Adult ADHD and working memory: Neural evidence of impaired encoding

Highlights

• ADHD college students are compared to their typically developing peers on neural and behavioural indices of working memory (WM).

• Neural indices of working memory (P3) are examined during working memory encoding using EEG.

• ADHD group showed lower P3 during working memory encoding, suggesting an inefficient encoding process in WM.

Abstract

Objectives

To investigate neural and behavioural correlates of visual encoding during a working memory (WM) task in young adults with and without Attention-Deficit/Hyperactivity Disorder (ADHD).

Methods

A sample of 30 college students currently meeting a diagnosis of ADHD and 25 typically developing students, matched on age and gender, performed a delayed match-to-sample task with low and high memory load conditions. Dense-array electroencephalography was recorded. Specifically, the P3, an event related potential (ERP) associated with WM, was examined because of its relation with attentional allocation during WM. Task performance (accuracy, reaction time) as well as performance on other neuropsychological tasks of WM was analyzed.

Results

Neural differences were found between the groups. Specifically, the P3 amplitude was smaller in the ADHD group compared to the comparison group for both load conditions at parietal–occipital sites. Lower scores on behavioural working memory tasks were suggestive of impaired behavioural WM performance in the ADHD group.

Conclusions

Findings from this study provide the first evidence of neural differences in the encoding stage of WM in young adults with ADHD, suggesting ineffective allocation of attentional resources involved in encoding of information in WM.

Significance

These findings, reflecting alternate neural functioning of WM, may explain some of the difficulties related to WM functioning that college students with ADHD report in their every day cognitive functioning.

Introduction

Attention-Deficit/Hyperactivity Disorder (ADHD) is the most frequently diagnosed psychiatric disorder in childhood with worldwide prevalence rates estimated at 5.3% (Polanczyk and Rohde, 2007). Longitudinal studies show that approximately 65% of children with ADHD continue to show symptoms in adulthood (Barkley et al., 2002, Faraone et al., 2006, Polanczyk and Rohde, 2007). A newly-emergent subset of young adults with ADHD – those who gain entrance into post-secondary education – is of interest because of their ongoing impairments despite educational success relative to others with ADHD (DuPaul et al., 2009). These students present various impairments in social and academic domains. For instance, they exhibit difficulties with college adjustment, social skills and self-esteem (Shaw-Zirt et al., 2005), lower Grade Point Averages, poorer academic success, and they are more likely to be placed on academic probation (Heiligenstein et al., 1999, Frazier et al., 2007). Working memory (WM), seen as one of the core deficits of ADHD (Martinussen et al., 2005, Hervey et al., 2004), could be a key factor explaining some of the functional impairments mentioned above. WM allows us to temporarily hold and manipulate information “on-line” for a few seconds in order to respond effectively based on that information (Baddeley, 2003). WM involves several stages of information processing: encoding, maintenance (rehearsal) and retrieval. WM has been linked with many real world activities (e.g., reading comprehension, following a conversation, problem-solving; Baddeley and Hitch, 1994) and therefore WM impairments may have pernicious effects on everyday life, especially considering the social and academic demands students face in college.

WM processing can be effectively investigated using ERP methodology due to its fine temporal resolution. Among ERP components, changes in P3 amplitudes, occurring about 300 ms after the stimulus, have been reliably associated with WM functioning. Several theories have been proposed to interpret the role of the P3 in working memory tasks (for overview, see Kok, 2001, Polich, 2007), however, there is no consensus as to what the P3 represents in the context of a WM task, especially during the encoding phase. For example, Donchin and Coles (1988) interpreted the P3 within the framework of a “context updating theory” which proposes that P3 is increased when there is a need to update, change, or refresh the current contents of WM. Researchers also focus on the intricate role of attentional processes in working memory functioning. For instance, some suggest that WM capacity is determined by an executive attentional process (Kane et al., 2007; Vogel et al., 2005), or the ‘capacity of the focus of attention’ (i.e., the scope of attention; Cowan, 2001). Ford et al. (1994) suggested that P3 amplitude reflects the effort to allocate attention (see also, Polich, 2007). Similarly, Kok (2001) proposed that the P3 reflects the ‘attentional capacity invested in the categorization of task relevant events’. In sum, these studies suggest a possible link between P3 amplitude and allocation of attentional resources that subserve working memory functioning. Thus, in the current study, we interpret P3 activation as reflecting the direction of attentional resources towards encoding information into WM, such as categorizing events or updating mental representations. However, attention acts at many levels of processing during working memory, including early perceptual processes (Rutman et al., 2010). For instance, ERP components such as the P1 are believed to represent sensory responses elicited by visual stimuli as early as 100 ms (Luck, 2005). Thus, we also measure the P1 component to ascertain whether perceptual/sensory processes are intact or altered in college students with ADHD.

A recent meta-analysis of six studies investigating the P3 component in adults with ADHD found significantly reduced P3 amplitude compared to controls (Szuromi et al., 2011). However, all of the studies used a GoNoGo paradigm: none used a WM task. Moreover, a recently published EEG study of WM functioning in adult ADHD utilized an n-back task and mainly investigated time-frequency measures (Missonnier et al., 2013). Among other findings in that study, Missonier and colleagues (2013) reported reduced low frequency oscillations (e.g., theta) in the ADHD group during the period in which the P3 would have occurred (e.g., between 200 and 500 ms), suggesting that both time-and frequency domain measures reflect similar underlying neural processes.

Only one study to date has investigated the P3 component in the context of a ‘delayed match-to-sample’ WM paradigm and this involved a comparison of participants with and without Schizophrenia (Haenschel et al., 2007). In this paradigm, the to-be-remembered target stimuli were presented in a sequence that varied in length (e.g., 2 versus 3 stimuli) to measure effects of WM load. Longer sequences place greater demands on WM in terms of storage and updating information compared to short sequences. Then, after a delay period, the participant is asked whether a test-stimulus matched one of the targets. The task uses irregular shapes as stimuli to avoid verbal/semantic processing. Significantly reduced mean P1 (an early visual component) and P3 amplitudes were found in individuals with Schizophrenia compared to controls. The load effect was present only for the P1 component. The authors interpreted the reduced P1 activity as an early visual processing deficit whereas the decreased P3 amplitudes were interpreted as evidence of reduced ability in categorizing or evaluating stimuli.

To investigate WM, the present study adapted Haenschel’s WM paradigm (Haenschel et al., 2007) and used it with a sample of college students with ADHD. This paradigm allowed us to investigate the neural effects of encoding stimuli presented in sequence under different load conditions (low versus high load). Specifically, the current task required participants to allocate attention to the stimulus, register it, and then quickly shift attention to the next stimulus while keeping the previous one in mind. This process requires both earlier attention allocation to sensory/perception of the stimuli and later allocation of attention to evaluate the stimulus and update the mental representation. To the best of our knowledge, no previous study has investigated the encoding phase of WM using a delayed-match-to-sample task in participants with ADHD. A complete understanding of ADHD necessitates the study of different subpopulations of this clinical condition, which represent different levels of functioning. Our sample is unique in that it consists of college students with ADHD who are relatively high functioning and successful academically, but who continue to show impairment (DuPaul et al., 2009). A better understanding of mechanisms underlying their difficulties may inform interventions designed to increase academic achievement and educational attainment in this population.

To determine whether participants with ADHD are impaired during WM encoding, we measured P1 and P3 amplitudes, which allowed us to ascertain at which stage (early vs. later visual processing) any impairment occurred. Furthermore, to test whether any impairment might vary according to the level of WM demand, we utilized two load conditions (low, high) in the delayed match-to-sample WM task. We predicted that individuals with ADHD would show impaired WM performance and reduced P3 amplitude and that these group differences would be most pronounced under the high-load WM condition.