et al., 2006) Stroop color-word (Stroop, 1935) test forLifetime psychiatric comorbiditiesd

MDD 47%

BD 20%

AD 27%

Past Drug Dependence 27%

Abbreviations: AD, anxiety disorders; ADHD, attention-deficit/hyperactivity dis-

order; ASRS, ADHD Self-Report Rating Scale; BD, bipolar disorder; MDD, major

depressive disorder; WURS, Wender Utah Rating Scale.a ADHD is diagnosed according to the Diagnostic and Statistical Manual of

Mental Disorders, 4th edition, text revision (DSM-IV-TR criteria).b Score range, 0 to 100.c Score range, 0 to 72.d Score range, 0 to 63.

Table 2A. Neuropsychological data in the present series for patients

with attention-deficit/hyperactivity disorder (n = 15) and values

(Norms) adjusted for age from reference population for each test

Characteristics Patients Norms

Executive functions

TMT A&B (ratio) 61.00 (24.70) 96.00 (12.80)

Wisconsin 6.00 (0.80) 5.10 (1.10)

Stroop color-word test (ratio) 1.70 (0.41) 2.25 (0.75)

Attention

Conners CPT-II

Inattention 68.00 (18.4) [40; 60]

Impulsivity 57.00 (13.3) [40; 60]

Memory tests

Digit Span Forward 5.80 (1.10) 6.51 (1.20)

Buschke Double Memory Test (Buschke 48)

Rec tot 27.96 (7.10) 28.07 (4.80)

RI 39.80 (4.10) 42.50 (3.20)

Int 3.80 (2.50) 2.30 (1.30)

Data are presented as mean (SD). TMT= Trail Making Test part A and B

(processing speed, in sec); Wisconsin: number of completed categories (out of 6);

Conners CPT-II data are presented as T-Score; Rec tot, recall total; RI, recall

immediate; Int, intrusions. See text for details.

Table 2B. Neuropsychological data in the present series for controls

(n = 15)

Characteristics Mean (SD)

Global tests

MMSE 29.78 (0.46)

DRS 25.00

Executives function

Verbal Fluency 23.33 (4.82)

Trail Making Test B (sec) 41.56 (13.23)

Language abilities

Boston Naming Test 20.00

Standardized praxis

Ideomotor praxies 5.00

Reflexive praxies 5.00

Constructional praxies 10.00

Gnosis

Ghent Overlapping Figures Test 4.00

Attention

WAIS-R; Code 12.22 (3.53)

Trail Making Test A (sec) 24.88 (9.34)

Memory tests

Digit Span Forward 9.00 (1.58)

Buschke Double Memory Test (16 items)

RL tot 29.78 (0.44)

RI tot 3.90 (6.14)

Rec 16.00

RDL 15.22 (1.30)

RDI 0.67 (1.12)

Shapes test 36.00

Differed recall shapes 12.00

Notes: Data are presented as mean (SD). MMSE, Mnini-Mental State Examina-

tion; DRS, Mattis Dementia Rating Scale; WAIS-R, Weshler adult intelligence

scale, revised; FR tot, free recall total; CR tot, cued recall total; Rec, recognition;

LTR, long-term recall; LTCR, long-term cued recall. See text for details.

P. Missonnier et al. / Neuroscience 241 (2013) 135146 137EF. Inattention and impulsivity were rated according to thesecond version of the CPT (CPT-II V.5) paradigm (Conners,2004). All patients were treated with methylphenidate andstopped their medication 48 h before EEG recording.A group of healthy controls without history of sustained head

injury or other neurologic disorders was also recruited (6 women,9 men; mean age: 32.3 5.97 SD). This control group includedparticipants without current or past psychiatric disorder and anysubjective complaint of ADHD who participated in a previousEEG study (Missonnier et al., 2012). Control data wereobtained during the same time period and with identicalsettings as the ADHD data. All individuals were screened withan extensive neuropsychological battery (Table 2B) includingthe Mini Mental State Examination (MMSE) (Folstein et al.,1975) and Mattis Dementia Rating Scale items (Gardner et al.,1981) for global assessment, Verbal Fluency Test (Butterset al., 1987) and the Trail Making Test B (Reitan, 1958) for EF,Boston Naming Test (Kaplan et al., 1983) for language abilities,a standardized praxis examination including ideomotor praxis(Schnider et al., 1997), reflexive praxis (Poeck, 1985)constructional praxis, Ghents Overlapping Figures Test (Ghent,1956) for gnosis abilities, Trail Making Test A (Reitan, 1958)and digit symbol test (Wechsler, 1981) for attention, Digit SpanForward (Wechsler, 1955), and French adaptation (Van derLinden et al., 1999) of the Buschke Double Memory Test(Buschke et al., 1997) for memory, as well as the Shapes Testand the differed recall shapes Test (Baddeley et al., 1994).

Control as well as ADHD participants had high school oruniversity degree and had normal or corrected-to-normal visualacuity. Their socio-educational level was comparable to that ofcontrols. Subsequently, no IQ assessment was performed inour ADHD patients. Current substance abuse, activeneurological disorders, history of sustained head injury as wellas the use of neuroleptics, antidepressants, benzodiazepinesand beta-blockers were exclusion criteria for both groups. TheEthics Committee of the University Hospitals of Genevaapproved the study. All participants gave informed writtenconsent.Experimental design

The subjects, comfortably seated, watched a computer-controlled display screen at a distance of 57 cm. They viewedpseudo-random sequences of consonants and vowels commonto the French language, and pressed a computer-controlledbutton with their right index finger as soon as a target appeared(response trials). For non-target stimuli, no motor response wasrequired (no-response trials). Targets were defined eitheraccording to the oddball (rare event) or to the N-back design.The size of the screen was 51 cm and stimuli consisted ofwhite letters, Arial font (2 2.5 visual angle), with 10% graynoise, embedded in a 50% random noise gray rectangularbackground patch (6 6.7 visual angle). They werepresented for a duration of 0.5 sec, separated by 5-secintervals (onset to onset) during which a dot helped subjectsmaintain fixation. In addition subjects were instructed to remainquiet and to only move their right index finger in accordancewith the nature of the task in order to minimize muscle artifacts.

Three active tasks were tested, in which stimuli were dividedbetween target with (1/3) and without motor-responses(respectively, 1/3 and 2/3 of stimuli in a sequence) (Fig. 1). Inthe detection task, sequential letters (no-response trials) orbackground patches without letters (response trials) werepresented. In the N-back tasks, all stimuli were sequentialletters. In the 1-back task, the target was any letter identical tothe one immediately preceding it. In the 2-back task, the targetwas any letter identical to the one presented two trials back.The oddball detection task was attention-related (memory free),while the N-back tasks involved the comparison of stimulus-related information with memory contents (for information onthis task, see Braver et al., 1997; Smith and Jonides, 1997;Nystrom et al., 2000; Fletcher and Henson, 2001). WM loadincreased from 1-back (moderately demanding) to 2-back

Fig. 1. Schematic representation of the four tasks included in this experimental setting. In the passive fixation task, letter series identical to the 2-back working memory task are presented, but the subject receives no instruction about the nature of the task. In the detection task, the subject mustpress a pushbutton as soon as a background patch without letters is presented. In the 1-back and 2-back tasks, the subject must decide whether theletter is identical to the one presented one trial back (1-back task) or two trials back (2-back task). Stimulus duration = 500 ms, interstimulus interval(ISI) = 5 s.

138 P. Missonnier et al. / Neuroscience 241 (2013) 135146(highly demanding) task. At the beginning of the recordingsession, an additional passive task was performed to control forvisual effects: letter series identical to the 2-back task werepresented with the instruction to passively watch the series.Each task was tested in three blocks (blocks 1, 2, 3) composedof 30 sequential stimuli, adding up to 90 trials per task (activetasks: 21 response trials, 69 no-response trials). Subjects werekept informed of the nature of the forthcoming task right beforeeach sequence. Task order presentation was chosen both forminimizing brain fatigue and optimizing the allocation ofattentional resources in ADHD patients: passive task (blocks 1,2, 3); detection (block 1); 1-back (block 1); 2-back (blocks 1, 2,3); 1-back (blocks 2, 3); detection (blocks 2, 3). The duration ofexperimental design approximated 30 min. Reaction time (RT)and performance were systematically recorded, but nofeedback on performance was provided. Learning, habituation,and fatigue effects were minimal during the recording session,as indicated by the absence of any difference in RT andperformance between blocks of the same task.Electrophysiological assessments were performed in themorning.Electrophysiological recordings

Continuous EEG (Micromed, Brain Quick system 98, Treviso,Italy) was recorded using 20 surface electrodes referenced tothe linked earlobes. Their locations, according to the 1020international system, were: Fp1, Fp2, F7, F3, Fz, F4, F8, T3,C3, Cz, C4, T4, T5, P3, Pz, P4, T6, O1, Oz, and O2. Skinimpedance was kept below 5 kO. Electrophysiological signalswere sampled at 1024 Hz with a lower cutoff of 0.3 Hz (DCamplifiers; Micromed). The electrooculogram was recordedusing two pairs of bipolar electrodes in both vertical andhorizontal directions. Single transistortransistor logic (TTL)pulses synchronized with stimulus onset were recorded andused off-line to segment the continuous EEG data into epochstime-locked to stimulus onset.Data processing

Using BrainVision Analyzer 2 software (Brain Products GmbH,Munich, Germany), EEG signals were corrected for blinks andeye movement artifacts through an independent componentanalysis (ICA) (Jung et al., 2000), whose parameters werecarefully selected in each individual to minimize any residualeffects on the visually inspected EEG signal. The total analysiswindow was 5500 ms, starting 2000 ms before stimulus onset.Spatial resolution of EEG data was enhanced by surfaceLaplacian estimation performed on continuous EEG(regularized 3D spline function, order 4). Such Laplaciancalculation acts as a high-pass spatial filter that reduces headvolume conduction and cancels out reference electrodeinfluence (Perrin et al., 1987; Babiloni et al., 1996) and,therefore, provides EEG topographies with more sharply

P. Missonnier et al. / Neuroscience 241 (2013) 135146 139localized peaks than those of scalp potential (Nunez et al., 1994;Tenke and Kayser, 2005; Nunez and Srinivasan, 2006). Allsubsequent analysis was performed on the Laplacian-transformed EEG signal (lV/m2) computed at each electrode.Then, the Laplacian-transformed EEG trials were automaticallyscanned for contamination by muscular or electrode artifacts(criteria for rejection: voltage step > 50 lV/msec or peak-to-peak deflection within 300-msec intervals > 200 lV/msec) andthe remaining trials were inspected visually to control forresidual minor artifacts. In order to eliminate effects frommanual responses and exclude the confounding effect of motorprocessing, only data with correct answers from no-motorresponse trials were analyzed according to the task condition(passive, detection, 1- and 2-back). For controls, the averagenumber of artifact-free epochs was 48.28 14.25,49.26 19.42, 51.09 18.26 and 47.37 11.46 in passive,detection, 1- and 2-back tasks, respectively. Similar number ofepochs was obtained for ADHD patients (46.94 13.68,45.89 15.04, 45.19 17.36 and 46.68 17.91,respectively). There were no significant group (p= 0.49), task(p= 0.874) or group-task (p= 0.998) interaction effects on thenumber of accepted trials. The EEG data were analyzed with 2different types of electrophysiological analyses: ERPs andevent-related spectral/changes perturbations (ERSPs).

Event-related potentials (ERPs)

ERP analyses were performed by averaging the EEG signal overa window of 500 msec with a 200-msec pre-stimulus onset, andthey were band-pass filtered between 0.5 and 30 Hz (48 dB/octave for a low-pass filter). ERPs were averaged with a 200-msec baseline epoch prior to stimulus onset. In order toinvestigate the integrity of visual information processing inADHD subjects, we examined the exogenous ERPs related tosensory treatment (mainly predominant in occipital areas forvisual stimuli). The ERP components of interest were P1,largest occipital positive deflection between 75 and 150 ms,and N1, largest occipital negative deflection between 110 and220 msec. Both P1 and N1 ERP components were identified onoccipital electrode sites (O1, Oz and O2 electrode combined) inthe grand-average waveforms (implemented in BrainVisionAnalyzer 2 software, Brain Products GmbH, Munich, Germany).To explore working-memory-related ERPs, the P2 and N2components, analyses were restricted to the anterior (FzCz)electrode locations, and these sites were thus selected andaveraged for the latency measurements. Latencies of the ERPcomponents were measured from stimulus onset to the time ofmaximum peak, and their amplitudes were measured from thepre-stimulus baseline to the maximum peak.

Event-related spectral perturbations (ERSPs)

The event-related power modulation spectral across time wasassessed over a window of 5500 msec with a 2000-msec pre-stimulus onset using the EEGLAB v10.2.5.5b toolbox (Delormeand Makeig, 2004) under MATLAB v7.04 (Mathworks, Natick,MA). Trial by-trial event-related spectral power changes wereanalyzed by the ERSP index (Delorme and Makeig, 2004). Forn trials, ERSP give the mean Fk(f,t), which is the spectralestimate of trial k at frequency f and time t. Fk(f,t) wascomputed using a hanning-tapered sinusoidal wavelet (short-time DFT) transform with linearly increased cycles, from twocycles for the lowest frequency (2 Hz) to 15 cycles for thehighest frequency (30 Hz) analyzed (step size, 0.5 Hz) withinone analysis window. Individual subjects ERSP results werebaseline-normalized by subtracting the mean baseline logpower spectrum from each spectral estimate and thresholdedby applying a significance threshold of p< 0.01. To avoid anyprobability distribution assumption, bootstrap statistics wereapplied comparing the data distributions against bootstrapdistributions that had been drawn at random from the pre-stimulus baseline (1500 to 500 msec) and applied 200 times(Delorme and Makeig, 2004). This method allows for visualizingsignificant deviations from baseline random fluctuationsfollowing stimulus onset.

According to the ERSP pattern for each participant, therewere two different timefrequency intervals with increasedspectral power and another interval with decreased spectralpower over frontal regions of interest (F3, Fz and F4 electrodecombined). An early significant increase from baseline in EEGspectral power (synchronization) was found in both groupsbetween approximately 0500 msec after the stimulus onset inthe 47 Hz (theta) frequency range (phasic theta ERS) (Fig. 3).Following this phasic theta ERS, a rapid development ofsustained theta synchronization occurs during the 5001200-msec time interval after stimulus onset for active tasks infrontal electrode locations (Missonnier et al., 2006; Deiberet al., 2007). From approximately 2001200 msec after thestimulus onset in controls and patients, a decreased spectralpower occurred in the 915-Hz frequency range thatcorresponds to boundaries of upper alpha and beta1 rhythms.This desynchronization was followed by a short synchronizationfor the control group in active tasks, while alpha/betadesynchronization in the 915 Hz range was longer for thepatients (8003000-msec time interval).

Four time-frequency windows within the following time andfrequency ranges were analyzed within frontal region of interest(F3, Fz and F4 electrode combined): 0500 msec and 5001200 msec in 47 (theta) Hz, 200900 msec and 9002400 msec in 915 (alpha) Hz. To compare groups andconditions, ERSP values were averaged across trials and TFpoints separately for each subject. The individual mean valueswithin each interval of interest were extracted with a region ofinterest procedure using custom MATLAB (MathWorks) scripts.Statistical analysis

Demographic (age and gender) characteristics as well asdifferences in performances between the two groups wereassessed using Student t, MannWhitney u or chi square testswhen appropriate.

First we performed only non-parametric statistical tests onnative values. Friedman non-parametric two-way analysis ofvariance was used to assess the existence of a task effect(passive, detection, 1-back, 2 back) in each group while takinginto account the repeated measure design. Wilcoxon matched-pairs signed-ranks test was subsequently used to detect task-related differences in EEG measures, with a P-value thresholdfor significance adjusted using the Bonferroni correction (i.e.p= 0.0042 = 0.05/12 repetitions: 2 groups and 6 variables).Then, we verified the normality of data distribution with theShapiroFrancia tests and applied the following transformation:reaction time (1/x), reaction-variability (1/x1/2); performance andP1 amplitude (x3); N1 amplitude, N2 latency, phasic andsustained theta power, and desynchronizationsynchronizationalpha power (x2); P1 and N1 latency (natural logarithm). Aftertransformation, all of these variables were normally distributed.We also computed the coefficient of variation (CV) of reactiontime by dividing the standard deviation by the mean of eachsubject. Group (controls vs. ADHD patients), task condition(passive, detection, 1-back, 2-back), and a group by taskinteraction term were included as independent variables in arepeated analysis of covariance (ANCOVA) to analyze theirrespective influence on each of the normalized dependentvariables (reaction time and its coefficient of variation,performance and EEG measures) while adjusting foreducational level. Group was the between-subject factor,education considered as continuous variable, and taskcondition was treated as a within-subject factor. Thesignificance values of the repeated factors in the ANCOVA

140 P. Missonnier et al. / Neuroscience 241 (2013) 135146were determined using Boxs conservative epsilon. The statisticalthreshold was set at p< 0.05. All statistical analyses wereperformed using the Stata software package, version 12.1.

RESULTS

Demographical data

There was a non-significant group effect on age(z= 1.736, p= 0.0825) in the present series. Genderscores were also comparable among groups (Pearsonchi2(1) = 0.56, p= 0.464).

Behavioral results

ADHD patients performed well in the three active tasks,and responded correctly to more than 96% of the trials(Table 3). After adjusting for age, performance wasrelated to task difficulty [(F(2, 27) = 16.43, p= 0.001;Table 3)] but neither group effect nor a group and taskinteraction were observed. Although performances forthe control and 1-back tasks did not differ significantly,all subjects performed significantly worse in the 2-backtask (regression analysis coefficient task: b = 74032.65,p= 0.001 compared to the 1-back; b = 77340.06;p< 0.001 compared to detection). The task difficultyhad significant effect on performance in controls(Friedman test = 9.905, p= 0.0075) and ADHDsubjects (Friedman test = 14.170, p= 0.001).

As expected, reaction times increased with taskdifficulty [(F(2, 27) = 3.36, p= 0.0498)], being shorterin the detection task, intermediate in the 1-back taskand longer in the 2-back task. However, after adjustingfor age, this effect was restricted to the 2-back condition(regression analysis coefficient task: b = 0.00023;p= 0.001 compared to 1-back; b = 0.00031;p< 0.0001 compared to detection) in both groups. Thistask effect was in fact observed both for controls(Friedman test = 35.567, p= 0.0012) and ADHDpatients (Friedman test = 33.867, p= 0.0022). Nogroup effect or group and task interaction was observed.

The coefficient of variation of reaction times increasedwith task difficulty [(F(2, 27) = 17.92; p= 0.0009;Table 3)] being shorter in the detection and 1-back taskTable 3. Reaction times [msec], coefficient of variation [SD/mean] of reaction tim

controls (n = 15) and patients with ADHD (n = 15)

Reaction time, mean (SD) msec Coefficie

Controls Patients Controls

Task

Detection 669.46 (173.07) 682.62 (169.45) 2.75 (0.5

1-back 702.89 (178.82) 720.73 (191.37) 1.90 (0.4

2-back 824.06 (186.64) 872.45 (257.47) 2.64 (0.6

Statistics

Group effect F(1, 27) = 0.17 p= 0.685 F(1, 27) =

Task effect F(2, 27) = 3.36 p< 0.050 F(2, 27) =

Group x Task Interaction F(2, 27) = 0.03 p= 0.966 F(2, 27) =

Average reaction times were related to task difficulty [(F(2, 56) = 3.36, p< 0.05]. Comp

(p< 0.001) and controls (p< 0.01). Coefficient of variation [SD/mean] of reaction times

this effect was present in detection and 1-back tasks for patients (p< 0.01) and con

p< 0.001]; this effect was restricted to the 2-back task (p< 0.01). The p values for wit

deviation.but longer in the 2-back task. Neither group effect norgroup and task interaction was observed.Event-related potentials (ERPs)Exogenous ERP components. In Fig. 2A, ERPwaveforms were plotted over the occipital region foreach participant. As expected, the visual stimuli eliciteddistinct occipital positivenegative complex responses atabout 100 msec and 145 msec after stimulus onset.These components were observed for all four tasks(passive, detection, 1-back and 2-back). After adjustingfor age, their latency was free from group-, task- orinteraction group and task-related effects (Table 4).Similarly, there was no group-, task- or interaction groupand task-related effect on P1 and N1 amplitudes. Notask nor interaction between group and task wasobserved.Endogenous ERP components. For each task,analysis of averaged ERPs revealed a series of ERPpeaks (P200 and N200) over anterior regions in bothgroups (Fig. 2B). P200 and N200 latencies weremodulated by task [(P200, F(3, 27) = 3.29, p= 0.036;N200, F(3, 27) = 13.37; p= 0.005)]. P200 latency wasshorter in the 2-back compared to the detection andpassive tasks (p= 0.001); it was also shorter in the 1-back compared to the detection (p= 0.001) andpassive tasks (p= 0.03). N200 latency was shortest inthe 2-back, followed by 1-back (p= 0.01), detection(p= 0.01) and passive tasks (p= 0.001). Unlike P200latency, a significant group effect was found for N200latency [(F1, 27 = 5.95, p= 0.022)]. No two-wayinteractions between factors were observed for thesetwo ERP components.

The P2 amplitude was significantly higher in controlscompared to ADHD patients [F(1, 27) = 6.02;p= 0.021], but no task nor interaction between groupand task was observed. In contrast, the N2 amplitudewas free from group-, task- or interaction-related effects(Table 5).es and performances [%] for the detection, 1-back and 2-back tasks in

nt of variation, (SD/mean) msec Performances, mean (SD)%

Patients Controls Patients

1) 2.57 (0.28) 99.63 (0.69) 99.15 (2.85)

1) 2.21 (0.56) 99.19 (1.07) 99.09 (1.37)

5) 3.06 (0.60) 97.11 (2.58) 96.46 (2.67)

1.19 p= 0.285 F(1, 27) = 0.92 p= 0.347

17.92 p< 0.001 F(2, 27) = 16.43 p< 0.001

2.28 p= 0.154 F(2, 27) = 0.15 p= 0.859

ared to 2-back, this effect was present in detection and 1-back tasks in patients

was related to task difficulty (F(2, 56) = 17.92; p< 0.001). Compared to 2-back,

trols (p< 0.02). Performance was related to task difficulty [(F(2, 56) = 16.43,

hin-subject effects were calculated using Boxs correction factor. SD = standard

Patients with ADHD

Time [ms]-100 0 100 200 300 400

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Fig. 2. (A) Grand average event-related potentials (ERPs) at occipital electrode sites (O1, Oz and O2 combined) for the passive, detection, 1-backand 2-back tasks averaged over no-motor response trials for controls and patients. (B) Grand average ERP waveform at anterior electrode sites (Fzand Cz combined for the four experimental tasks, averaged over no-motor response trials for controls and patients. Note the shorter P2 and N2 ERPlatencies in N-back tasks compared to detection and passive tasks for both controls and patients.

Table 4. Early and late sensory ERP amplitude (lV/m2) and latencies [msec] (standard deviations [SD] measured on passive, detection, 1- and 2-backtasks recorded over occipital electrode locations (O1, Oz and O2 combined) for controls (n = 15) and patients with attention-deficit/hyperactivity

disorder (n = 15)

Tasks P1 amplitude N1 amplitude P1 latency N1 latency

Controls Patients Controls Patients Controls Patients Controls Patients

Passive 5.42 (4.55) 4.50 (5.56) 4.62 (5.92) 1.51 (5.03) 111.67 (19.43) 117.40 (16.15) 174.13 (24.25) 173.33 (19.67)Detection 5.78 (7.64) 4.69 (6.06) 7.19 (7.43) 3.24 (4.75) 113.60 (21.96) 118.07 (15.53) 172.40 (23.42) 169.20 (21.53)1-back 6.54 (5.64) 4.39 (5.15) 5.94 (4.93) 2.38 (5.12) 116.40 (17.18) 113.00 (16.58) 169.93 (21.79) 160.07 (27.42)2-back 6.17 (5.78) 4.41 (4.88) 8.20 (7.73) 3.35 (4.42) 114.20 (16.10) 117.73 (19.36) 169.40 (20.63) 169.07 (28.33)Group effect F(1, 27) = 1.27;

p= 0.270

F(1, 27) = 3.17;

p= 0.086

F(1, 27) = 0.22;

p= 0.642

F(1, 27) = 0.04;

p= 0.277

Task effect F(3, 27) = 0.01;

p= 0.998

F(3, 27) = 0.13;

p= 0.944

F(3, 27) = 0.02;

p= 0.997

F(3, 27) = 0.14;

p= 0.933

Group TaskInteraction

F(3, 27) = 0.10;

p= 0.959

F(3, 27) = 0.49;

p= 0.689

F(3, 27) = 0.19;

p= 0.899

F(3, 27) = 0.02;

p= 0.997

In both groups, latencies and amplitudes of sensory ERP components were not affected by the task difficulty.

P. Missonnier et al. / Neuroscience 241 (2013) 135146 141Timefrequency (TF) results

Theta frequency band. The representation of TFpower averaged across single trials over frontalelectrodes showed a transient power increase in thetheta frequency range (47 Hz) between 0 and500 msec after stimulus onset in both groups for alltasks (Fig. 3). This theta synchronization was reducedin ADHD patients. After adjusting for age, statisticalanalysis revealed a significant group effect on frontal

Table 5. Endogenous ERP amplitude (lV/m2) and latencies [msec] (standard deviations [SD] measured on passive, detection, 1- and 2-back tasksrecorded over occipital electrode locations (O1, Oz and O2 combined) in controls (n = 15) and ADHD patients (n = 15)

Tasks P2 amplitude N2 amplitude P2 latency N2 latency

Controls Patients Controls Patients Controls Patients Controls Patients

Passive 15.42 (7.87) 7.46 (7.33) 4.97 (6.80) 2.88 (5.61) 219.67 (10.70) 218.00 (9.28) 299.80 (18.42) 291.13 (15.95)Detection 7.68 (10.02) 4.90 (7.48) 8.92 (7.72) 1.46 (5.71) 226.00 (16.10) 219.40 (18.82) 285.53 (22.35) 274.87 (18.97)1-back 10.03 (9.61) 5.49 (6.66) 6.61 (10.35) 2.85 (6.42) 214.73 (15.61) 203.27 (22.95) 270.80 (10.03) 253.33 (24.18)2-back 11.61 (8.60) 5.76 (8.42) 5.72 (8.55) 3.06 (3.97) 207.47 (12.52) 203.60 (15.45) 268.73 (15.27) 254.07 (18.65)Group effect F(1, 27) = 6.02;

p= 0.021

F(1, 27) = 2.69;

p= 0.113

F(1, 27) = 1.62;

p= 0.196

F(1, 27) = 5.95;

p= 0.022

Task effect F(3, 27) = 0.76;

p= 0.405

F(3, 27) = 0.40;

p= 0.856

F(3, 27) = 3.29;

p= 0.036

F(3, 27) = 13.17;

p= 0.005

Group Task Interaction

F(3, 27) = 0.19;

p= 0.673

F(3, 27) = 0.53;

p= 0.485

F(3, 27) = 0.16;

p= 0.926

F(3, 27) = 0.10;

p= 0.754

In ADHD patients, P200 and N200 latency was significantly modulated by the difficulty of the task (p= 0.008 and p= 0.01, respectively). Patients displayed a significant

decrease of P200 latency in the 1-back (p= 0.04) and 2-back (p= 0.003) tasks compared to working memory-free tasks. Similar effect was also observed in N2 latency

(p= 0.02 and p= 0.006, respectively).

In controls, P200 and N200 latency was also significantly modulated by the difficulty of the task (p= 0.003). Controls displayed a significant decrease of P200 latency in the

2-back (p= 0.002) task compared to working memory-free tasks and in the 1back compared to detection (p= 0.03) task. Similar to patients, controls also displayed a

significant decrease of N200 latency in the 1-back (p= 0.03) and 2-back (p= 0.02) tasks compared to working memory-free tasks.

Phasic theta power

2-back 1-back Detection Passive20

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Alpha (), 9-15 Hz

Fig. 3. Group average of frontal (F3, Fz and F4 combined) timefrequency modulations during an adapted N-back working memory task for thecontrol (left) and patient (center) group. Significant deviations from the mean baseline corrected (1500 to 500 msec) level are highlighted(p< 0.01), producing negative (cold colors) and positive (warm colors) values. In the theta frequency range (47 Hz), there is a transient (phasic)component (0500 msec) [1] after stimulus onset followed by a sustained component (5001200 msec) [2] in both groups. In the four tasks, there isa decreased alpha power occurring 200 msec after stimulus onset (812 Hz) [3], followed by a long rebound [4] only in the three active tasks.ERSP: event-related spectral perturbations in dB. On the far right, mean amplitudes in responses to passive, detection, 1-back and 2-back tasksover frontal (F3, Fz and F4 combined) electrode location for controls (blue) and patients (red). Error bars represent SE. (For interpretation of thereferences to color in this figure legend, the reader is referred to the web version of this article.)

142 P. Missonnier et al. / Neuroscience 241 (2013) 135146early theta power [(F(1, 27) = 8.50, p= 0.007)], but notask [(F(3, 27) = 0.68, p= 0.495)] effect or interactionbetween group and task (F(3, 27) = 0.01, p= 0.915).As previously described (Deiber et al., 2007; Pesonenet al., 2007), a later sustained power (from 500-msecpost-stimulus onset) was observed in the theta bandduring approximately 700 msec. This sustained thetaoscillatory activity was observed in all active conditionsin both groups. There was no significant group or taskeffect on sustained theta activity, and no significantgroup-task interaction.

Alpha frequency band. In the 916 Hz frequencyrange corresponding to boundaries of lower and upper

P. Missonnier et al. / Neuroscience 241 (2013) 135146 143alpha rhythms, the representation of TF power averagedacross single trials revealed a decrease(desynchronization) at 2001200 msec, followed by asharp increase at 8003000 msec. The early powersuppression, present in both groups and for eachcondition, is consistent with the typical time course ofalpha power decrease in response to the recruitment ofattentional resources. Temporally, controls displayed arapid return to inhibition after a short lasting period ofcortical excitation. This rapid resynchronization can beinterpreted as the readiness to perform a new cognitivetask. In contrast, ADHD subjects exhibited a prolongedresynchronization, inverting the timing duration of alphaERD/ERS for tasks demanding attention. After adjustingfor age and normalizing power with a x2 transform,alpha desynchronization (ERD) amplitude wassignificantly lower in ADHD patients compared to controlparticipants [(F(1, 27) = 14.21, p= 0.001)]. No task[(F(3, 27) = 0.63, p= 0.447)] effect or interactionbetween group and tasks [(F(3, 27) = 0.57, p= 0.471)]were observed (Fig. 3). Following alpha ERD, asustained power increase (synchronization; ERS) wasobserved in both groups for all active tasks during the9002400-msec interval after stimulus onset. In contrastto the ERD, this alpha ERS was significantly higher inADHD patients [(F(1, 27) = 4.71, p= 0.034)]. Neither atask effect [(F(3, 27) = 0.39, p= 0.549)] nor two-wayinteractions between group and tasks were observed[(F(3, 27) = 0.14, p= 0. 720)].DISCUSSION

To our knowledge, this is the first investigation of brainoscillation changes during the successful performanceof an N-back WM task in adults with ADHD. Strengthsof the present study include the use of time-frequencyanalysis of brain oscillations and a careful exclusion ofconcomitant DSM-IV Axis I conditions in adult ADHDsubjects. However, this does not formally preclude apossible influence of past psychiatric comorbidities inthe observed EEG patterns. Moreover, the presentADHD cohort cannot be considered as representative ofthe whole spectrum of ADHD. In contrast to the poorcognitive performances reported in ADHD cases, mostof our ADHD cases obtained high school degrees andhad a socio-educational level comparable to thecontrols. Likewise, a residual effect of methylphenidatecannot be excluded, although it was stopped 48 hoursbefore EEG recordings. The limited number of surfaceelectrodes, although representative of routine clinicalsetting, does not allow for exploring EEG compensationphenomena in cortical areas not usually activated by theN-back task. Finally, the limited number of ADHD casesdoes not make it possible to explore differential EEGpatterns related to clinical subtypes.

As expected, a task-independent transient increase offrontal theta was observed both in controls and ADHDcases during the first 500 msec after the appearance ofthe stimulus. This early frontal theta activity primarilyreflects activation of neural networks involved in theallocation of attention to target stimuli (Missonnier et al.,2006; Deiber et al., 2007; Pesonen et al., 2007).Compared to controls, ADHD subjects showed reducedamplitude of this EEG spectral component, suggestingan impaired activation of neural generators sub-servingattention directed to the incoming visual information.During these initial stages of information processing,control subjects exhibited an increased frontal alphaERD that is thought to allow an enhanced efficiency ofinformation transfer across thalamo-cortical pathwayssubtending active cortical processing (Gruber et al.,2005; Klimesch, 1999; Klimesch et al., 2004; Mitchellet al., 2008; Krause et al., 2000; Babiloni et al., 2004;Suffczynski et al., 2001; Paloyelis et al., 2007; Shawet al., 2007; Greene et al., 2008; Schecklmann et al.,2010, 2012). The decrease of alpha desynchronizationin ADHD patients in all task conditions could reflect thereduction of cortical activation at early post-stimulustime points. In line with this observation, functionalimaging studies revealed significant default activationwithin right parietal, occipital and anterior cingulatecortex, as well as cortico-striato-thalamic networks inyoung adults with ADHD performing attention and WMtasks (Paloyelis et al., 2007; Shaw et al., 2007; Greeneet al., 2008; Schecklmann et al., 2010, 2012).Interestingly, the P1N1 complex latency related toearly and late stages of sensory processing waspreserved in our ADHD patients, indicating a correctintegration of visual information for further cognitiveprocessing. Similarly, P200 and N200 latenciesdecreased as a function of WM load in both groupswithout group task interaction. From aneurophysiological viewpoint, they reflect active storageand retrieval phases of the visual stimulus processingstored in short-term memory. In the presence ofpreserved sensory ERP components, the absence ofgroup differences in endogenous ERP and sustainedtheta ERS strongly support the idea that ADHD patientsactivate in an adapted manner neural networks involvedin memory processes related to target stimuli. Takentogether, these data suggest that the cortical generatorsinvolved in attention processing may be affected duringN-back task performance in ADHD. The absence of taskand group interaction further supports this interpretation.However, our findings partly disagree with thosereported by Keage et al. (2008) who found delayedlatencies of late WM-related ERPs in young ADHDsubjects. As in our study, however, there wereattenuated amplitudes of these ERP components inADHD cases. Two main methodological differences mayexplain this discrepancy. First, the endogenous ERPcomponent (N300 and P450) analyzed in this latterstudy were respectively about 300 msec and 450 msecpost-stimulus. In contrast, the present endogenous ERPcomponents were measured in the 200-300 msec time-window post-stimulus. Second, our observationsconcern WM load-related ERPs, while Keage et al.assessed ERP components relevant to updating WMprocesses. Taken together, the present data support theidea that despite preserved visual processing and WM-related ERP, young adults with ADHD have difficulties in

144 P. Missonnier et al. / Neuroscience 241 (2013) 135146activating the cortical networks involved in the allocationof attentional resources.

ADHD patients showed surprisingly highperformances suggesting that they are able tocompensate the deficient activation of attention-relatedneural generators at early post-stimulus time points. Inline with previous studies (Gomarus et al., 2009a,b),ADHD and control subjects showed an identical profileon sustained theta ERS activity (starting 500 msec post-stimulus), indicating incremental retention andmaintenance of new items for further task requirementsduring N-back task (Pesonen et al., 2007). Importantly,our theta oscillation findings disagree with thosereported by Yordanova et al. (2006), who found anincrease of this parameter in ADHD subjects. Two mainmethodological differences may explain thisdiscrepancy. First, the present observations concerntheta reactivity during the successful performance of anadapted visual N-back WM paradigm, while Yordanovaet al. recorded theta reactivity during attentionalactivation to target and no-target stimuli in an auditorymodality (oddball paradigm). Second, oscillationchanges were calculated by applying the TF analysisprocedure in our study (Pfurtscheller, 1992, 2001),whereas Yordanova et al. decomposed ERPs in time-frequency domains (Morlet wavelet analysis). Mostimportantly, there was an increase of alpha ERSbetween 800 and 3000 msec post-stimulus time pointsin all active N-back conditions in ADHD patients. Thistrend implies that the alteration of attentional processingin ADHD subjects needs under certain circumstances alate compensatory inhibition of neural generators.Temporally, ADHD subjects exhibited a significantprolonged resynchronization, inverting the timingduration of alpha ERD/ERS for tasks demandingattention (Woertz et al., 2004). This suggests that non-relevant cognitive operations still need to be activelysuppressed and that ADHD subjects have to use neuralresources for a longer time in order to successfullyperform the attentional phase of the cognitiveprocessing. In this context, a shorter duration of alphaERD may be an EEG trait marker of inattention, whichis a major ADHD symptom. Likewise, prolonged ERSmay reflect a highly specific top-down inhibitory controlprocess maintained over a longer period of time inADHD subjects. Such dysfunctional top-down regulationis in line with the neurobiological hypothesis proposedby Halperin and Schulz (2006) for explaining thepersistence of ADHD in adulthood. According to thismodel, adult ADHD is a two-step neurodevelopmentaldisorder where sub-cortical neuronal dysfunctionspresent early in life and relatively stable throughout thelifespan are not efficiently compensated by laterprefrontal cortical development.CONCLUSION

Adults with ADHD performing successfully a WMactivation task showed changes in theta and alpharhythm patterns both at early and late post-stimulus timepoints when compared to controls. Physiologically,these changes did not concern sensory processing andWM activation per se and but most probably linked tothe attentional neural networks. The final success of thecognitive processing is based on the preservation ofsustained theta ERS and prolonged increase of alphaERS at later post-stimulus time points. Whether thesemechanisms would still be efficient with more difficultWM tasks is still unknown. Studies with largerpopulations using various WM paradigms and combiningEEG (ERP and ERSP) and functional imaging areneeded to elucidate whether the earlyneurophysiological anomalies described here areaccompanied by subtle metabolic changes within thefrontal cortex and elucidate the compensatorymechanisms that are bringing into play in adult ADHDsubjects.

DECLARATION OF INTEREST

None to declare.

CONTRIBUTORS

Missonnier P has contributed in the conception anddesign, in the analysis, in the interpretation of data, indrafting the article and in its revising. Hasler R hascontributed in the recruiting, recordings and in theinterpretation of data, to revising the paper and finalapproval of the version to be published. Millet P andHerrmann F-R contributed to the design of the paper, tothe analyses of the data, to revising the paper and finalapproval of the version to be published. Richiardi Jcontributed to the development of the analyses of thedata, to revising the paper and final approval of theversion to be published. Baud P and Perroud Ncontributed to the recruiting and characterization ofpatients, to the drafting and revising of the article and tothe final approval of the version to be published.Malafosse A and Giannakopoulos P contributed to therecruiting, characterization, conception and design ofthe study, to the drafting and revising of the article andto the final approval of the version to be published.

AcknowledgmentsThis project was funded by the Swiss Na-

tional Foundation for Scientific Research, Grant 3100A0/

103770/1, and the Research and Development Hospital, Grant

02-1-122.REFERENCES

Adler LA, Spencer T, Faraone SV, Kessler RC, Howes MJ,

Biederman J, Secnik K (2006) Validity of pilot adult ADHD Self-

Report Scale (ASRS) to rate adult ADHD symptoms. Ann Clin

Psychiatry 18:145148.

Babiloni F, Babiloni C, Carducci F, Fattorini L, Onorati P, Urbano A

(1996) Spline Laplacian estimate of EEG potentials over a

realistic magnetic resonance-constructed scalp surface model.

Electroencephalogr Clin Neurophysiol 98:363373.

Babiloni C, Babiloni F, Carducci F, Cappa S, Cincotti F, Del Percio C,

Miniussi C, Moretti DV, Pasqualetti P, Rossi S, Sosta K, Rossini

PM (2004) Human cortical EEG rhythms during long-term

episodic memory task. A high-resolution EEG study of the

HERA model. Neuroimage 21:15761584.

P. Missonnier et al. / Neuroscience 241 (2013) 135146 145Baddeley A, Emslie H, Nimmo-Smith L (1994) The Doors and People

Test: a test of visual and verbal recall and recognition. Bury St.

Edmonds: Thames Valley Test.

Barkley RA (2010) Differential diagnosis of adults with ADHD: the role

of executive function and self-regulation. J Clin Psychiatry 71:e17.

Bayle FJ, Krebs MO, Martin C, Bouvard MP, Wender P (2003) French

version of Wender Utah rating scale (WURS). Can J Psychiatry

48:132.

Biederman J, Petty C, Fried R, Fontanella J, Doyle A, Seidman L,

Faraone SV (2006) Impact of psychometrically defined deficits of

executive functioning in adults with attention deficit hyperactivity

disorder. Am J Psychiatry 163:17301738.

Braver TS, Cohen JD, Nystrom LE, Jonides J, Smith EE, Noll DC

(1997) A parametric study of prefrontal cortex involvement in

human working memory. Neuroimage 5:4962.

Burgess GC, Depue BE, Ruzic L, Willcutt EG, Du YP, Banich MT

(2010) Attentional control activation relates to working memory in

attention-deficit/hyperactivity disorder. Biol Psychiatry

67:632640.

Buschke H, Sliwinski MJ, Kuslansky G, Lipton RB (1997) Diagnosis of

early dementia by the Double Memory Test: encoding specificity

improves diagnostic sensitivity and specificity. Neurology

48:989997.

Butters N, Granholm E, Salmon DP, Grant I, Wolfe J (1987) Episodic

and semantic memory: a comparison of amnesic and demented

patients. J Clin Exp Neuropsychol 9:479497.

Conners K (2004) Conners Continuous Performance Test II Version

5 (CPT II V. 5). Canada: Multi-Health Systems Inc..

Cowan N (1984) On short and long auditory stores. Psychol Bull

96:341370.

Cowan N (1995) Attention and Memory, and Integrated

Framework. Oxford: Oxford University Press.

Deiber MP, Missonnier P, Bertrand O, Gold G, Fazio-Costa L, Ibanez

V, Giannakopoulos P (2007) Distinction between perceptual and

attentional processing in working memory tasks: a study of phase-

locked and induced oscillatory brain dynamics. J Cogn Neurosci

19:158172.

Delorme A, Makeig S (2004) EEGLAB: an open source toolbox for

analysis of single-trial EEG dynamics including independent

component analysis. J Neurosci Methods 134:921.

Ehlis AC, Bahne CG, Jacob CP, Herrmann MJ, Fallgatter AJ (2008)

Reduced lateral prefrontal activation in adult patients with

attention-deficit/hyperactivity disorder (ADHD) during a working

memory task: a functional near-infrared spectroscopy (fNIRS)

study. J Psychiatry Res 42:10601067.

Fayyad J, De Graaf R, Kessler R, Alonso J, Angermeyer M,

Demyttenaere K, De Girolamo G, Haro JM, Karam EG, Lara C,

Lepine JP, Ormel J, Posada-Villa J, Zaslavsky AM, Jin R (2007)

Cross-national prevalence and correlates of adult attention-deficit

hyperactivity disorder. Br J Psychiatry 190:402409.

Fletcher PC, Henson RNA (2001) Frontal lobes and human memory:

insights from functional neuroimaging. Brain 124:849881.

Folstein MF, Folstein SE, McHugh PR (1975) Mini-mental state. A

practical method for grading the cognitive state of patients for the

clinician. J Psychiatry Res 12:189198.

Gardner Jr R, Oliver-Munoz S, Fisher L, Empting L (1981) Mattis

Dementia Rating Scale: internal reliability study using a diffusely

impaired population. J Clin Neuropsychol 3:271275.

Ghent L (1956) Perception of overlapping and embedded figures by

children of different ages. Am J Psychol 69:575581.

Gomarus HK, Wijers AA, Minderaa RB, Althaus M (2009a) Do

children with ADHD and/or PDD-NOS differ in reactivity of alpha/

theta ERD/ERS to manipulations of cognitive load and stimulus

relevance? Clin Neurophysiol 120:7379.

Gomarus HK, Wijers AA, Minderaa RB, Althaus M (2009b) ERP

correlates of selective attention and working memory capacities in

children with ADHD and/or PDD-NOS. Clin Neurophysiol

120:6072.

Greene CM, Braet W, Johnson KA, Bellgrove MA (2008) Imaging the

genetics of executive function. Biol Psychol 79:3042.Gruber WR, Klimesch W, Sauseng P, Doppelmayr M (2005) Alpha

phase synchronization predicts P1 and N1 latency and amplitude

size. Cereb Cortex 15:371377.

Halperin JM, Schulz KP (2006) Revisiting the role of the prefrontal

cortex in the pathophysiology of attention-deficit/hyperactivity

disorder. Psychol Bull 132:560581.

Heaton RK (1981) Wisconsin Card Sorting Test manual. Odessa,

FL: Psychological Assessment Resources.

Hervey AS, Epstein JN, Curry JF (2004) Neuropsychology of adults

with attention-deficit/hyperactivity disorder: a meta-analytic

review. Neuropsychology 8:485503.

Jung TP, Makeig S, Humphries C, Lee TW, McKeown MJ, Iragui V,

Sejnowski TJ (2000) Removing electroencephalographic artifacts

by blind source separation. Psychophysiology 37:163178.

Kaplan EF, Goodglass H, Weintraub S (1983) The Boston Naming

Test. Philadelphia: Lea and Febiger.

Keage HAD, Clark CR, Hermens DF, Williams LM, Kohn MR, Clarke

S, Lamb C, Crewther D, Gordon E (2008) ERP indices of working

memory updating in AD/HD: differential aspects of development,

subtype, and medication. J Clin Neurophysiol 25:3241.

Kessler RC, Adler L, Barkley R, Biederman J, Conners CK, Demler

O, Faraone SV, Greenhill LL, Howes MJ, Secnik K, Spencer T,

Ustun TB, Walters EE, Zaslavsky AM (2006) The prevalence and

correlates of adult ADHD in the United States: results from the

national comorbidity survey replication. Am J Psychiatry

163:716723.

Klimesch W (1999) EEG alpha and theta oscillations reflect cognitive

and memory performance: a review and analysis. Brain Res

29:169195.

Klimesch W, Schack B, Schabus M, Doppelmayr M, Gruber W,

Sauseng P (2004) Phase-locked alpha and theta oscillations

generate the P1N1 complex and are related to memory

performance. Brain Res Cogn Brain Res 19:302316.

Klimesch W, Sauseng P, Hanslmayr S (2007) EEG alpha oscillations:

the inhibition-timing hypothesis. Brain Res 53:6388.

Krause CM, Sillanmaki L, Koivisto M, Saarela C, Haggqvist A, Laine

M, Hamalainen H (2000) The effects of memory load on event-

related EEG desynchronization and synchronization. Clin

Neurophysiol 111:20712078.

Marchetta ND, Hurks PP, Krabbendam L, Jolles J (2008) Interference

control, working memory, concept shifting, and verbal fluency in

adults with attention-deficit/hyperactivity disorder (ADHD).

Neuropsychology 22:7484.

McEvoy LK, Smith ME, Gevins A (1998) Dynamic cortical networks of

verbal and spatial working memory: effects of memory load and

task practice. Cereb Cortex 8:563574.

McEvoy LK, Pellouchoud E, Smith ME, Gevins A (2001)

Neurophysiological signals of working memory in normal aging.

Cogn Brain Res 11:363376.

Missonnier P, Leonards U, Gold G, Palix J, Ibanez V,

Giannakopoulos P (2003) A new electrophysiological index

for working memory load in humans. NeuroReport

14:14511455.

Missonnier P, Deiber MP, Gold G, Millet P, Gex-Fabry Pun M, Fazio-

Costa L, Giannakopoulos P, Ibanez V (2006) Frontal theta

event-related synchronization: comparison of directed attention

and working memory load effects. J Neural Transm

113:14771486.

Missonnier P, Herrmann FR, Zanello A, Badan Ba M, Curtis L,

Canovas D, Chantraine F, Richiardi J, Giannakopoulos P, Merlo

MC (2012) Event-related potentials and changes of brain rhythm

oscillations during working memory activation in patients with first-

episode psychosis. J Psychiatry Neurosci 37:95105.

Mitchell DJ, McNaughton N, Flanagan D, Kirk IJ (2008) Frontal-

midline theta from the perspective of hippocampal theta. Prog

Neurobiol 86:156185.

Nunez PL, Srinivasan R (2006) A theoretical basis for standing and

traveling brain waves measured with human EEG with

implications for an integrated consciousness. Clin Neurophysiol

117:24242435.

146 P. Missonnier et al. / Neuroscience 241 (2013) 135146Nunez PL, Silberstein RB, Cadusch PJ, Wijesinghe RS, Westdorp

AF, Srinivasan R (1994) A theoretical and experimental study of

high resolution EEG based on surface Laplacians and cortical

imaging. Electroencephalogr Clin Neurophysiol 90:4057.

Nystrom LE, Braver TS, Sabb FW, Delgado MR, Noll DC, Cohen JD

(2000) Working memory for letters, shapes, and locations: fMRI

evidence against stimulus-based regional organization in human

prefrontal cortex. Neuroimage 11:424446.

Paloyelis Y, Mehta MA, Kuntsi J, Asherson P (2007) Functional MRI

in ADHD: a systematic literature review. Expert Rev Neurother

7:13371356.

Perrin F, Bertrand O, Pernier J (1987) Scalp current density mapping:

value and estimation from potential data. IEEE Trans Biomed Eng

34:283288.

Pesonen M, Hamalainen H, Krause CM (2007) Brain oscillatory 4

30 Hz responses during a visual n-back memory task with varying

memory load. Brain Res 138:171177.

Pfurtscheller G (1992) Event-related synchronization (ERS): an

electrophysiological correlate of cortical areas at rest.

Electroencephalogr Clin Neurophysiol 83:6269.

Pfurtscheller G (2001) Functional brain imaging based on ERD/ERS.

Vision Res 41:12571260.

Poeck K (1985) Clues to the nature of disruption to limb Praxis. In:

Roy EA, editor. Neuropsychological Studies of Apraxia and

Related Disorders. Amsterdam, North-Holland: Elsevier. p.

99109.

Preisig M, Fenton BT, Mattey ML, Berney A, Ferrero F (1999)

Diagnostic interview for genetic studies (DIGS): inter-rater and

test-retest reliability of the French version. Eur Arch Psychiatry

Clin Neurosci 249:174179.

Reitan RM (1958) Validity of the Trail Making Test as an indicator of

organic brain damage. Percept Mot Skills 8:271276.

Schecklmann M, Romanos M, Bretscher F, Plichta MM, Warnke A,

Fallgatter AJ (2010) Prefrontal oxygenation during working

memory in ADHD. J Psychiatry Res 44:621628.

Schecklmann M, Ehlis AC, Plichta MM, Dresler T, Heine M, Boreatti-

Hummer A, Romanos M, Jacob C, Pauli P, Fallgatter AJ (2012)

Working memory and response inhibition as one integral

phenotype of adult ADHD? A behavioral and imaging

correlational investigation. J Atten Disord, February, 8.

Schnider A, Hanlon RE, Alexander DN, Benson DF (1997) Ideomotor

apraxia: behavioral dimensions and neuroanatomical basis. Brain

Lang 58:125136.Seidman LJ (2006) Neuropsychological functioning in people with

ADHD across the lifespan. Clin Psychol Rev 26:466485.

Shaw P, Eckstrand K, Sharp W, Blumenthal J, Lerch JP, Greenstein

D, Clasen L, Evans A, Giedd J, Rapoport JL (2007) Attention-

deficit/hyperactivity disorder is characterized by a delay in cortical

maturation. Proc Natl Acad Sci U S A 104:1964919654.

Smith EE, Jonides J (1997) Working memory: a view from

neuroimaging. Cogn Psychol 33:542.

Strauss E, Sherman EMS, Spreen S (2006) Compendium of

Neuropsychological Tests. Administration, Norms, and

Commentary. third ed. Oxford, New York: Oxford University

Press.

Stroop JR (1935) Studies of interference in serial verbal reactions. J

Exp Psychol Gen 18:643661.

Suffczynski P, Kalitzin S, Pfurtscheller G, Lopes da Silva FH (2001)

Computational model of thalamo-cortical networks: dynamical

control of alpha rhythms in relation to focal attention. Int J

Psychophysiol 43:2540.

Tenke CE, Kayser J (2005) Reference-free quantification of EEG

spectra: combining current source density (CSD) and frequency

principal components analysis (fPCA). Clin Neurophysiol

116:28262846.

Valera EM, Faraone SV, Biederman J, Poldrack RA, Seidman LJ

(2005) Functional neuroanatomy of working memory in adults with

attention-deficit/hyperactivity disorder. Biol Psychiatry

57:439447.

Van der Linden M, Collette F, Seron X (1999) Adaptation francaise de

la procedure de Grober et Buschke. Marseille: Solal.

Wechsler D (1981) Manual for the Wechsler Adult Intelligence

ScaleRevised. New York: Psychological Corporation.

Wechsler D (1955) Manual for the Wechsler Adult Intelligence

Scale. New York: Psychological Corporation.

Willcutt EG, Doyle AE, Nigg JT, Faraone SV, Pennington BF (2005)

Validity of the executive function theory of attention-deficit/

hyperactivity disorder: a meta-analytic review. Biol Psychiatry

57:13361346.

Woertz M, Pfurtscheller G, Klimesch W (2004) Alpha power

dependent light stimulation: dynamics of event-related

(de)synchronization in human electroencephalogram. Cogn

Brain Res 20:256260.

Yordanova J, Heinrich H, Kolev V, Rothenberger A (2006) Increased

event-related theta activity as a psychophysiological marker of

comorbidity in children with tics and attention-deficit/hyperactivity

disorders. Neuroimage 32:940955.(Accepted 7 March 2013)(Available online 19 March 2013)

EEG anomalies in adult ADHD subjects performing a working memory taskIntroductionExperimental proceduresParticipantsExperimental designElectrophysiological recordingsData processingEvent-related potentials (ERPs)Event-related spectral perturbations (ERSPs)Statistical analysis

ResultsDemographical dataBehavioral resultsEvent-related potentials (ERPs)Exogenous ERP componentsEndogenous ERP components

Timefrequency (TF) resultsTheta frequency bandAlpha frequency band

DiscussionConclusionDeclaration of interestContributorsAcknowledgmentsReferences