Dataset Information

Ex-Gaussian, Frequency and Reward Analyses Reveal Specificity of Reaction Time Fluctuations to ADHD and Not Autism Traits.

ABSTRACT: Both attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) have been linked to increased reaction time variability (RTV), a marker of attentional fluctuation. Here we test whether specificity to either trait emerges when we examine (1) detailed ex-Gaussian and frequency RTV subcomponents, (2) effects while controlling for the other trait and (3) improvement in the RTV measures following rewards or a faster event rate. 1110 children aged 7-10 years from a population-based sample completed a Go/No-Go task under three conditions (slow, fast and incentives). We measured RTV with standard deviation of RT (SDRT), ex-Gaussian distribution measures (Sigma and Tau), RT fluctuations in cycles of ~14-90 s in all conditions (Slow-4 and Slow-5), and RT fluctuations in cycles of 2-14 s in the fast condition (Slow-2 and Slow-3). Parent-rated ADHD and ASD traits were obtained. All refined RTV components were linked to ADHD traits only and not to ASD traits, while Sigma did not relate to either trait. Although both ADHD and ASD social-communication traits were associated with SDRT, the association with social-communication impairments disappeared when controlling for ADHD traits. A reward-induced improvement in RTV measures, indicating malleability, emerged in relation to ADHD traits but not ASD traits. Under closer inspection, specificity emerges of high RTV to ADHD traits. For the clinician, our findings indicate that attentional fluctuation in children with high ASD traits may be due to co-occurring ADHD traits and emphasise how the effectiveness of rewards does not generalise from ADHD to ASD traits.

SUBMITTER: Adamo N

PROVIDER: S-EPMC6397137 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Ex-Gaussian, Frequency and Reward Analyses Reveal Specificity of Reaction Time Fluctuations to ADHD and Not Autism Traits.

Adamo Nicoletta N Hodsoll John J Asherson Philip P Buitelaar Jan K JK Kuntsi Jonna J

Journal of abnormal child psychology 20190301 3

Both attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) have been linked to increased reaction time variability (RTV), a marker of attentional fluctuation. Here we test whether specificity to either trait emerges when we examine (1) detailed ex-Gaussian and frequency RTV subcomponents, (2) effects while controlling for the other trait and (3) improvement in the RTV measures following rewards or a faster event rate. 1110 children aged 7-10 years from a population-b ...[more]

PMID: 30027330

Similar Datasets

Project description:ObjectiveAttention deficit disorder (ADHD) is commonly associated with inhibitory dysfunction contributing to typical behavioral symptoms like impulsivity or hyperactivity. However, some studies analyzing intraindividual variability (IIV) of reaction times in children with ADHD (cADHD) question a predominance of inhibitory deficits. IIV is a measure of the stability of information processing and provides evidence that longer reaction times (RT) in inhibitory tasks in cADHD are due to only a few prolonged responses which may indicate deficits in sustained attention rather than inhibitory dysfunction. We wanted to find out, whether a slowing in inhibitory functioning in adults with ADHD (aADHD) is due to isolated slow responses.MethodsComputing classical RT measures (mean RT, SD), ex-Gaussian parameters of IIV (which allow a better separation of reaction time (mu), variability (sigma) and abnormally slow responses (tau) than classical measures) as well as errors of omission and commission, we examined response inhibition in a well-established GoNogo task in a sample of aADHD subjects without medication and healthy controls matched for age, gender and education.ResultsWe did not find higher numbers of commission errors in aADHD, while the number of omissions was significantly increased compared with controls. In contrast to increased mean RT, the distributional parameter mu did not document a significant slowing in aADHD. However, subjects with aADHD were characterized by increased IIV throughout the entire RT distribution as indicated by the parameters sigma and tau as well as the SD of reaction time. Moreover, we found a significant correlation between tau and the number of omission errors.ConclusionsOur findings question a primacy of inhibitory deficits in aADHD and provide evidence for attentional dysfunction. The present findings may have theoretical implications for etiological models of ADHD as well as more practical implications for neuropsychological testing in aADHD.

Project description:ObjectiveIncreased levels of reaction time variability (RTV) are characteristics of sustained attention deficits. The clinical significance of RTV has been widely recognized. However, the reliability of RTV measurements has not been widely studied. The present study aimed to assess the test-retest reliability of RTV conventional measurements, e.g., the standard deviation (SD), the coefficient of variation (CV), and a new measurement called the amplitude of low frequency fluctuation (ALFF) of RT. In addition, we aimed to assess differences and similarities of these measurements between different tasks.MethodThirty-seven healthy college students participated in 2 tasks, i.e., an Eriksen flanker task (EFT) and a simple reaction task (SRT), twice over a mean interval of 56 days. Conventional measurements of RTV including RT-SD and RT-CV were assessed first. Then the RT time series were converted into frequency domains, and RT-ALFF was further calculated for the whole frequency band (0.0023-0.167 Hz) and for a few sub-frequency bands including Slow-6 (<0.01 Hz), Slow-5 (0.01-0.027 Hz), Slow-4 (0.027-0.073 Hz), and Slow-3 (0.073-0.167 Hz). The test-retest reliability of these measurements was evaluated through intra-class correlation (ICC) tests. Differences and correlations between each EFT and SRT measurement were further examined during both visits.Results1) The RT-ALFF of the Slow-5/4/3 and conventional measurements of RT-SD and RT-CV showed moderate to high levels of test-retest reliability. EFT RT-ALFF patterns generated slightly higher ICC values than SRT values in higher frequency bands (Slow-3), but SRT RT-ALFF values showed slightly higher ICC values than EFT values in lower frequency bands (Slow-5 and Slow-4). 2) RT-ALFF magnitudes in each sub-frequency band were greater for the SRT than those for the EFT. 3) The RT-ALFF in the Slow-4 of the EFT was found to be correlated with the RT-ALFF in the Slow-5 of the SRT for both two visits, but no consistently significant correlation was found between the same frequency bands.ConclusionsThese findings reveal good test-retest reliability for conventional measurements and for the RT-ALFF of RTV. The RT-ALFF presented frequency-dependent similarities across tasks. All of our results reveal the presence of different frequency structures between the two tasks, and thus the frequency-dependent characteristics of different tasks deserve more attention in future studies.

Project description:ContextAttention-deficit/hyperactivity disorder (ADHD)--characterized by symptoms of inattention and hyperactivity-impulsivity--is the most prevalent childhood psychiatric disorder that frequently persists into adulthood, and there is increasing evidence of reward-motivation deficits in this disorder.ObjectiveTo evaluate biological bases that might underlie a reward/motivation deficit by imaging key components of the brain dopamine reward pathway (mesoaccumbens).Design, setting, and participantsWe used positron emission tomography to measure dopamine synaptic markers (transporters and D(2)/D(3) receptors) in 53 nonmedicated adults with ADHD and 44 healthy controls between 2001-2009 at Brookhaven National Laboratory.Main outcome measuresWe measured specific binding of positron emission tomographic radioligands for dopamine transporters (DAT) using [(11)C]cocaine and for D(2)/D(3) receptors using [(11)C]raclopride, quantified as binding potential (distribution volume ratio -1).ResultsFor both ligands, statistical parametric mapping showed that specific binding was lower in ADHD than in controls (threshold for significance set at P < .005) in regions of the dopamine reward pathway in the left side of the brain. Region-of-interest analyses corroborated these findings. The mean (95% confidence interval [CI] of mean difference) for DAT in the nucleus accumbens for controls was 0.71 vs 0.63 for those with ADHD (95% CI, 0.03-0.13, P = .004) and in the midbrain for controls was 0.16 vs 0.09 for those with ADHD (95% CI, 0.03-0.12; P < or = .001); for D(2)/D(3) receptors, the mean accumbens for controls was 2.85 vs 2.68 for those with ADHD (95% CI, 0.06-0.30, P = .004); and in the midbrain, it was for controls 0.28 vs 0.18 for those with ADHD (95% CI, 0.02-0.17, P = .01). The analysis also corroborated differences in the left caudate: the mean DAT for controls was 0.66 vs 0.53 for those with ADHD (95% CI, 0.04-0.22; P = .003) and the mean D(2)/D(3) for controls was 2.80 vs 2.47 for those with ADHD (95% CI, 0.10-0.56; P = .005) and differences in D(2)/D(3) in the hypothalamic region, with controls having a mean of 0.12 vs 0.05 for those with ADHD (95% CI, 0.02-0.12; P = .004). Ratings of attention correlated with D(2)/D(3) in the accumbens (r = 0.35; 95% CI, 0.15-0.52; P = .001), midbrain (r = 0.35; 95% CI, 0.14-0.52; P = .001), caudate (r = 0.32; 95% CI, 0.11-0.50; P = .003), and hypothalamic (r = 0.31; CI, 0.10-0.49; P = .003) regions and with DAT in the midbrain (r = 0.37; 95% CI, 0.16-0.53; P < or = .001).ConclusionA reduction in dopamine synaptic markers associated with symptoms of inattention was shown in the dopamine reward pathway of participants with ADHD.

Dataset Information

Ex-Gaussian, Frequency and Reward Analyses Reveal Specificity of Reaction Time Fluctuations to ADHD and Not Autism Traits.

Publications

Ex-Gaussian, Frequency and Reward Analyses Reveal Specificity of Reaction Time Fluctuations to ADHD and Not Autism Traits.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets