Elsevier

Brain Research

Volume 1273, 1 June 2009, Pages 114-128
Brain Research

Research Report
A lack of default network suppression is linked to increased distractibility in ADHD

https://doi.org/10.1016/j.brainres.2009.02.070Get rights and content

Abstract

Heightened distractibility in participants with ADHD as indexed by increased reaction time (RT) variability has been hypothesized to be due to a failure to sufficiently suppress activation in the default attention network during cognitively demanding situations. The present study utilized fMRI to examine the relationship between intra-individual variability (IIV) in task RT and suppression of BOLD response in regions of the default network, using a working memory paradigm and two levels of control tasks. IIV was calculated separately for thirteen healthy control and twelve children with ADHD, Combined Type. Children with ADHD displayed significantly more RT variability than controls. Neural measures showed that although both groups displayed a pattern of increasing deactivation of the medial prefrontal cortex (PFC) with increasing task difficulty, the ADHD group was significantly less deactive than controls. Correlations between IIV and brain activation suggested that greater variability was associated with a failure to deactivate ventromedial PFC with increasing task difficulty. T-tests on brain activation between participants with ADHD with low versus high IIV implicated a similar region so that high variability was associated with greater activity in this region. These data provide support for the theory that increased distractibility in at least some participants with ADHD may be due to an inability to sufficiently suppress activity in the default attention network in response to increasing task difficulty.

Introduction

Attention Deficit Hyperactivity Disorder is a common childhood disorder characterized by inattention, hyperactivity and impulsivity (Barkley, 2006). Although it is a widely studied disorder, the underlying pathophysiology is still much debated. A number of theoretical frameworks have been proposed as mechanisms for the disorder including a weakness in executive functioning (Barkley, 1997), difficulties with reward processing (Sagvolden et al., 1998), and energetic dysfunctions as described by the cognitive energetic model (Sergeant, 2000, Sergeant, 2005). ADHD is a disorder typically characterized by high degrees of intra-individual variability (IIV) in reaction time (RT) (e.g., Castellanos et al., 2005, Leth-Steensen et al., 2000). This characteristic high RT variability has been argued to be an important endophenotype for the disorder (Band and Scheres, 2005, Castellanos et al., 2005, Castellanos and Tannock, 2002, Douglas, 1999, Kuntsi et al., 2001, Kuntsi and Stevenson, 2001, Nigg et al., 2004). Increased RT variability has been associated with fluctuations in attention or arousal (Bellgrove et al., 2004, Cao et al., 2008, Stuss et al., 2003) or response control (Suskauer et al., 2008). Greater RT variability has been noted in ADHD compared to healthy control (HC) participants utilizing a variety of different paradigms including inhibition and sustained attention tasks (Alderson et al., 2007, Bellgrove et al., 2005, Cao et al., 2008, de Zeeuw et al., 2008, Epstein et al., 2006, Heiser et al., 2004, Hervey et al., 2006, Johnson et al., 2007, Klein et al., 2006, Kuntsi et al., 2005, Lijffijt et al., 2005, Shallice et al., 2002), choice reaction time tasks (Geurts et al., 2008, Leth-Steensen et al., 2000), flanker paradigm (Castellanos et al., 2005) and working memory tasks (Buzy et al., 2009, Karatekin, 2004, Klein et al., 2006, Piek et al., 2004) and has been associated, in particular, with DAT-1 dopamine transporter genotype (Bellgrove et al., 2005). However, many studies of IIV in ADHD utilize the standard deviation of RT across the entire task, a summary statistic that gives an estimate of variability around the mean and assumes that RTs fall on a normal Gaussian distribution. Recent findings, suggest, that RT distributions of ADHD participants are not necessarily best characterized by fitting the normal distribution because they are usually positively skewed (Douglas, 1999, Epstein et al., 2006, Leth-Steensen et al., 2000) and research suggests that parametric studies of the shape of the RT would provide more information than standard summaries such as the mean and standard deviation (Leth-Steensen et al., 2000).

The ex-Gaussian model is a right-tailed distribution which is commonly used to estimate the distribution of RT (Heathcote,1996). It can be decomposed into the summation of two independent components: a symmetric Gaussian component and an exponential component (which captures the extremely slow RTs displayed by ADHD participants) which can dramatically influence the mean and standard deviation. A small number of studies have utilized the ex-Gaussian model to examine IIV in ADHD (Buzy et al., 2009, Epstein et al., 2006, Geurts et al., 2008, Hervey et al., 2006, Leth-Steensen et al., 2000) and have all found differences in IIV between ADHD and HC volunteers, with the exception of Geurts et al. (2008). The latter authors suggest that their choice reaction time task of 3 min length may have been too brief to reveal differences in IIV.

Variable RT is associated with both weak positive activation of task relevant regions and insufficient suppression of the “default-mode network” (Weissman et al., 2006). With regard to task positive activations, slow and variable RT has been linked to altered activation in dorsolateral PFC in HC participants (Bellgrove et al., 2004, Stuss et al., 2003). In a recent study comparing IIV in HC and ADHD participants, increased IIV in controls was associated with a decrease in activity in pre-supplementary motor area and increased activity in prefrontal cortex, whereas the ADHD participants displayed exactly the opposite pattern (Suskauer et al., 2008).

The ‘default-mode’ attention network is a set of brain regions, primarily located along the medial wall of the brain, associated with task-irrelevant mental processes that are putatively suppressed in order to perform optimally in cognitively demanding situations (Raichle et al., 2001). That is, these regions are commonly deactive during cognitively demanding paradigms. Deactivation in this network is thought to be due to an interruption of ongoing processes that occur during rest and non-demanding situations (Binder et al., 1999, Gusnard et al., 2001b, Shulman et al., 1997). These processes are thought to include monitoring of the environment, body state or emotional state (Gusnard et al., 2001b, Shulman et al., 1997), ongoing internal thought processes or mind wandering (Binder et al., 1999, Shulman et al., 1997). An inability to sufficiently suppress activation in this network has been linked to distraction or momentary attention lapses and errors in performance (Eichele et al., 2008, Weissman et al., 2006), whereas successful performance has been linked to increased deactivation in these regions in HC participants (Daselaar et al., 2004, Hahn et al., 2007, Hester et al., 2004, Polli et al., 2005). Raichle et al. (2001) proposed that these regions are tonically active, monitoring the surroundings of an organism and must be inhibited in situations that require concentrated attention. In HC subjects, the degree of suppression in these default network regions appears to be related to task difficulty, with greater deactivation associated with increasing difficulty (McKiernan et al., 2003).

Inspired by the Weissman et al. (2006) finding that variable RT is linked to a failure to suppress the default network, Sonuga-Barke, Castellanos et al. proposed the “default-mode interference” hypothesis (Castellanos et al., 2008, Sonuga-Barke and Castellanos, 2007). They suggest that variability in performance in ADHD may be due to a dysfunctional synchronization in the default network or interactions between this network and “task-active” regions. Castellanos et al. (2008) examined functional connectivity between active regions usually implicated in cognitive control processes and default network regions during a resting state in ADHD and HC adults. The ADHD subjects evidenced decreases in connectivity between the posterior cingulate/precuneus and task-active regions such as dorsal ACC but also other default network regions such as ventromedial PFC. Recent evidence from this group suggests that slow or variable RTs are associated with a weak correlation between task positive regions and task negative regions (Kelly et al., 2004). Finally, a reduction in power in very low frequency oscillations electrodes consistent with default network regions was found in young adults with greater numbers of ADHD symptoms, particularly symptoms relating to inattention (Helps et al., 2008). Low frequency oscillations in resting state fMRI data have previously been found to reflect interactions in the default attention network (De Luca et al., 2006).

This study sought to explore how IIV, calculated using the ex-Gaussian distribution, was associated with deactivation in the default network among children with ADHD, Combined Type in comparison to HC children and whether IIV changed with different levels of task difficulty. Sonuga-Barke and Castellanos (2007) suggest that the default-mode interference hypothesis might be most pertinent for the primarily inattentive ADHD subtype. We sought to examine whether there was support for their theory in our Combined Type sample, considering that these subjects also exhibit inattentive symptoms.

We utilized data from a previous working memory study (Schweitzer et al., under review) to examine how task difficulty level, that is, working memory load, affected patterns of deactivation in the default network in ADHD compared to HC children. Previous research utilizing a working memory task with parametrically-increasing working memory load in HC children suggested an active suppression of default network regions with increasing task difficulty (Thomason et al., 2008). The authors utilized a correlation method to confirm that areas which showed increased suppression with increasing task difficulty overlapped with regions of the default network which were defined by being functionally connected during rest. Castellanos et al. address how inattention in ADHD may be related to default network activity interfering with current engagement in active task performance. Hence we sought to examine how default network activity is attenuated in children with ADHD during a cognitively demanding paradigm and with increasing task difficulty. This contrasts with other studies which have examined activity in the default network in ADHD during resting states only.

Based on our previous work (Buzy et al., 2009) we hypothesized that children with ADHD would display greater levels of IIV than controls during the working memory paradigm. We also predicted that IIV would increase with task difficulty in all children (McKiernan et al., 2003, Thomason et al., 2008). Furthermore, we expected that participants with ADHD would fail to sufficiently suppress activity in the default attention network with increasing cognitive load and that this would be paired with increased IIV in comparison to their healthy control peers. Finally, we hypothesized that ADHD children who displayed the least amount of suppression of the default network would also have greater levels of intra-individual RT variability.

Section snippets

Results

The following results represent a subset of participants from our previous working memory study (Schweitzer et al., under review). We excluded one ADHD female from this analysis as her data for the present study lay almost 3 standard deviations outside her peers'. Groups did not differ across age, SES, or IQ (Table 1). There were no differences in accuracy or mean RT between the ADHD and HC groups on the Visual Serial Attention Task (VSAT), Addition Task (AT) or Match-to-Sample Task (MST).

Discussion

The default attention network is a group of regions located along the brain's medial wall, which are active during non-cognitively demanding paradigms and have been associated with task-irrelevant thought processes, mind wandering, and attention to the outside environment or one's own mental state (Gusnard et al., 2001b, Shulman et al., 1997). Using tasks with increasing levels of cognitive demand, we isolated a number of regions – principally in medial PFC and ACC, and consistent with the

Participants

Through recruitment strategies that included newspaper advertisements, pediatric and ADHD clinics, support groups and websites 17 ADHD and 22 HC children between the ages of 8 and 14 years were recruited. The final group of participants included 12 ADHD (11 male) and 13 HC (8 male) children selected to match the age, IQ, and SES of the ADHD group (see Table 1). Six (four ADHD) children were excluded for excessive amounts of movement or asking to discontinue the fMRI session. One ADHD female

Acknowledgments

The authors thank the participants and their parents; Mark Cochran, Ph.D., Rao Gullapalli, Ph.D., Malle Tagamets, Ph.D., Caitlin Dunning, Psy.D., Barbara McGee, J. Daniel Ragland, Ph.D., Gloria Reeves, M.D., T. Andrew Windsor and Jiachen Zhuo for their assistance. The authors report no competing interests.

Funding for this study was provided by the National Institutes of Mental Health, National Institute of Health (R01 MH066310) and University of Maryland School of Medicine Intramural Award to

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