scholarly journals The comparisons of inhibitory control and post-error behaviors between different types of athletes and physically inactive adults

PLoS ONE ◽  
2021 ◽  
Vol 16 (8) ◽  
pp. e0256272
Author(s):  
Chia-Chuan Yu ◽  
Neil G. Muggleton ◽  
Chiao-Yun Chen ◽  
Cheng-Hung Ko ◽  
Suyen Liu
Keyword(s):  
Reaction Time ◽  
Behavioral Pattern ◽  
Stop Signal ◽  
Stop Signal Task ◽  
Error Processing ◽  
Error Monitoring ◽  
Sport Training ◽  
Different Types ◽  
Stop Signal Reaction Time ◽  
Skill Groups

To properly behave and correct mistakes, individuals must inhibit inappropriate actions and detect errors for future behavioral adjustment. Increasing evidence has demonstrated that athletes are superior in cognitive functions and this benefit varied dependent on the types of sport that individuals involved in, but less is known on whether athletes have a different error-related behavioral pattern. The purpose of this study was to compare the behavioral performance of inhibition and error monitoring between individuals who participated in an open-skill sport (n = 12), a closed-skill sport (n = 12), and a sedentary lifestyle (n = 16). A combined flanker/stop signal task was presented and the derived stop signal reaction time (SSRT), post-correct accuracy and reaction time (RT), as well as post-error accuracy and RT were compared across groups. Our findings indicated there was no difference in SSRT between groups. Surprisingly, significant post-error slowing (PES) was observed only in controls but not in sport groups, the controls also exhibited significantly longer post-error RT compared with the open-skill group. However, there was no difference in the post-error accuracy between groups, indicating a higher efficiency in the post-error processing among open- and closed-skill groups by requiring comparatively less time for behavioral adjustments. The present study is the first to disclose the discrepancies in PES between different types of athletes and controls. The findings suggest that sport training along with higher amounts of physical activity is associated with a more efficient behavioral pattern for error processing especially when the sport requires open skills in nature.

scholarly journals Is motor inhibition involved in the processing of sentential negation? An assessment via the Stop-Signal Task

2021 ◽  
Author(s):  
Martina Montalti ◽  
Marta Calbi ◽  
Valentina Cuccio ◽  
Maria Alessandra Umiltà ◽  
Vittorio Gallese
Keyword(s):  
Reaction Time ◽  
Language Processing ◽  
Stop Signal ◽  
Stop Signal Task ◽  
Motor Inhibition ◽  
Good Tool ◽  
Scientific Debate ◽  
Sentential Negation ◽  
Stop Signal Reaction Time ◽  
Methodological Considerations

AbstractIn the last decades, the embodied approach to cognition and language gained momentum in the scientific debate, leading to evidence in different aspects of language processing. However, while the bodily grounding of concrete concepts seems to be relatively not controversial, abstract aspects, like the negation logical operator, are still today one of the main challenges for this research paradigm. In this framework, the present study has a twofold aim: (1) to assess whether mechanisms for motor inhibition underpin the processing of sentential negation, thus, providing evidence for a bodily grounding of this logic operator, (2) to determine whether the Stop-Signal Task, which has been used to investigate motor inhibition, could represent a good tool to explore this issue. Twenty-three participants were recruited in this experiment. Ten hand-action-related sentences, both in affirmative and negative polarity, were presented on a screen. Participants were instructed to respond as quickly and accurately as possible to the direction of the Go Stimulus (an arrow) and to withhold their response when they heard a sound following the arrow. This paradigm allows estimating the Stop Signal Reaction Time (SSRT), a covert reaction time underlying the inhibitory process. Our results show that the SSRT measured after reading negative sentences are longer than after reading affirmative ones, highlighting the recruitment of inhibitory mechanisms while processing negative sentences. Furthermore, our methodological considerations suggest that the Stop-Signal Task is a good paradigm to assess motor inhibition’s role in the processing of sentence negation.

scholarly journals Cognitive Modeling Suggests That Attentional Failures Drive Longer Stop-Signal Reaction Time Estimates in Attention Deficit/Hyperactivity Disorder

2019 ◽  
Vol 7 (4) ◽  
pp. 856-872 ◽  
Author(s):  
Alexander Weigard ◽  
Andrew Heathcote ◽  
Dóra Matzke ◽  
Cynthia Huang-Pollock
Keyword(s):  
Attention Deficit Hyperactivity Disorder ◽  
Reaction Time ◽  
Attention Deficit ◽  
Cognitive Modeling ◽  
Stop Signal ◽  
Stop Signal Task ◽  
Unbiased Estimation ◽  
Children With Adhd ◽  
Hyperactivity Disorder ◽  
Stop Signal Reaction Time

Mean stop-signal reaction time (SSRT) is frequently employed as a measure of response inhibition in cognitive neuroscience research on attention deficit/hyperactivity disorder (ADHD). However, this measurement model is limited by two factors that may bias SSRT estimation in this population: (a) excessive skew in “go” RT distributions and (b) trigger failures, or instances in which individuals fail to trigger an inhibition process in response to the stop signal. We used a Bayesian parametric approach that allows unbiased estimation of the shape of entire SSRT distributions and the probability of trigger failures to clarify mechanisms of stop-signal task deficits in ADHD. Children with ADHD displayed greater positive skew than their peers in both go RT and SSRT distributions. However, they also displayed more frequent trigger failures, which appeared to drive ADHD-related stopping difficulties. Results suggest that performance on the stop-signal task among children with ADHD reflects impairments in early attentional processes, rather than inefficiency in the stop process.

scholarly journals Age-Related Structural and Functional Changes of the Hippocampus and the Relationship with Inhibitory Control

2020 ◽  
Vol 10 (12) ◽  
pp. 1013
Author(s):  
Sien Hu ◽  
Chiang-shan R. Li
Keyword(s):  
Reaction Time ◽  
Cognitive Aging ◽  
Gray Matter Volume ◽  
Stop Signal ◽  
Sequential Effect ◽  
Stop Signal Task ◽  
Functional Changes ◽  
Age Related ◽  
Stop Signal Reaction Time ◽  
Age Related Changes

Aging is associated with structural and functional changes in the hippocampus, and hippocampal dysfunction represents a risk marker of Alzheimer’s disease. Previously, we demonstrated age-related changes in reactive and proactive control in the stop signal task, each quantified by the stop signal reaction time (SSRT) and sequential effect computed as the correlation between the estimated stop signal probability and go trial reaction time. Age was positively correlated with the SSRT, but not with the sequential effect. Here, we explored hippocampal gray matter volume (GMV) and activation to response inhibition and to p(Stop) in healthy adults 18 to 72 years of age. The results showed age-related reduction of right anterior hippocampal activation during stop success vs. go trials, and the hippocampal activities correlated negatively with the SSRT. In contrast, the right posterior hippocampus showed higher age-related responses to p(Stop), but the activities did not correlate with the sequential effect. Further, we observed diminished GMVs of the anterior and posterior hippocampus. However, the GMVs were not related to behavioral performance or regional activities. Together, these findings suggest that hippocampal GMVs and regional activities represent distinct neural markers of cognitive aging, and distinguish the roles of the anterior and posterior hippocampus in age-related changes in cognitive control.

scholarly journals A stop-signal task for sheep: introduction and validation of a direct measure for the stop-signal reaction time

2017 ◽  
Vol 20 (4) ◽  
pp. 615-626 ◽  
Author(s):  
Franziska Knolle ◽  
Sebastian D. McBride ◽  
James E. Stewart ◽  
Rita P. Goncalves ◽  
A. Jennifer Morton
Keyword(s):  
Reaction Time ◽  
Stop Signal ◽  
Stop Signal Task ◽  
Direct Measure ◽  
Stop Signal Reaction Time

Working Memory Load Selectively Influences Response Inhibition in a Stop Signal Task

2020 ◽  
pp. 003329412092827
Author(s):  
Leanne Boucher ◽  
Brandi Viparina ◽  
W. Matthew Collins
Keyword(s):  
Working Memory ◽  
Reaction Time ◽  
Memory Load ◽  
Working Memory Capacity ◽  
Memory Capacity ◽  
Stop Signal ◽  
Stop Signal Task ◽  
Working Memory Load ◽  
Stop Signal Reaction Time ◽  
Load Conditions

Inhibitory control is a key executive function and has been studied extensively using the stop signal task. By applying a simple race model that posits an independent race between a GO process responsible for initiation of responses and a STOP process responsible for inhibition of responses, one can estimate how long it takes an individual to inhibit an ongoing response, the stop signal reaction time. Here, we examined how stop signal reaction time can be affected by working memory. Participants engaged in a dual task; they completed a stop signal task under low and high working memory load conditions. Working memory capacity was also measured. We found that the STOP process was lengthened in the high, compared to the low, working memory load condition, as evidenced by differences in stop signal reaction time. The GO process was unaffected and working memory capacity could not account for differences across the load conditions. These results indicate that inhibitory control can be influenced by placing demands on working memory.

Proactive and Reactive Motor Inhibition in Top Athletes Versus Nonathletes

2018 ◽  
Vol 125 (2) ◽  
pp. 289-312 ◽  
Author(s):  
Damien Brevers ◽  
Etienne Dubuisson ◽  
Fabien Dejonghe ◽  
Julien Dutrieux ◽  
Mathieu Petieau ◽  
...  
Keyword(s):  
Reaction Time ◽  
Response Inhibition ◽  
Motor Response ◽  
Proactive Inhibition ◽  
Stop Signal ◽  
Stop Signal Task ◽  
Reactive Inhibition ◽  
Stop Signal Reaction Time ◽  
Motor Response Inhibition ◽  
Inhibition Performance

We examined proactive (early restraint in preparation for stopping) and reactive (late correction to stop ongoing action) motor response inhibition in two groups of participants: professional athletes ( n = 28) and nonathletes ( n = 25). We recruited the elite athletes from Belgian national taekwondo and fencing teams. We estimated proactive and reactive inhibition with a modified version of the stop-signal task (SST) in which participants inhibited categorizing left/right arrows. The probability of the stop signal was manipulated across blocks of trials by providing probability cues from the background computer screen color (green = 0%, yellow =17%, orange = 25%, red = 33%). Participants performed two sessions of the SST, where proactive inhibition was operationalized with increased go-signal reaction time as a function of increased stop-signal probability and reactive inhibition was indicated by stop-signal reaction time latency. Athletes exhibited higher reactive inhibition performance than nonathletes. In addition, athletes exhibited higher proactive inhibition than nonathletes in Session 1 (but not Session 2) of the SST. As top-level athletes exhibited heightened reactive inhibition and were faster to reach and maintain consistent proactive motor response inhibition, these results confirm an evaluative process that can discriminate elite athleticism through a fine-grained analysis of inhibitory control.

scholarly journals Dynamical EEG Indices of Progressive Motor Inhibition and Error-Monitoring

2021 ◽  
Vol 11 (4) ◽  
pp. 478
Author(s):  
Trung Van Nguyen ◽  
Prasad Balachandran ◽  
Neil G. Muggleton ◽  
Wei-Kuang Liang ◽  
Chi-Hung Juan
Keyword(s):  
Inhibitory Control ◽  
Control Process ◽  
Stop Signal ◽  
Stop Signal Task ◽  
Error Processing ◽  
Alpha Power ◽  
Error Monitoring ◽  
Motor Inhibition ◽  
Hilbert Huang Transform ◽  
Time Frequency

Response inhibition has been widely explored using the stop signal paradigm in the laboratory setting. However, the mechanism that demarcates attentional capture from the motor inhibition process is still unclear. Error monitoring is also involved in the stop signal task. Error responses that do not complete, i.e., partial errors, may require different error monitoring mechanisms relative to an overt error. Thus, in this study, we included a “continue go” (Cont_Go) condition to the stop signal task to investigate the inhibitory control process. To establish the finer difference in error processing (partial vs. full unsuccessful stop (USST)), a grip-force device was used in tandem with electroencephalographic (EEG), and the time-frequency characteristics were computed with Hilbert–Huang transform (HHT). Relative to Cont_Go, HHT results reveal (1) an increased beta and low gamma power for successful stop trials, indicating an electrophysiological index of inhibitory control, (2) an enhanced theta and alpha power for full USST trials that may mirror error processing. Additionally, the higher theta and alpha power observed in partial over full USST trials around 100 ms before the response onset, indicating the early detection of error and the corresponding correction process. Together, this study extends our understanding of the finer motor inhibition control and its dynamic electrophysiological mechanisms.

scholarly journals Orbitofrontal neuron ensembles contribute to inhibitory control

2018 ◽  
Author(s):  
Pragathi Priyadharsini Balasubramani ◽  
Benjamin Y. Hayden
Keyword(s):  
Reaction Time ◽  
Orbitofrontal Cortex ◽  
Early Stage ◽  
Stop Signal ◽  
Self Control ◽  
Stop Signal Task ◽  
Sensory Inputs ◽  
Stop Signal Reaction Time ◽  
Recorded Activity ◽  
Core Part

SUMMARYStopping, or inhibition, is a form of self-control that is a core part of adaptive behavior. We hypothesize that inhibition commands originate, in part, from the orbitofrontal cortex (OFC). We recorded activity of OFC neurons in macaques performing a stop signal task. Decoding analyses revealed a clear difference in ensemble responses that distinguish successful from failed inhibition that begins after the stop signal and before the stop signal reaction time. We also found a different and unrelated ensemble pattern that distinguishes successful from failed stopping before the beginning of the trial. These signals were distinct from, and orthogonal to, value encoding, which was also observed in these neurons. The timing of the early and late signals was, respectively, consistent with the idea that OFC contributes both proactively and reactively to inhibition. These results support the view, inspired by anatomy, that OFC gathers diverse sensory inputs to compute early-stage executive signals.

scholarly journals Obsessive Compulsive Disorder and Response Inhibition: Meta-analysis of the Stop-Signal Task

2021 ◽  
Author(s):  
Kendall Mar ◽  
Parker Townes ◽  
Petros Pechlivanoglou ◽  
Paul Arnold ◽  
Russell James Schachar
Keyword(s):  
Reaction Time ◽  
Obsessive Compulsive Disorder ◽  
Response Inhibition ◽  
Meta Analysis ◽  
Stop Signal ◽  
Mean Difference ◽  
Stop Signal Task ◽  
Obsessive Compulsive ◽  
Compulsive Disorder ◽  
Stop Signal Reaction Time

This systematic review and meta-analysis updates evidence pertaining to deficient response inhibition in obsessive-compulsive disorder (OCD) as measured by the stop-signal task (SST). We conducted a meta-analysis of the literature to compare response inhibition in patients with OCD and healthy controls, meta-regressions to determine relative influences of age and sex on response inhibition impairment, and a risk of bias assessment for included studies using the Newcastle-Ottawa Scale (NOS). Stop-signal reaction time (SSRT), which estimates the latency of the stopping process deficit, was significantly longer in OCD samples than in controls, reflecting inferior inhibitory control (Raw mean difference = 23.43ms; p = <0.001; 95% CI = [17.42, 29.45]). We did not observe differences in mean reaction time (MRT) in OCD compared to controls (Raw mean difference = 2.51ms; p = 0.755; 95% CI = [-13.27, 18.30]). Age impacted effect size of SSRT, indicating a greater deficit in older patients than younger ones. We did not observe a significant effect of sex on SSRT or MRT scores.

scholarly journals An ERP study on proactive and reactive response inhibition in individuals with schizotypy

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Lu-xia Jia ◽  
Xiao-jing Qin ◽  
Ji-fang Cui ◽  
Qi Zheng ◽  
Tian-xiao Yang ◽  
...  
Keyword(s):  
Reaction Time ◽  
Response Inhibition ◽  
Proactive Inhibition ◽  
Stop Signal ◽  
Stop Signal Task ◽  
Signal Probability ◽  
Reactive Inhibition ◽  
Eeg Data ◽  
Stop Signal Reaction Time ◽  
Stop Condition

AbstractSchizotypy, a subclinical group at risk for schizophrenia, has been found to show impairments in response inhibition. However, it remains unclear whether this impairment is accompanied by outright stopping (reactive inhibition) or preparation for stopping (proactive inhibition). We recruited 20 schizotypy and 24 non-schizotypy individuals to perform a modified stop-signal task with electroencephalographic (EEG) data recorded. This task consists of three conditions based on the probability of stop signal: 0% (no stop trials, only go trials), 17% (17% stop trials), and 33% (33% stop trials), the conditions were indicated by the colour of go stimuli. For proactive inhibition (go trials), individuals with schizotypy exhibited significantly lesser increase in go response time (RT) as the stop signal probability increasing compared to non-schizotypy individuals. Individuals with schizotypy also exhibited significantly increased N1 amplitude on all levels of stop signal probability and increased P3 amplitude in the 17% stop condition compared with non-schizotypy individuals. For reactive inhibition (stop trials), individuals with schizotypy exhibited significantly longer stop signal reaction time (SSRT) in both 17% and 33% stop conditions and smaller N2 amplitude on stop trials in the 17% stop condition than non-schizotypy individuals. These findings suggest that individuals with schizotypy were impaired in both proactive and reactive response inhibition at behavioural and neural levels.

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