Early Gamma-Band Activity During Interference Predicts Working Memory Distractibility in ADHD

Abstract

Objectives: Patients with attention-deficit/hyperactivity disorder (ADHD) display deficits in working memory (WM) and enhanced distractibility. Methods: Evoked gamma-band response (GBR) occurs already 50ms after stimulus onset and is modulated by attention. 16 boys with ADHD and 20 healthy controls (10-14 years) completed a WM task with distraction. Results: Occipitally evoked 40Hz-GBR was higher during distraction in ADHD than controls. GBR correlated negatively with interference control. Conclusion: These data suggest that ADHD patients are disturbed by interference on an early level of perception.

Keywords

ADHD working memory interference evoked gamma-band response

Introduction

Patients with ADHD are characterized by patterns of inattention, hyperactivity, and/or impulsiveness (American Psychiatric Association [APA], 2000). Neuropsychological, imaging, and genetic studies show that alterations in the central catecholamine system cause deficits in working memory (WM) and susceptibility to interference (Brennan & Arnsten, 2008; Lansbergen, Kenemans, & van Engeland, 2007; Martinussen, Hayden, Hogg-Johnson, & Tannock, 2005). Studies using electroencephalogram (EEG) revealed that ADHD patients showed a reduced event-related component P3 during visual or acoustic interference processing during WM (Gumenyuka et al., 2005; Keage et al., 2006), indicating an inappropriate attention switch at a later level of stimulus processing. Event-related oscillations in the EEG gamma-band range (30-100 Hz) can be divided into the early evoked and the later induced gamma-band response (GBR). Both EEG patterns are associated with memory processes (Herrmann, Frund, & Lenz, 2010). However, as evoked GBR is one of the first cortical responses to stimulus perception, they reflect filtering at very early stages of perception more suitable compared with induced GBR occurring later in the EEG. In the case of visual perception, evoked GBR occurs 50 to 150 ms after stimulus onset maximum around 40 Hz over visual cortex areas (Tallon-Baudry & Bertrand, 1999). Besides bottom–up stimulus features (Herrmann et al., 2010), evoked GBR amplitude can also be modulated by endogenous factors such as dopaminergic availability (Herrmann & Demiralp, 2005) as well as cognitive processes like attention (Debener, Herrmann, Kranczioch, Gembris, & Engel, 2003) and memory (Herrmann et al., 2004). Although ADHD is characterized by deficits in attention and WM caused by reduced availability of dopamine (Brennan & Arnsten, 2008), studies investigating evoked GBR in attention and memory processes in ADHD are rare. Lenz and colleagues reported an overshooting but unspecific level of visually evoked GBR during a declarative memory task in young ADHD patients (Lenz et al., 2008), and deviant evoked GBR during memory matching indicated deficits in early automatic stimulus processing (Lenz et al., 2010). Enhanced evoked GBR in ADHD were also reported during discrimination between relevant and irrelevant auditory information (Yordanova, Banaschewski, Kolev, Woerner, & Rothenberger, 2001). However, it is still unclear whether GBR might act as a biomarker for enhanced distractibility during memory processes in ADHD. We hypothesize that, in the context of visual WM, patients with ADHD compared with controls are more distracted by interfering stimuli accompanied by an increased occipital evoked 40 Hz-GBR during visual distraction.

Method

Participants

A total of 16 male patients with ADHD and 20 healthy control children (10-14 years) participated in this study. Patients were recruited in our outpatient clinic, whereas healthy controls were recruited by announcements in local newspapers. All participants (right-handed and with normal or corrected-to-normal vision) and their parents were interviewed with a German translation of the Revised Schedule for Affective Disorders and Schizophrenia for School-Age Children: Present and Lifetime Version (K-SADS-PL; Delmo et al., 2000; Kaufman et al., 1997). Parents filled out a standard parent-reported questionnaire (Child Behavior Checklist [CBCL]; Achenbach, 1991). All patients met the criteria for ADHD according to Diagnostic and Statistical Manual of Mental Disorders (4th ed., text rev.; DSM-IV-TR; APA, 2000; 9 inattentive and 7 combined type, no comorbidities). In all, 12 patients took methylphenidate (MPH) but discontinued medication 48 hr (approximately 12 half-lives) prior to the experiment. Healthy controls did not exhibit psychiatric symptoms. Patients and healthy controls differed in CBCL attention problems (p < .001) but not in IQ (p = .607), as measured by Culture Fair Intelligence Test Revised Vision (Weiss, 2006), or in age (p = .197, Table 1).

Table 1.

Participant Characteristics, Behavioral and GBR Data.

	ADHD (N = 16)	Controls (N = 20)	ADHD vs. controls
	M ± SEM	M ± SEM	t	p
Age	12.7 ± 0.32	13.2 ± 0.28	1.31	.197
IQ	106.6 ± 2.7	108.3 ± 2.1	0.30	.607
CBCL (T-scores)
Attention problems	68.8 ± 1.8	52.5 ± 0.9	8.60	<.001
Delinquent rule-breaking behavior	58.6 ± 1.7	51.1 ± 0.6	4.41	<.001
Aggressive behavior	62.2 ± 2.4	51.9 ± 0.7	4.51	<.001
Internalizing	60.2 ± 2.2	54.5 ± 2.3	1.78	.084
Externalizing	60.6 ± 2.4	48.4 ± 1.3	4.73	<.001
WM accuracy
Without distractor	67.9 ± 0.5.6	77.8 ± 3.6	1.53	.135
With distractor	61.1 ± 0.3.9	77.8 ± 3.0	3.41	.002
Evoked GBR
Sample	0.75 ± 0.13	0.41 ± 0.09	1.56	.127
Distraction	0.78 ± 0.18	0.29 ± 0.06	2.9	.007
Match	0.68 ± 0.17	0.18 ± 0.04	1.9	.068

Note. CBCL = Child Behavior Checklist; WM = working memory; GBR = gamma-band response (average of peaks in 39, 40, and 42 Hz EEG spectrum). Bold values indicate significant group differences.

All participants and parents gave written informed consent, and participants were reimbursed with a voucher for participation. The study was approved by the ethics committee of the medical faculty of the University of Kiel and followed the ethical standards of the Helsinki Declaration.

Stimulus Material

Stimuli were 232 pictures of places (116 indoor, 116 outdoor), 32 pictures of nonemotional faces, and 32 emotional pictures taken from the International Affective Pictures System (Lang, Bradley, & Cuthbert, 2005). Pictures were used for a visual WM task (delayed-match-to-sample paradigm). At the beginning of the trial, a picture of a place (sample) was presented for 1 s. After a delay of 8 s (gray square with a centered fixation asterisk), another picture of a place (match) was presented for 1 s. After the match picture disappeared, participants had to indicate whether the match was identical to the sample picture by pressing one of two response buttons. In three of four trials, a distractor appeared for 1 s (place, face, or emotional picture) 3.5 s after the sample picture. Participants were informed that an additional picture could occur in the delay interval but were instructed to ignore those pictures. We choose different types of distracting pictures to arouse attention. A new trial started after 10 s (jitter = ±2 s). Trials were presented in pseudorandomized order. We used a very similar WM paradigm in a former functional magnetic resonance imaging (fMRI) study (Prehn-Kristensen et al., 2011).

Electrophysiological Data

EEG and electroocculogram signals were recorded by a BrainAmp (Brain Products, Gilching, Germany) amplifier using sintered Ag/AgCl electrodes (impedances < 10 kOhm, sampling rate = 500 Hz, band-pass filter = 0.1-250 Hz; 50 Hz notch). EEG was recorded from 32 channels according to the international 10 to 20 system (left/right mastoid as reference; ground electrode at the forehead). For evoked GBR calculation, only data from O1 and O2 were analyzed. Bipolar recordings of horizontal and vertical eye movements were obtained from the outer canthi of both eyes and the sub- and supraorbital positions. Analysis was conducted using BrainVision Analyzer 2 (Brain Products, Gilching, Germany). Eye-movement activity was corrected using independent-component-analysis. Data were segmented into epochs of 800 ms (−200 to 600 ms after stimulus onset) according to the three conditions “sample,” “distractor,” and “match.” Baseline activity (−200 to −100 ms before stimulus onset) was calculated and subtracted from each epoch. Automatic artifact rejection excluded epochs from further analyses, if the difference between the highest and lowest amplitude within any epoch exceeded 100 µV. Continuous complex wavelets (morlet parameter c = 4, absolute power values) were calculated to determine the frequency spectrum power between 1 and 60 Hz in 60 frequency steps. Within each participant, wavelets were calculated for each single trial and subsequent averaged with respect to the three conditions. To obtain 40 Hz-GBR, maximum amplitude activity for the frequency steps 39, 40, and 42 Hz was detected 50 to 150 ms after stimulus onset using an automated peak detection procedure. Thereafter, GBRs were averaged over the frequency range 39 to 42 Hz and subsequently over both occipital electrodes O1 and O2.

Statistical Analyses

GBR data were analyzed by comparing mean peak activity between ADHD and controls within each condition (“sample,” “distractor,” and “match”) and each frequency step by using t tests. Behavioral data were analyzed by calculating performance accuracy (Snodgrass & Corwin, 1988). Performance was analyzed by using a 2 × 2 ANOVA with the within-factor Interference (without vs. with interference) and the between-factor Group (ADHD vs. controls). Correlations between the peak of evoked GBR around 40 Hz (averaged for 39-42 Hz) and behavioral data were performed by Pearson’s correlation coefficients.

Results

GBR during sample or match presentation did not differ between ADHD and controls (p > .05; see Table 1 and Figure 1). However, in the distractor condition, ADHD patients displayed higher GBR than controls (p = .007). ADHD patients displayed worse performance than controls overall (main effect GROUP: p = .004), which was mainly due to the condition with interference (ADHD vs. controls; with distractor: p = .002; without distractor: p = .135; Table 1). Although performance with or without interference did not differ (p = .999) in healthy controls, ADHD patients were disturbed by interference at the edge of significance (p = .052). The interaction Group × Interference, however, only showed a trend of significance (p = .164). Correlation analyses revealed that mean peak GBR ranging between 39 and 42 Hz during distraction was negatively associated with WM performance during distraction (r = −.481, p = .003). Additional correlation analyses revealed that behavioral data between trials with and without distraction were not correlated (r = −.229, p = .180). Moreover, GBR during distraction was correlated with CBCL scores for attention problems (r = .378, p = .021) but not with scores for delinquent rule-breaking behavior (r = .074, p = 669), aggressive behavior (r = −.019, p = .914), and internal (r = .241, p = .157), or external problems (r = .131, p = .445). To control for the impact of symptom severity on the correlation between GBR and WM performance during distraction, we performed an additional partial correlation. However, even after introducing CBCL scores for attention problems as a control variable, the correlation coefficient still reached significance (r = −.346, p = .042). Behavioral performance in both task conditions (with and without distraction) were not correlated (r = −.229, p = .180).

Figure 1.

(A) Behavioral results. (B) Correlation between accuracy and the evoked gamma-band response (GBR) during distraction for patients with ADHD (black dotted) and healthy controls (white dotted). (C) Time frequency plots for all three conditions “sample,” “distraction,” and “match.”

Discussion

Young patients with ADHD displayed deficits in WM performance, when WM maintenance was distracted by additional interference. This enhanced distractibility was accompanied by an increased evoked 40 Hz-GBR during distractor perception, but not during encoding or retrieval. Moreover, evoked GBR correlated with WM performance during distraction.

Although ADHD is accompanied by WM deficits (Martinussen et al., 2005) and distractibility (Lansbergen et al., 2007), only few electrophysiological studies investigated the effect of interference control during WM. EEG data revealed in ADHD patients a reduced P3a during interference (Gumenyuka et al., 2005; Keage et al., 2006). These results are interpreted in terms of an enhanced attention switch during distraction in ADHD. Our data extend these findings in that ADHD patients are disturbed on an earlier level of stimulus perception (50-150 ms) than suggested by the P3a. Increased evoked GBR in ADHD was reported previously in auditory and visual stimulus processing (Lenz et al., 2008; Lenz et al., 2010; Yordanova et al., 2001). GBRs in our ADHD sample were substantially increased during distraction but not during WM encoding. Therefore, our results cannot be ascribed to an overall attentional deficit but rather to a specific feature of interference susceptibility in ADHD. A comparable selective overshooting GBR in ADHD was reported in an incidental declarative memory paradigm (Lenz et al., 2008): GBR was enhanced only during a matching task but not during task encoding. Based on additional correlation analyses, our data suggest that the evoked GBR during distraction could be used as a biomarker for attention deficits in ADHD, independently of the occurrence of disruptive behavior, which often accompanies ADHD (Connor & Ford, 2012).

In light of the match-and-utilization model, evoked GBR is proposed to reflect matching processes in the context of memory tasks (Herrmann et al., 2004). From this point of view, our data suggest that ADHD patients inevitably and mistakenly compared the distractor with the sample picture, indicating an overestimation of delay duration. This interpretation fits into the findings that ADHD patients are accompanied by delay aversion (Sonuga-Barke, Wiersema, van der Meere, & Roeyers, 2010) and overestimate particularly very short time intervals (Hurks & Hendriksen, 2011).

As GBR is inversely proportional to dopaminergic availability (Herrmann & Demiralp, 2005), it is plausible to assume that the enhanced GBR in our patient sample is caused by the well-documented dopaminergic dysfunctions in ADHD (Brennan & Arnsten, 2008). MPH increases dopamine levels, which leads to the assumption that MPH decreases GBR, resulting in decreased interference susceptibility. Interestingly, we recently reported that MPH had no impact on distractibility in a very similar WM paradigm in ADHD (Prehn-Kristensen et al., 2011). Thus, further functional imaging studies are required to investigate the associations between dopamine, GBR, and distractibility in ADHD. Moreover, including reaction times into the analyses would support data validity. This was not possible in our paradigm due to the instruction to not give an answer until the match stimulus disappeared.

Taken together, we observed that young patients with ADHD compared with healthy controls were more distracted by interference and that WM maintenance was disturbed already on an early level of interference perception.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was supported by grants from the German Research Foundation (KFO 163 and SFB 654).

Author Biographies

Alexander Prehn-Kristensen, PhD, works as a research assistant in the Department of Child and Adolescent Psychiatry and Psychotherapy at the Center for Integrative Psychiatry of Kiel, Germany. Currently his research work focuses on memory deficits in children suffering from ADHD.

Christian D. Wiesner, PhD, works as a research assistant in the Department of Child and Adolescent Psychiatry and Psychotherapy at the Center for Integrative Psychiatry of Kiel, Germany. His research interests are motivation and memory performance in mental diseases related to dopaminergic dysfunctions.

Lioba Baving, PhD, MD, is a full professor of Child and Adolescent Psychiatry at the University of Kiel and director of the Department of Child and Adolescent Psychiatry and Psychotherapy at the Center for Integrative Psychiatry of Kiel, Germany. Her research interests include memory deficits in young patients with disruptive behaviour disorders.

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