Behavioral correlates of reaction time variability in children with and without ADHD.

Attention Deficit Hyperactivity Disorder (ADHD)-related deficits in working memory, attention, and inhibitory control have been well documented on neuropsychological tests (see Hervey et al., 2004 & Willcutt et al., 2005 for meta-analytic reviews). In addition to these cognitive deficits, children with ADHD have higher levels of intra-individual variability in reaction times than typically-developing children (De Zeeuw et al., 2008; Epstein et al., 2011a; Klein, Wendling, Huettner, Ruder, & Peper, 2006; Vaurio, Simmonds, & Mostofsky, 2009). Researchers have proposed that reaction time (RT) variability may be a potential endophenotype for ADHD (Castellanos & Tannock, 2002), particularly since heritability of RT variability is high (Kuntsi & Stevenson, 2001; Andreou et al., 2007). Most studies have demonstrated increased RT variability using RT standard deviation (RTSD). However, more recent studies have used ex-Gaussian estimates and fast Fourier transform analyses to demonstrate that children with ADHD are not consistently slower or always more variable than typical children, but that children with ADHD tend to exhibit intermittent long reaction times during task performance (Hervey et al., 2006; Leth-Steensen, Elbaz, & Douglas, 2000; Vaurio et al., 2009). In addition, these instances of long reaction times in children with ADHD may be predictably periodic (Castellanos et al., 2005; Johnson et al., 2007; Vaurio et al., 2009). Although these analyses help to better describe the patterns of RT variability among children with ADHD, it remains unclear what these intermittent periods of long reaction times signify (Tamm et al., 2012). Multiple hypotheses exist postulating what RT variability represents in children with ADHD, including slower cognitive processing, deviant time perception (Kalff et al., 2005) and problems with state regulation (Sergeant, 2005). Several investigators have also posited that periods of long reaction times are indicative of lapses in attention (Leth-Steensen et al., 2000; Hervey et al., 2006), although this remains unsubstantiated. In an attempt to better understand RT variability, researchers have begun to examine its behavioral correlates. For example, does RT variability relate specifically to inattention? Studies examining differences between children with ADHD-Combined Type and children with ADHD-Predominantly Inattentive Type have shown that both groups have slower mean reaction times and greater RT variability than control groups, but have not indicated substantial differences between the two subtypes (Epstein et al., 2011a; Nigg, Blaskey, Huang-Pollock, & Rappley, 2002; Pasini, Paloscia, Alessandrelli, Porfirio, & Curatolo, 2007, Solanto et al., 2007). Correlational studies examining associations between RT variability and parent- and teacher-reported ADHD symptom domains have found that RT variability is related to composite scores of inattention more so than to hyperactivity/impulsivity (Nigg, 1999; Wahlstedt, 2009). However, a study examining relations between RT variability and individual ADHD symptoms found that RT variability was related to specific symptoms in both ADHD symptom domains (Epstein et al., 2003). Examining behavioral correlates of RT variability using parent- or teacher reports of ADHD behaviors may be limited as behavioral ratings provide general summaries of behavior over an extended period of time (e.g., last week) rather than temporally-specific, moment-by-moment, information about behavioral variability. Observational methods with temporal coding of inattentive behavior may better relate to RT variability than parent or teacher ratings. Indeed, using behavioral observations, children with ADHD exhibit more off-task behavior than controls (see Kofler, Rapport, & Alderson, 2008 for a meta-analytic review). Further, children with ADHD appear to exhibit greater within-subject variability in their off-task behavior than controls (Abikoff, Gittelman-Klein, & Klein, 1977; Lauth, Heubeck, & Mackowiak, 2006; Kofler et al., 2008). Using a continuous coding strategy, Rapport, Kofler, Alderson, Timko, and DuPaul (2009) found that compared with controls, children with ADHD stay on-task for shorter periods of time and exhibit greater variability in visual attention during academic assignment completion in the classroom. There is a limited literature examining relations between continuously observed ADHD behavior and neuropsychological indicators (Weis & Totten, 2004; Solanto et al., 2001). No study to date has examined neuropsychological-behavioral relations using RT variability as a neuropsychological indicator. Given the magnitude of between-group differences on RT variability outcomes (Epstein et al., 2011a) and the supposition that RT variability may be indicative of attentional lapses (Hervey et al., 2006; Leth-Steenson, et al., 2000), an examination of the behavioral correlates of RT variability using continuous behavioral observations provides the opportunity to increase our understanding of RT variability. The current study sought to build on the results reported by Epstein et al. (2011a). In this study, children with and without ADHD completed five computerized tasks, which tapped into various aspects of executive functioning. Analyses focused on group differences for a variety of reaction time performance indicators from these five tasks. Results indicated that children with ADHD had greater values of Ex-gaussian tau and the coefficient of variation (RTSD ÷ RT mean) than controls across all five tasks. In addition, group differences in accuracy were found on some of the tasks. No group differences were found for mu or sigma on any of the tasks (all ps ≤ .05). Along with completing the computerized tasks, participants also completed a math test, during which they were video-recorded. examined the relationship between indicators of RT variability on five neuropsychological tests and on-task behavior during an analogue math task among children with and without ADHD. We also included additional alternative neuropsychological indicators in order to examine whether the relationship between neuropsychological functioning and observed behavior was specific to RT variability.