Children with ADHD symptoms show deficits in reactive but not proactive inhibition, irrespective of their formal diagnosis

Hulst, Branko M. van; Zeeuw, Patrick de; Vlaskamp, Chantal; Rijks, Yvonne; Zandbelt, Bram B.; Durston, Sarah

doi:10.1017/s0033291718000107

Cited by 43 publications

(46 citation statements)

References 39 publications

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“…The proactive component of response inhibition has been often evaluated by modified versions of the SST, where cues are inserted to inform subjects about the probability of an upcoming stop-signal, as in the conditional SST [ 64 ], or in the stop-signal anticipation task [ 65 ]. However, to distinguish reactive and proactive processes within the same task, as well as to isolate them from other cognitive process that likely modulate response inhibition (e.g., attention and working memory load), has proven difficult.…”

Section: Discussionmentioning

confidence: 99%

Mouse Tracking to Explore Motor Inhibition Processes in Go/No-Go and Stop Signal Tasks

et al. 2020

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Response inhibition relies on both proactive and reactive mechanisms that exert a synergic control on goal-directed actions. It is typically evaluated by the go/no-go (GNG) and the stop signal task (SST) with response recording based on the key-press method. However, the analysis of discrete variables (i.e., present or absent responses) registered by key-press could be insufficient to capture dynamic aspects of inhibitory control. Trying to overcome this limitation, in the present study we used a mouse tracking procedure to characterize movement profiles related to proactive and reactive inhibition. A total of fifty-three participants performed a cued GNG and an SST. The cued GNG mainly involves proactive control whereas the reactive component is mainly engaged in the SST. We evaluated the velocity profile from mouse trajectories both for responses obtained in the Go conditions and for inhibitory failures. Movements were classified as one-shot when no corrections were observed. Multi-peaked velocity profiles were classified as non-one-shot. A higher proportion of one-shot movements was found in the SST compared to the cued GNG when subjects failed to inhibit responses. This result suggests that proactive control may be responsible for unsmooth profiles in inhibition failures, supporting a differentiation between these tasks.

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Section: Discussionmentioning

confidence: 99%

Mouse Tracking to Explore Motor Inhibition Processes in Go/No-Go and Stop Signal Tasks

et al. 2020

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“…Proactive inhibition is related to the attenuation of a motor plan relevant to the task [48]. In this study, we assessed both proactive and reactive inhibition, as they are important for ADHD [49].…”

Section: Methodsmentioning

confidence: 99%

Mouse movement measures enhance the stop-signal task in adult ADHD assessment

Leontyev

Yamauchi

2019

PLoS ONE

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The accurate detection of attention-deficit/hyperactivity disorder (ADHD) symptoms, such as inattentiveness and behavioral disinhibition, is crucial for delivering timely assistance and treatment. ADHD is commonly diagnosed and studied with specialized questionnaires and behavioral tests such as the stop-signal task. However, in cases of late-onset or mild forms of ADHD, behavioral measures often fail to gauge the deficiencies well-highlighted by questionnaires. To improve the sensitivity of behavioral tests, we propose a novel version of the stop-signal task (SST), which integrates mouse cursor tracking. In two studies, we investigated whether introducing mouse movement measures to the stop-signal task improves associations with questionnaire-based measures, as compared to the traditional (keypress-based) version of SST. We also scrutinized the influence of different parameters of stop-signal tasks, such as the method of stop-signal delay setting or definition of response inhibition failure, on these associations. Our results show that a) SSRT has weak association with impulsivity, while mouse movement measures have strong and significant association with impulsivity; b) machine learning models trained on the mouse movement data from “known” participants using nested cross-validation procedure can accurately predict impulsivity ratings of “unknown” participants; c) mouse movement features such as maximum acceleration and maximum velocity are among the most important predictors for impulsivity; d) using preset stop-signal delays prompts behavior that is more indicative of impulsivity.

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“…This paradigm is unique in allowing the estimation of the stop process covert latency: the stop-signal reaction time (SSRT), a sensitive individual index of inhibitory ability 10 . Nevertheless, previous studies using the SST in ASD populations have reported mixed findings, some showing longer SSRTs in ASD compared with typically developing (TD) children [11][12][13][14] and others not [15][16][17][18][19] . Importantly, comorbid ADHD seems to partly explain inhibitory deficits in individuals with ASD 14 .…”

Section: Introductionmentioning

confidence: 99%

ADHD and ASD: distinct brain patterns of inhibition-related activation?

et al. 2020

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Attention-deficit/hyperactivity (ADHD) and autism spectrum (ASD) disorders often co-occur. In both cases, response inhibition deficits and inhibition-related atypical brain activation have been reported, although less consistently in ASD. Research exploring the overlap/distinctiveness between ADHD and ASD has significantly increased in recent years, but direct comparison of the inhibition-related neuronal correlates between these disorders are scarce in the literature. This study aimed at disentangling the shared and specific inhibitory brain dysfunctions in ASD and ADHD. Using functional magnetic resonance imaging (fMRI), brain activity was compared between children with ADHD, ASD and typically developing (TD) children aged 8-12 years during an inhibition stop-signal task, using stringent inclusion criteria. At the behavioural level, only children with ADHD exhibited inhibition deficits when compared with the TD group. Distinct patterns of brain activity were observed during successful inhibition. In children with ADHD, motor inhibition was associated with right inferior parietal activation, whereas right frontal regions were activated in children with ASD. Between-group comparisons disclosed higher middle frontal activation in the ASD group compared with the ADHD and the TD groups. Our results evidence different patterns of activation during inhibition in these two disorders, recruiting different regions of the fronto-parietal network associated to inhibition. Besides brain activity differences, behavioural inhibition deficits found only in children with ADHD further suggest that reactive inhibition is one of the core deficits in ADHD, but not in ASD. Our findings provide further evidence contributing to disentangle the shared and specific inhibitory dysfunctions in ASD and ADHD.

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Children with ADHD symptoms show deficits in reactive but not proactive inhibition, irrespective of their formal diagnosis

Cited by 43 publications

References 39 publications

Mouse Tracking to Explore Motor Inhibition Processes in Go/No-Go and Stop Signal Tasks

Mouse Tracking to Explore Motor Inhibition Processes in Go/No-Go and Stop Signal Tasks

Mouse movement measures enhance the stop-signal task in adult ADHD assessment

ADHD and ASD: distinct brain patterns of inhibition-related activation?

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