Annual Research Review: Reaction time variability in ADHD and autism spectrum disorders: measurement and mechanisms of a proposed trans‐diagnostic phenotype

May combine two claims.

In the new meta-analysis, the pooled effect size for direct ASD versus ADHD comparisons was g = −0.17 (SE = 0.13; 95% CI −0.43 to 0.09; p = .207), indicating that children with ADHD were nonsignificantly more variable than children with ASD.

“The pooled ES for the 10 studies reporting direct comparisons of ASD (N = 455) versus ADHD (N = 426) groups was g = −0.17 (SE = 0.13; 95% CI: −0.43 to 0.09; p = .207), indicating that children with ADHD were nonsignificantly more variable than children with ASD.”

May combine two claims.

In the new meta-analysis, the ADHD-Control pooled effect size for the 10 studies reporting this comparison was g = 0.37 (SE = 0.15; 95% CI 0.17-0.66; p = .015), indicating small to moderate increases in RT variability in ADHD samples compared to non-ADHD controls in studies that also included an ASD group.

“The ADHD-Control pooled ES (total NADHD = 426, Ncontrol = 1,065) was g = 0.37 (SE = 0.15; 95% CI: 0.17–0.66; p = .015), indicating small to moderate increases in RT variability in the ADHD samples as compared to non-ADHD controls in studies that also included an ASD group.”

May combine two claims.

Exclusion of comorbid ADHD significantly moderated the ASD-Control effect size (p = .043), with a smaller effect for studies excluding ADHD (g = 0.15, SE = 0.15, p = .341) than for those not excluding ADHD (g = 0.52, SE = 0.10, p < .001).

“Exclusion of ADHD significantly moderated the ES (p = .043) with a smaller ES for studies that excluded ADHD (g = 0.15, SE = 0.15, p = .341) than for those that did not (g = 0.52, SE = 0.10, p < .001).”

• AssumptionThe authors state this as an assumption: For studies with no information on ADHD exclusion, the meta-analysis assumed that they did not exclude ADHD.

May combine two claims.

Quality of ASD diagnosis significantly moderated the ASD-Control effect size (p = .048), with low quality diagnostic procedures yielding a larger effect (g = 0.63, SE = 0.16) than high quality procedures (g = 0.24, SE = 0.11).

“Quality of the ASD diagnosis (coded as either “High Quality,” including observational schedules and clinical interviews given individually or in combination, and “Low Quality,” including prior clinical diagnosis and diagnosis based on rating scales only) significantly moderated the size of effect observed (p = .048).”

• Also stated in: § Moderators of between-study heterogeneity for ASD-control group comparisons · plain

  “Studies relying on Low Quality diagnostic procedures had larger ESs (g = 0.63, SE = 0.16) than those relying on High Quality diagnostic procedures (g = 0.24, SE = 0.11).”

May combine two claims.

In the new meta-analysis, the pooled effect size for ASD versus typically developing controls was g = 0.37 (SE = 0.09; 95% CI 0.19-0.55; p < .001), indicating that individuals with ASD were significantly more variable with a small to moderate effect.

“The pooled ES for the ASD-Control group comparison (total NASD = 455, Ncontrol = 1065) was g = 0.37 (SE = 0.09; 95% confidence interval [CI]: 0.19–0.55; p < .001), indicating that individuals with ASD were significantly more variable than typically developing controls but with a small to moderate ES.”

May combine two claims.

All studies excluding ADHD from the ASD sample also used high quality diagnostic procedures for ASD, so the effects of diagnostic quality and ADHD exclusion cannot be separated.

“All studies excluding ADHD from the ASD sample also used “High Quality” diagnostic procedures for diagnosing ASD, so the effects of diagnostic quality and ADHD exclusion cannot be separated.”

May combine two claims.

Meta-regression found that age, sample gender composition, and IQ were not related to observed effect sizes for ASD-Control comparisons (all p > .302).

“Meta-regression analyses indicated that age, sample gender composition (% male), and IQ were not related to the observed ESs for the ASD-Control group comparisons (all p > .302).”

May combine two claims.

RT variability in ADHD is explained by moderate to large increases (d = 0.63-0.99) in the ex-Gaussian parameter τ and the diffusion parameter drift rate, as well as by smaller differences (d = 0.32) in the diffusion parameter of nondecision time.

“Furthermore, RT variability in ADHD is explained by moderate to large increases (d = 0.63–0.99) in the ex-Gaussian parameter τ and the diffusion parameter drift rate, as well as by smaller differences (d = 0.32) in the diffusion parameter of nondecision time.”

May combine two claims.

The magnitude of RT variability effects in ADHD, with or without ASD, is moderate and similar to that of other cognitive measures in these disorders.

“ESs for RT variability for ADHD (with or without ASD) remain moderate, and similar in size to other cognitive measures in these disorders”

May combine two claims.

In ADHD, variability in reaction time is accounted for by occasional extremely slow responses (tau) and by slow drift rate, and less so by faster nondecision times.

“RT variability in ADHD is explained by very slow RTs on some trials (τ parameter) and by slow drift rate, as well as to a lesser extent by faster nondecision times”

May combine two claims.

After accounting for age, Kofler et al. (2013) found no significant unexplained between-study variance in effects, suggesting other sample or task characteristics were not required to explain between-study differences.

“After accounting for participants’ age, there was no significant unexplained between-study variance in effects, suggesting that other sample characteristics (e.g. gender) or task characteristics (e.g. duration, inhibitory control demands) were not required to explain between-study differences in the size of effects”

• cites Kofler et al., 2013Not checked yet

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May combine two claims.

Kofler et al. (2013) found that RT variability effects were attenuated by stimulant treatments but were unaffected by nonstimulant and psychosocial treatments.

“Kofler et al. (2013) also found that RT variability effects were attenuated by stimulant treatments, but they were unaffected by nonstimulant and psychosocial treatments.”

• cites Kofler et al., 2013Not checked yet

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May combine two claims.

Overall, the ADHD RT variability literature shows a reliable association of RT variability with ADHD that is to a small extent distinct from other conditions in aggregate.

“Overall, the literature on ADHD and RT variability is large, has been reduced by meta-analysis, and shows a reliable association of RT variability to ADHD that is to a small extent distinct from other conditions in aggregate.”

May combine two claims.

For the set of studies with an ASD group, the ADHD-Control effect size was similar to the ASD-Control effect size and smaller than in larger ADHD meta-analyses.

“Thus, for this group of studies, ES was similar for ADHD and ASD and obviously somewhat smaller than that seen in the larger population of studies in meta-analyses that could ignore ASD.”

May combine two claims.

The pooled ASD-Control effect size (g = 0.37, or g = 0.15 excluding comorbid ADHD) is smaller than previously found in ADHD using a larger sample of studies (0.72-0.85).

“Of note, the pooled ES for the ASD-control group comparison (g = 0.37, and g = 0.15 if samples with comorbid ADHD are excluded) is smaller than has previously been found in ADHD using a larger sample of studies (0.72– 0.85, Klein et al., 2006; Kofler et al., 2013; Lijffijt et al., 2005; Metin et al., 2012);”

• cites Klein et al., 2006Not checked yet

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• cites Kofler et al., 2013Not checked yet

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• cites Lijffijt et al., 2005Not checked yet

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The quote only partly states this claim.

Funnel plots showed no evidence of publication bias for the ASD versus ADHD comparison.

“Funnel plots showed no evidence of publication bias.”

May combine two claims.

Standard statistics using SDRT assume that RTs fit a Gaussian distribution, but RT distributions are nearly always positively skewed.

“Second, standard statistics using SDRT assume that RTs fit a Gaussian (normal) distribution, but in fact RT distributions are nearly always positively skewed to some extent (see Figure 3 for example).”

May combine two claims.

Gaussian measures do not accurately reflect the shape of RT distributions and are underpowered to detect group differences.

“Because Gaussian measures do not accurately reflect the shape of RT distributions, they are underpowered to detect group differences (Ratcliff, 1993).”

• cites Ratcliff, 1993Not checked yet

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May combine two claims.

No specific frequency band drives RT variability in ADHD, and no consistent predictable time course of long RTs can be identified within the studied RT bands.

“suggesting that no specific frequency band drives RT variability in ADHD and that no consistent, predictable time course of long RTs can be identified within the RT bands studied.”

May combine two claims.

Ex-Gaussian decomposition can handle skewed RT distributions and model them more accurately than a regular Gaussian RT variability analysis.

“Ex-Gaussian decomposition can handle skewed RT distributions and model them more accurately than a regular Gaussian RT variability analysis.”

May combine two claims.

The ex-Gaussian τ and drift-rate increases may suggest problems in state regulation or arousal and difficulty detecting signal from noise, whereas the nondecision-time difference may reflect contributions from deficits in motor organization or output.

“The former may suggest problems in state regulation or arousal and difficulty detecting signal from noise, whereas the latter may reflect contributions from deficits in motor organization or output.”

• AssumptionRests on an assumption: RT variability is determined by multiple cognitive processes, including stimulus encoding, speed of information processing, speed-accuracy trade-offs, post-error slowing, motor preparation, and response execution.

May combine two claims.

The pooled effect size for τ is based on a small number of studies and has a wide confidence interval, so the conclusions could be overturned with additional study.

“However, the pooled ES for τ is based on a small number of available studies and there is a wide CI around the effect. So, these conclusions could be overturned with additional study, or, more notably, it may emerge that τ is reliably more sensitive than SDRT when more studies are available to pool.”

May combine two claims.

The neuroimaging literature converges with the multicomponent interpretation and highlights the role of top-down control circuits.

“The neuroimaging literature converges with this multicomponent interpretation and also highlights the role of top-down control circuits.”

• AssumptionRests on an assumption: RT variability is determined by multiple cognitive processes, including stimulus encoding, speed of information processing, speed-accuracy trade-offs, post-error slowing, motor preparation, and response execution.

May combine two claims.

Decomposition of the RT signal provides superior interpretive power and suggests mechanisms convergent with those implicated using other cognitive paradigms.

“We underscore the importance of considering the interactions between top-down control, state regulation (e.g. arousal), and motor preparation when interpreting RT variability and conclude that decomposition of the RT signal provides superior interpretive power and suggests mechanisms convergent with those implicated using other cognitive paradigms.”

• AssumptionRests on an assumption: RT variability is determined by multiple cognitive processes, including stimulus encoding, speed of information processing, speed-accuracy trade-offs, post-error slowing, motor preparation, and response execution.

Classified as probably not a substantial claim.

RT variability has been explicitly proposed as a trans-diagnostic phenotype that indexes shared risk for ADHD and ASD.

“and RT variability has been explicitly proposed as a trans-diagnostic phenotype that indexes shared risk for these disorders (Rommelse, Geurts, Franke, Buitelaar, & Hartman, 2011).”

• cites Rommelse et al., 2011Not checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing).

The opposite interpretation of τ, that it primarily reflects motor processes, has also been made.

“precisely the opposite interpretation of τ, that it primarily reflects motor processes, has also been made (see Matzke & Wagenmakers, 2009)”

• cites Matzke & Wagenmakers, 2009Not checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing).

The ex-Gaussian parameter τ is commonly interpreted as reflecting attention lapses.

“The ex-Gaussian parameter τ is commonly interpreted as reflecting “attention lapses””

• cites de Kieviet et al., 2012Not checked yet

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• cites Sonuga-Barke & Castellanos, 2007Not checked yet

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• cites Unsworth et al., 2009Not checked yet

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Probably not a substantial claim: may not pass S1 (asserted), S3 (load-bearing).

Faster nondecision times in ADHD indicate differences in motor processing in this population.

“our hypothesis would be that faster nondecision times indicate differences in motor processing in this population.”

• cites Carte, Nigg, & Hinshaw, 1996Not checked yet

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• cites Sergeant & Scholten, 1985Not checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing).

Older work suggested that τ reflects higher-order decision processing while μ and σ index motor response.

“older work suggesting that τ reflects higher-order decision processing while μ and σ index motor response (Hohle, 1965)”

• cites Hohle, 1965Not checked yet

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The quote only partly states this claim.

Slow drift rate may be consistent with classic theories of ADHD emphasizing a deficit in cortical arousal or disruption in ascending noradrenergic neural systems that facilitate signal detection.

“slow drift rate may be consistent with classic theories of ADHD emphasizing a deficit in cortical “arousal””

• cites Satterfield, Cantwell, & Satterfield, 1974Not checked yet

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• cites Zentall & Zentall, 1983Not checked yet

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• cites McCracken, 1991Not checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing).

The diffusion model conceptualizes drift rate as an RT counterpart to a signal detection model of accuracy.

“the diffusion model conceptualizes drift rate as an RT counterpart to a signal detection model of accuracy.”

May combine two claims.

The drift rate parameter in the diffusion model is linked conceptually to neural noise, with slower drift rate indicative of a low signal-to-noise ratio in neural circuits underlying decision-making.

“the drift rate parameter in the diffusion model is linked conceptually to neural noise, with slower drift rate (i.e. slower, less efficient information processing) indicative of a low signal-to-noise ratio in neural circuits underlying decision-making”

• cites Ratcliff, Cherian, & Segraves, 2003Not checked yet

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• cites Ratcliff, Philiastides, & Sajda, 2009Not checked yet

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• cites Ratcliff & Rouder, 1998Not checked yet

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May combine two claims.

In ASD, both under- and over-arousal are reported, leaving the main trend unclear.

“in ASD both under- and over-arousal are reported, leaving the main trend unclear”

• cites Geurts et al., 2009Not checked yet

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• cites Raymaekers et al., 2004Not checked yet

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• cites Raymaekers et al., 2006Not checked yet

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Classified as probably not a substantial claim.

Within a signal detection framework, d′ is often interpreted as an index of arousal.

“Within a signal detection framework, d′ is often interpreted as an index of arousal”

• cites van der Meere & Sergeant, 1988Not checked yet

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• cites Sergeant, Oosterlaan, & van der Meere, 1999Not checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Attention includes components such as filtering, alerting/arousal, orienting, and executive control.

“which includes components like filtering, alerting/arousal, orienting, and executive control”

• cites Deutsch & Deutsch, 1963Not checked yet

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• cites Fan et al., 2002Not checked yet

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• cites Treisman, 1964Not checked yet

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Probably not a substantial claim: may not pass S1 (asserted), S3 (load-bearing), S4 (based).

Elevated tonic LC activity is also associated with slower drift rate.

“and thus, we would hypothesize, is also associated with slower drift rate”

Probably not a substantial claim: may not pass S3 (load-bearing).

Cognitive neuroscientists disagree as to whether executive control is handled by one or two neural networks.

“cognitive neuroscientists disagree as to whether executive control is handled by one or two neural networks”

• cites Carter & Krug, 2012Not checked yet

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• cites Petersen & Posner, 2012Not checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing).

Arousal and alerting have historically been associated with a right-hemisphere fronto-parietal-thalamic-brainstem network modulated by the norepinephrine system.

“Arousal and alerting have historically been associated with a right-hemisphere fronto-parietal-thalamic-brainstem network modulated by the norepinephrine (NE) system”

• cites Pardo, Fox, & Raichle, 1991Not checked yet

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• cites Posner & Petersen, 1990Not checked yet

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• cites Sturm et al., 2004Not checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Both alerting/arousal and executive control functions of attention have been suggested as putative contributors to RT variability.

“Both the alerting/arousal and executive control functions of attention have been suggested as putative contributors to RT variability”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Executive control of attention is required for suppressing interference, handling response conflict, complex working memory, and top-down regulation of arousal and motivation.

“Executive control of attention is required for suppressing interference, handling response conflict, complex working memory, and top-down regulation of arousal and motivation.”

May combine two claims.

Two fMRI studies in ADHD demonstrated that children with ADHD showed greater RT variability and reduced brain activity in the right-sided anterior cingulate gyrus.

“Two fMRI studies in ADHD demonstrated that children with ADHD showed greater RT variability and reduced brain activity in the right-sided anterior cingulate gyrus (Konrad, Neufang, Hanisch, Fink, & Herpertz-Dahlmann, 2006)”

• cites Konrad et al., 2006Not checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Posner and Petersen noted two distinct functions: phasic alerting to a stimulus and tonic sustaining of attention (vigilance).

“Posner and Petersen (1990) noted two distinct functions: phasic alerting to a stimulus and tonic sustaining of attention to the stimulus, which they called vigilance.”

• cites Posner & Petersen, 1990Not checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing).

In the Petersen-Posner perspective, the brain is organized by modular interconnected networks responsible for distinct attentional functions including orienting, alerting (arousal), and executive control.

“the brain is organized by modular interconnected networks responsible for distinct attentional functions including orienting, altering (arousal), and executive control.”

• cites Petersen & Posner, 2012Not checked yet

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• cites Posner & Petersen, 1990Not checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing).

The perspective that argues for two networks proposes a fronto-parietal task network involved in initial onset of task control.

“proposes that a fronto-parietal task network includes lateral frontal and parietal nodes, and is involved in the initial onset of task control.”

• cites Dosenbach et al., 2008Not checked yet

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• cites Petersen & Posner, 2012Not checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing).

RT variability has been discussed as a general indicator of the integrity of brain networks.

“RT variability has been discussed as a general indicator of the integrity of brain networks”

• cites MacDonald, Li, & Bäckman, 2009Not checked yet

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May combine two claims.

A wide range of correlated brain patterns have been associated with RT variability in normal adult populations, making it difficult to identify a single brain mechanism implicated in RT variability in ADHD specifically.

“Thus, a wide range of correlated brain patterns have been associated with RT variability in normal adult populations, and it is difficult to use that literature to identify a single brain mechanism being implicated in RT variability in ADHD, specifically.”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

The alerting network is responsible for establishing and maintaining an alert state suitable to task demands, as well as enhancing the signal:noise ratio for novelty detection.

“The alerting network is responsible for establishing and maintaining an alert state suitable to task demands, as well as enhancing the signal:noise ratio for novelty detection.”

May combine two claims.

Within this framework, phasic release of NE via the locus coeruleus is associated with optimal decision-making and task performance, whereas less phasic and greater tonic LC activation produces a less optimized and more distractible behavioral pattern.

“Within this framework, phasic release of NE (via the locus coeruleus [LC]) is associated with optimal decision-making and task performance, whereas less phasic and greater tonic LC activation produces a less optimized and more distractible behavioral pattern.”

May combine two claims.

Elevated tonic LC activity is associated with both lower d′ and lowered response thresholds.

“Elevated tonic LC activity is associated with both lower d′ (signal detection in an accuracy task, such as the continuous performance task) and lowered response thresholds”

• cites Aston-Jones, Rajkowski, Kubiak, & Alexinsky, 1994Not checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing).

Maintaining task set over time is handled by a cingulo-opercular network including medial PFC, dorsal anterior cingulate, dorsal anterior prefrontal cortex, lateral frontal pole, and anterior insula.

“Maintaining task set over time is handled by a second network, termed the cingulo-opercular network, which includes medial PFC, dorsal anterior cingulate, dorsal anterior prefrontal cortex, lateral frontal pole, and anterior insula.”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

The cingulo-opercular network is likely involved in many other functions, but its putative role in maintaining task set seems relevant to RT variability.

“The cingulo-opercular network is likely involved in many other functions (such as task switching), but here we highlight its putative role in maintaining task set—a function that would seem relevant to RT variability.”

Probably not a substantial claim: may not pass S3 (load-bearing).

The default-mode network includes the precuneus/posterior cingulate cortex, medial prefrontal cortex, and medial, lateral, and inferior parietal cortex.

“The default-mode network includes the precuneus/posterior cingulate cortex (PCC), the medial prefrontal cortex and the medial, lateral, and inferior parietal cortex”

• cites Laird et al., 2009Not checked yet

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• cites Schilbach et al., 2008Not checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing).

Activity in the default-mode network is attenuated, although not extinguished, during the transition from rest-to-task states.

“Activity in the default-mode network is attenuated, although not extinguished, during the transition from rest-to-task states”

• cites Eichele et al., 2008Not checked yet

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• cites Greicius et al., 2004Not checked yet

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• cites Raichle et al., 2001Not checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing).

Stronger deactivation of the default-mode network is associated with increased task difficulty.

“Stronger deactivation is associated with increased task difficulty (Singh & Fawcett, 2008)”

• cites Singh & Fawcett, 2008Not checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing).

The default-mode network activates when task control is relaxed.

“it activates when task control is relaxed”

• cites Andrews-Hanna, 2012Not checked yet

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• cites Christoff et al., 2009Not checked yet

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• cites Spreng, 2012 sourceNot checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing).

The authors of that study suggest the pattern of activation may implicate motor output functions.

“The authors suggest that in this case the pattern of activation may implicate motor output functions”

• cites Rubia et al., 2007Not checked yet

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May combine two claims.

The exact nature of default-mode network abnormalities in both ADHD and ASD remains unclear, with both hyper- and hypo-activation variously found.

“the exact nature of default-mode network abnormalities in both ADHD (Konrad & Eickhoff, 2010) and ASD (Minshew & Keller, 2010), remains unclear with both hyper- and hypo-activation variously found”

• cites Konrad & Eickhoff, 2010Not checked yet

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• cites Minshew & Keller, 2010Not checked yet

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May combine two claims.

Both ADHD and ASD have been associated with alterations in the power spectra in EEG signal.

“Both ADHD and ASD have been associated with alterations in the power spectra in EEG signal”

• cites Barry, Johnstone, & Clarke, 2003Not checked yet

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• cites Broyd, Helps, & Sonuga-Barke, 2011Not checked yet

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May combine two claims.

Higher power in fast frequencies (e.g., beta band) is indicative of high arousal, while higher power in slow frequencies (e.g., theta band) is indicative of low arousal.

“higher power in fast frequencies (e.g. the beta band) is indicative of high arousal, while higher power in slow frequencies (e.g. theta band) is indicative of low arousal”

• cites Arns, Conners, & Kraemer, 2013Not checked yet

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• cites Pizzagalli, 2007Not checked yet

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May combine two claims.

Both ADHD and ASD have been associated with alterations in ERP markers.

“and with alterations in ERP markers (Johnstone, Barry, & Clarke, 2012)”

• cites Johnstone et al., 2012Not checked yet

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May combine two claims.

Because P300 depends on attention deployment, it is thought to represent the allocation of executive control resources to the task.

“Because P300 depends on attention deployment, it is thought to represent the allocation of executive control resources to the task (Polich, 2007).”

• cites Polich, 2007Not checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing).

ITC is thought to be related to the temporal stability of information processing in traditional evoked response potentials.

“ITC is thought to be related to the temporal stability of information processing (i.e. latency variability) in traditional evoked response potentials.”

May combine two claims.

Results from EEG and ERP studies are broadly consistent with those using functional MRI approaches, and provide some evidence for both arousal and executive control contributions to RT variability.

“Taken together, results from EEG and ERP studies are broadly consistent with those using functional MRI approaches, and provide some evidence for both arousal and executive control contributions to RT variability.”

Classified as probably not a substantial claim. May combine two claims.

The P300 is believed to reflect working memory updating and the decision about which is the correct response.

“The ‘P300’ is believed to reflect working memory updating and the decision about which is the correct response (Verleger, 1997).”

• cites Verleger, 1997Not checked yet

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Classified as probably not a substantial claim.

Intertrial phase coherence (ITC) is a measure of the degree to which the phase of frequency-domain evoked responses aligns across trials, independently of amplitude.

“the EEG measure of intertrial phase coherence (ITC) is a measure of the degree to which the phase (or timing) of the frequency-domain evoked responses aligns across trials, independently of amplitude”

• cites Delorme & Makeig, 2004Not checked yet

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• cites Groom et al., 2010Not checked yet

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• cites Makeig et al., 2004Not checked yet

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May combine two claims.

Contingent negative variation can index cortical activation either as an orienting reaction (early CNV) or as preparation for rapid motor execution (late CNV).

“contingent negative variation (CNV), one example of a slow cortical potential, can be an index of cortical activation in terms of either an orienting (initial alerting) reaction (early CNV) or preparation of a rapid execution of the motor response (late CNV).”

Probably not a substantial claim: may not pass S3 (load-bearing).

Several measures of brain signal complexity on EEG or MRI have been applied in the study of RT variability, although not yet within the context of ADHD or ASD.

“several measure of brain signal complexity on EEG or MRI have also been applied in the study of RT variability, although not yet within the context of ADHD or ASD (Garrett et al., 2013).”

• cites Garrett et al., 2013Not checked yet

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May combine two claims.

Networks formed under greater noise are more resistant to disruption, which enhances learning and environmental adaptation and helps sustain optimal performance.

“connectionist and cellular research suggest that networks formed in the presence of greater noise are more robust to disruption, thus enhancing learning and environmental adaptation, and helping to maintain optimal performance”

• cites Basalyga & Salinas, 2006Not checked yet

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• cites Faisal, Selen, & Wolpert, 2008Not checked yet

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Probably not a substantial claim: may not pass S1 (asserted).

Children with ADHD may recruit prefrontal regions to compensate for less efficient premotor system use.

“leading to the hypothesis that children with ADHD may recruit prefrontal regions to compensate for less efficient use of premotor systems.”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Arousal modulates early processing stages such as stimulus encoding and is linked to phasic neural activity.

“Arousal modulates early stages of processing (such as stimulus encoding) and is related to phasic neural activity.”

May combine two claims.

In children with ADHD during the same task, greater pre-SMA activation is associated with more RT variability, and greater prefrontal activation with less RT variability.

“a reverse brain activation pattern was observed in children with ADHD during the identical task with increased pre-SMA activation associated with more RT variability and greater prefrontal activation associated with less RT variability in the patients’ group (Suskauer et al., 2008).”

• cites Suskauer et al., 2008Not checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Activation influences response preparation and motor output and is hypothesized to relate to tonic neural activation.

“Activation influences response preparation and motor output and is hypothesized to be related to tonic neural activation (Sergeant, 2000).”

• cites Sergeant, 2000Not checked yet

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Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing). May combine two claims.

The findings allow competing interpretations but show some convergence with the summarized cognitive studies.

“Findings are amenable to competing interpretations, but have some convergence with the cognitive studies summarized.”

Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

How top-down circuits interact with arousal or motor response networks in ADHD remains poorly understood.

“The interaction of top-down circuits with arousal or motor response networks in ADHD remains poorly understood.”

May combine two claims.

In typically developing children performing a go/no-go task, lower RT variability is associated with premotor circuit activation, while higher RT variability is associated with prefrontal circuit activation.

“Using fMRI in typically developing children, less RT variability on a go/no-go task was associated with activation in premotor circuits, and more RT variability was associated with activation in prefrontal circuits (Simmonds et al., 2007).”

• cites Simmonds et al., 2007Not checked yet

  Not checked in the free run.

Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based). May combine two claims.

The interaction between prefrontal and premotor circuits is not necessarily linear and may include compensatory effects.

“The interplay of PFC and premotor, as well as other circuits, is not necessarily linear but can include compensatory effects.”

May combine two claims.

SDRT in ADHD has been correlated with breakdowns in top-down control circuits, with arousal state measures, and with neural measures of motor preparation.

“SDRT in ADHD has been correlated with breakdowns in top-down control circuits, with measures of arousal states, and with neural measures of motor preparation”

Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based). May combine two claims.

Convergence in understanding neural correlates of RT variation components such as drift rate, tau, or nondecision times appears achievable over time and should help clarify mechanisms.

“convergence in understanding neural correlates, particularly of components of RT variation like drift rate, τ, or nondecision times appears tractable over time, and should help elucidate mechanisms.”

Classified as probably not a substantial claim.

The CEM proposes that task performance is affected by three distinct, hierarchically organized energetic pools: effort, arousal, and activation.

“the CEM suggests that task performance is affected by three distinct, hierarchically organized energetic pools: effort, arousal, and activation.”

May combine two claims.

The CEM has influenced the ADHD field more than other models and is often cited in papers interpreting RT variability findings.

“it has had a greater influence to-date on the ADHD field than other models and is frequently cited in papers attempting to interpret RT variability findings.”

Probably not a substantial claim: may not pass S3 (load-bearing).

The CEM addresses the coordination of bottom-up and top-down processes needed for optimal performance on attention-demanding tasks.

“also speaks to the coordination of bottom-up and top-down processes required for optimal performance on attention-demanding tasks.”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Dynamic causal modeling depends on model comparisons for causal inference, so its conclusions require careful interpretation.

“even these advanced models rely on model comparisons to make causal inferences, and so conclusions need to be interpreted carefully.”

• cites Friston, Harrison, & Penny, 2003Not checked yet

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• cites Smith et al., 2011Not checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

The cognitive-energetic model is an influential state-regulation model used in ADHD research and, less so, in ASD research.

“The cognitive-energetic model (CEM) is an influential state-regulation model applied in the ADHD literature (Sergeant, 2000; Sergeant et al., 1999), and, to a lesser extent in the ASD literature.”

• cites Sergeant, 2000Not checked yet

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• cites Sergeant et al., 1999Not checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing).

The effort pool is hypothesized to be regulated in a top-down manner by an executive management system.

“The effort pool is hypothesized to be further regulated in a top-down manner by an “executive management” system (Sergeant, 2000)”

• cites Sergeant, 2000Not checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

The effort pool feeds the other energetic pools and drives central decision-making processes.

“The effort pool feeds each of the other energetic pools and drives central decision-making (computational) processes.”

Probably not a substantial claim: may not pass S3 (load-bearing).

The authors regard the CEM executive management system as similar to top-down executive or cognitive control systems.

“which we take to be similar to the top-down executive or cognitive control systems pointed out by Petersen and Posner and many other authors.”

May combine two claims.

Only a subset of children in either population show increased RT variability, or RT variability is quite distant from pathophysiology.

“suggesting that only a subset of children in either population are characterized by increased RT variability or that it is quite distant from pathophysiology.”

May combine two claims.

The evidence indicates that RT variability effects are somewhat specific to ADHD and to a subgroup of children with comorbid ASD and ADHD.

“The data so far at hand suggest some specificity of RT variability effects to ADHD and a subgroup of children with comorbid ASD and ADHD.”

• Also stated in: § Conclusions · hedged

  “RT variability shows some specificity to ADHD, including to a subset of children with ASD who share comorbid ADHD diagnosis”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

In the CEM, the arousal energetic pool primarily affects stimulus encoding and is related to phasic NE release.

“the “arousal” energetic pool from a CEM perspective primarily affects stimulus encoding and is related to phasic NE release based on related earlier work by Pribram and McGuinness (1975).”

• cites Pribram and McGuinness, 1975Not checked yet

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May combine two claims.

In Aston-Jones and Cohen, phasic NE release is empirically linked to central decision processing, which the CEM aligns more closely with effort.

“the phasic NE release that defines part of the “arousal” function as discussed by Aston-Jones and Cohen (2005) is empirically linked to central decision processing, a function that the CEM more closely aligns with “effort.””

• cites Aston-Jones and Cohen, 2005Not checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing).

Studies of cognitive deficits in ADHD using a CEM perspective have been interpreted as supporting activation or effort deficits more consistently than arousal deficits.

“studies of cognitive deficits in ADHD using a CEM perspective have been interpreted as supporting deficits in activation or effort more consistently than deficits in arousal.”

Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

All cognitive tasks require optimal management of all three energetic pools for optimal performance.

“Given that all cognitive tasks require optimal management of all three energetic pools for optimal performance”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Person-centered approaches that identify subgroups of children sharing features are just beginning to be applied to cognitive profiles in ADHD, but have not yet been applied in ASD literature or mixed diagnostic samples.

“person-centered approaches that can identify subgroups of children who share features are just beginning to be applied to cognitive profiles (e.g. using graph theory community detection approach, Fair, Bathula, Nikolas, & Nigg, 2012), but have not yet been applied with the ASD literature or within samples containing children with a range of diagnostic designations”

• cites Fair, Bathula, Nikolas, & Nigg, 2012Not checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing).

The CEM has some parallels with the attention models used to guide the discussion of neural findings.

“the CEM does have some parallels to the attention models used to guide our discussion of neural findings.”

Probably not a substantial claim: may not pass S3 (load-bearing).

Evidence suggests that reward incentives may help normalize default network activation in ADHD.

“evidence that reward incentives may help normalize default network activation in ADHD may suggest that this network corresponds inversely to the effort construct in the CEM framework (Liddle et al., 2011)”

• cites Liddle et al., 2011Not checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing).

The exact correspondence between terminologies used in different models is not entirely clear.

“the precise correspondence in the terminologies applied in different models is not entirely clear.”

May combine two claims.

In the CEM, event rate manipulations on high motor output tasks are interpreted as activation, while event rate increases on perceptually demanding tasks are interpreted as arousal changes.

“manipulating event rates on tasks with high motor output demands (e.g. go/no go tasks) is interpreted in terms of activation, whereas increasing event rates on tasks with greater perceptual demands (e.g. continuous performance tests) is interpreted in terms of changes in arousal (Sergeant et al., 1999).”

• cites Sergeant et al., 1999Not checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Aston-Jones and Cohen hypothesize that the balance of tonic and phasic NE release relates to perceived task utility, which may be determined partly by reward contingencies and executive considerations.

“Aston-Jones and Cohen (2005) hypothesize that the balance of tonic and phasic NE release is related to perceived task utility, which may be determined, in part, by reward contingencies as well as by executive (strategic) considerations.”

• cites Aston-Jones and Cohen, 2005Not checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Findings from both studies may be consistent with the idea that motor output processes relate to mean RT differences in ADHD but less so to RT variability.

“findings in both studies may actually be consistent with the suggestion that motor output processes (indicated by event rate measures of activation and nondecision times) are related to mean RT differences in ADHD but less so to RT variability.”

May combine two claims.

A recent meta-analysis found no evidence of event rate effects on SDRT in go/no-go tasks, although it found effects on other performance variables such as mean RT.

“a recent meta-analysis (Metin et al., 2012) found no evidence of event rate effects on SDRT in go/no-go tasks despite finding effects on other performance variables, such as mean RT.”

• cites Metin et al., 2012Not checked yet

  Not checked in the free run.

Probably not a substantial claim: may not pass S3 (load-bearing).

The CEM suggests that cognitive performance depends on the individual's state regulation in response to perceived strategic value.

“the CEM, which similarly suggests that cognitive performance is dependent on the state of the individual (i.e. their regulation of state in response to perceived strategic value).”

Classified as probably not a substantial claim.

The relationship between RT variability and other cognitive measures such as working memory, attention, or inhibition remains unclear.

“RT variability’s relationship to other measures of cognitive processing, such as working memory, attention, or inhibition remains unclear.”

Probably not a substantial claim: may not pass S1 (asserted). May combine two claims.

RT variability may mediate deficits in other cognitive domains or reflect a distinct cognitive problem.

“It may mediate deficits in these other cognitive domains (Karalunas & Huang-Pollock, 2013) or reflect a distinct cognitive problem”

• cites Karalunas & Huang-Pollock, 2013Not checked yet

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Classified as probably not a substantial claim.

RT variability may reflect different antecedents depending on task, practice, and time scale.

“RT variability may reflect different antecedents depending on task, practice (Allaire & Marsiske, 2005), and time scale (Schmiedek et al., 2009).”

• cites Allaire & Marsiske, 2005Not checked yet

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• cites Schmiedek et al., 2009Not checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing).

Arousal can be assessed through peripheral nervous system measures such as skin conductance and pre-ejection period.

“Processes such as arousal can be assessed via peripheral nervous system measures of skin conductance and pre-ejection period (Berntson, Quigley, & Lozano, 2007; Dawson, Schell, & Filion, 2007).”

• cites Berntson, Quigley, & Lozano, 2007Not checked yet

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• cites Dawson, Schell, & Filion, 2007Not checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing).

Dynamic causal modeling has not yet been applied to the study of RT variability.

“contemporary models, such as dynamic causal modeling (Friston et al., 2003; Smith et al., 2011), have yet to be applied to the study of RT variability.”

• cites Friston et al., 2003Not checked yet

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• cites Smith et al., 2011Not checked yet

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May combine two claims.

Diffusion model parameters have somewhat clearer cognitive interpretations but cannot easily be applied to tasks other than forced two-choice paradigms, leaving out many clinical tasks.

“diffusion model parameters have somewhat clearer cognitive interpretations, but cannot easily be applied to tasks other than forced two-choice paradigms, which leaves out many tasks commonly used in the clinical literature.”

May combine two claims.

Neuroimaging findings align with this behavioral account and emphasize considering how top-down control networks interact with arousal and motor preparation networks.

“The neuroimaging literature converges with this picture and highlights the importance of considering the interaction of top-down control networks with those involved in arousal and motor preparation.”

May combine two claims.

Ex-Gaussian models can be applied to many task types, but they do not account for response accuracy and their parameter interpretations remain unclear.

“Ex-Gaussian models can be applied to a wide range of task types, however, they do not take into account response accuracy and the cognitive interpretation of parameters remains unclear.”

Classified as probably not a substantial claim.

It is unlikely that RT variability reflects a single unitary cognitive mechanism.

“It seems unlikely that RT variability reflects one unitary cognitive mechanism.”

Classified as probably not a substantial claim.

Grouping individuals who share the common feature of RT variability may not reduce within-group heterogeneity.

“grouping individuals who share the common feature of RT variability, as suggested above, may not reduce within-group heterogeneity.”

Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

In both ex-Gaussian and diffusion models, defining and eliminating outlier data points can be somewhat arbitrary.

“In both cases, defining and eliminating outlier data points can be somewhat arbitrary.”

Probably not a substantial claim: may not pass S3 (load-bearing).

Peripheral nervous system measures have rarely been studied together with RT variability.

“Peripheral nervous system measures have only rarely been studied in conjunction with RT variability (but see for example Börger et al., 1999; Sroufe, Sonies, West, & Wright, 1973)”

• cites Börger et al., 1999Not checked yet

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• cites Sroufe, Sonies, West, & Wright, 1973Not checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

Faster nondecision times may be related to inefficient motor organization.

“which may be related to inefficient motor organization.”

May combine two claims.

Alternative analysis approaches have not increased measurement sensitivity in ADHD, but they have helped characterize how RT distributions differ and narrowed the focus for future neuroimaging work.

“Alternative analysis approaches have not increased measurement sensitivity (at least in ADHD), but have helped characterize specific ways in which RT distributions differ and narrowed the focus as a target for future neuroimaging work.”