Abstract:The ability to inhibit a prepotent response is a crucial prerequisite of goal-directed behavior. So far, research on response inhibition has mainly examined these processes when there is little to no cognitive control during the decision to respond. We manipulated the “context” in which response inhibition has to be exerted (i.e., a controlled or an automated context) by combining a Simon task with a go/no-go task and focus on theta-band activity. To investigate the role of “context” in response inhibition, we… Show more
“…On the other hand, a significantly higher overall accuracy in incongruent trials (96.15% ± 0.38) than in congruent trials (94.60% ± 0.48) was found in the Nogo condition ( t = −6.087, p = 0.002). These results were also confirmed by additional Wilcoxon signed-rank tests for Go ( z = −3.049, p = 0.004) and Nogo trials ( z = −5.234, p = 0.002) and align with previous findings using the same experimental paradigm on healthy participants [ 21 , 23 ].…”
Section: Resultssupporting
confidence: 89%
“…To measure the effect of automatic vs. controlled processes on response inhibition, an integration of Simon and Go/Nogo paradigms was used ( Figure 1 ) [ 22 , 23 , 43 ].…”
Section: Methodsmentioning
confidence: 99%
“…To this end, we used a relatively recently developed experimental paradigm combining the Simon task and the Go/Nogo task, which allows the examination of the interplay of controlled and automated processing during goal-directed actions [ 21 , 22 , 23 ]. For the Simon task, the dual-route model [ 24 ] states that conflicts arise due to competing automatic and controlled (response) selection processes.…”
Section: Introductionmentioning
confidence: 99%
“…This interplay of the so-called direct (automatic) route and the indirect (controlled) route is essential to explain behavior: In congruent trials, the direct route is sufficient for correct responding, but, in incongruent trials, the indirect route also needs to be activated to ‘control’ the direct route. When processing via the direct route dominates, response inhibition becomes harder and more error-prone, ultimately resulting in more inhibition failures in congruent trials compared with incongruent trials, where the indirect (controlled) route already exerts some control over the direct (automatic) route [ 21 , 23 , 25 ]. As a consequence of these mechanisms, the “regular” Simon effect is characterized by better behavioral performance in congruent than in incongruent Go trials.…”
The behavioral and neural dynamics of response inhibition deficits in alcohol use disorder (AUD) are still largely unclear, despite them possibly being key to the mechanistic understanding of the disorder. Our study investigated the effect of automatic vs. controlled processing during response inhibition in participants with mild-to-moderate AUD and matched healthy controls. For this, a Simon Nogo task was combined with EEG signal decomposition, multivariate pattern analysis (MVPA), and source localization methods. The final sample comprised n = 59 (32♂) AUD participants and n = 64 (28♂) control participants. Compared with the control group, AUD participants showed overall better response inhibition performance. Furthermore, the AUD group was less influenced by the modulatory effect of automatic vs. controlled processes during response inhibition (i.e., had a smaller Simon Nogo effect). The neurophysiological data revealed that the reduced Simon Nogo effect in the AUD group was associated with reduced activation differences between congruent and incongruent Nogo trials in the inferior and middle frontal gyrus. Notably, the drinking frequency (but not the number of AUD criteria we had used to distinguish groups) predicted the extent of the Simon Nogo effect. We suggest that the counterintuitive advantage of participants with mild-to-moderate AUD over those in the control group could be explained by the allostatic model of drinking effects.
“…On the other hand, a significantly higher overall accuracy in incongruent trials (96.15% ± 0.38) than in congruent trials (94.60% ± 0.48) was found in the Nogo condition ( t = −6.087, p = 0.002). These results were also confirmed by additional Wilcoxon signed-rank tests for Go ( z = −3.049, p = 0.004) and Nogo trials ( z = −5.234, p = 0.002) and align with previous findings using the same experimental paradigm on healthy participants [ 21 , 23 ].…”
Section: Resultssupporting
confidence: 89%
“…To measure the effect of automatic vs. controlled processes on response inhibition, an integration of Simon and Go/Nogo paradigms was used ( Figure 1 ) [ 22 , 23 , 43 ].…”
Section: Methodsmentioning
confidence: 99%
“…To this end, we used a relatively recently developed experimental paradigm combining the Simon task and the Go/Nogo task, which allows the examination of the interplay of controlled and automated processing during goal-directed actions [ 21 , 22 , 23 ]. For the Simon task, the dual-route model [ 24 ] states that conflicts arise due to competing automatic and controlled (response) selection processes.…”
Section: Introductionmentioning
confidence: 99%
“…This interplay of the so-called direct (automatic) route and the indirect (controlled) route is essential to explain behavior: In congruent trials, the direct route is sufficient for correct responding, but, in incongruent trials, the indirect route also needs to be activated to ‘control’ the direct route. When processing via the direct route dominates, response inhibition becomes harder and more error-prone, ultimately resulting in more inhibition failures in congruent trials compared with incongruent trials, where the indirect (controlled) route already exerts some control over the direct (automatic) route [ 21 , 23 , 25 ]. As a consequence of these mechanisms, the “regular” Simon effect is characterized by better behavioral performance in congruent than in incongruent Go trials.…”
The behavioral and neural dynamics of response inhibition deficits in alcohol use disorder (AUD) are still largely unclear, despite them possibly being key to the mechanistic understanding of the disorder. Our study investigated the effect of automatic vs. controlled processing during response inhibition in participants with mild-to-moderate AUD and matched healthy controls. For this, a Simon Nogo task was combined with EEG signal decomposition, multivariate pattern analysis (MVPA), and source localization methods. The final sample comprised n = 59 (32♂) AUD participants and n = 64 (28♂) control participants. Compared with the control group, AUD participants showed overall better response inhibition performance. Furthermore, the AUD group was less influenced by the modulatory effect of automatic vs. controlled processes during response inhibition (i.e., had a smaller Simon Nogo effect). The neurophysiological data revealed that the reduced Simon Nogo effect in the AUD group was associated with reduced activation differences between congruent and incongruent Nogo trials in the inferior and middle frontal gyrus. Notably, the drinking frequency (but not the number of AUD criteria we had used to distinguish groups) predicted the extent of the Simon Nogo effect. We suggest that the counterintuitive advantage of participants with mild-to-moderate AUD over those in the control group could be explained by the allostatic model of drinking effects.
“…In incongruent Simon trials, the automatic and controlled routes are activated and induce a conflict (Chmielewski & Beste, 2017 ; Hommel, 2011 ; Keye et al, 2013 ), which increases the contribution of controlled response selection processes. Using a Simon‐Go/Nogo task, it has been shown that there is a lower rate of false alarms (i.e., erroneous responses in Nogo trials) when a Nogo stimulus is embedded in incongruent than congruent Simon task trials (Chmielewski et al, 2018 ; Chmielewski et al, 2020 ; Chmielewski & Beste, 2017 ; Opitz et al, 2019 ; Wendiggensen et al, 2022 ). Previous studies investigated the neural dynamics underlying the interplay of automatic and controlled processes during response inhibition (Chmielewski et al, 2018 ; Chmielewski et al, 2020 ; Chmielewski & Beste, 2017 ; Opitz et al, 2019 ; Wendiggensen et al, 2022 ).…”
Inhibitory control processes have intensively been studied in cognitive science for the past decades. Even though the neural dynamics underlying these processes are increasingly better understood, a critical open question is how the representational dynamics of the inhibitory control processes are modulated when engaging in response inhibition in a relatively automatic or a controlled mode. Against the background of an overarching theory of perception‐action integration, we combine temporal and spatial EEG signal decomposition methods with multivariate pattern analysis and source localization to obtain fine‐grained insights into the neural dynamics of the representational content of response inhibition. For this purpose, we used a sample of
N
= 40 healthy adult participants. The behavioural data suggest that response inhibition was better in a more controlled than a more automated response execution mode. Regarding neural dynamics, effects of response inhibition modes relied on a concomitant coding of stimulus‐related information and rules of how stimulus information is related to the appropriate motor programme. Crucially, these fractions of information, which are encoded at the same time in the neurophysiological signal, are based on two independent spatial neurophysiological activity patterns, also showing differences in the temporal stability of the representational content. Source localizations revealed that the precuneus and inferior parietal cortex regions are more relevant than prefrontal areas for the representation of stimulus–response selection codes. We provide a blueprint how a concatenation of EEG signal analysis methods, capturing distinct aspects of neural dynamics, can be connected to cognitive science theory on the importance of representations in action control.
Response inhibition is an important instance of cognitive control and can be complicated by perceptual conflict. The neurophysiological mechanisms underlying these processes are still not understood. Especially the relationship between neural processes directly preceding cognitive control (proactive control) and processes underlying cognitive control (reactive control) has not been examined although there should be close links. In the current study, we investigate these aspects in a sample of N = 50 healthy adults. Time‐frequency and beamforming approaches were applied to analyze the interrelation of brain states before (pre‐trial) and during (within‐trial) cognitive control. The behavioral data replicate a perceptual conflict‐dependent modulation of response inhibition. During the pre‐trial period, insular, inferior frontal, superior temporal, and precentral alpha activity was positively correlated with theta activity in the same regions and the superior frontal gyrus. Additionally, participants with a stronger pre‐trial alpha activity in the primary motor cortex showed a stronger (within‐trial) conflict effect in the theta band in the primary motor cortex. This theta conflict effect was further related to a stronger theta conflict effect in the midcingulate cortex until the end of the trial. The temporal cascade of these processes suggests that successful proactive preparation (anticipatory information gating) entails a stronger reactive processing of the conflicting stimulus information likely resulting in a realization of the need to adapt the current action plan. The results indicate that theta and alpha band activity share and transfer aspects of information when it comes to the interrelationship between proactive and reactive control during conflict‐modulated motor inhibition.
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