scholarly journals The Phenomenology of Error Processing: The Dorsal ACC Response to Stop-signal Errors Tracks Reports of Negative Affect

2012 ◽  
Vol 24 (8) ◽  
pp. 1753-1765 ◽  
Author(s):  
Robert P. Spunt ◽  
Matthew D. Lieberman ◽  
Jessica R. Cohen ◽  
Naomi I. Eisenberger
Keyword(s):  
Cognitive Control ◽  
Negative Affect ◽  
Task Performance ◽  
Subjective Experience ◽  
Stop Signal ◽  
Stop Signal Task ◽  
Affective States ◽  
Subject Variability ◽  
Fear And Anxiety ◽  
Within Subject Variability

A reliable observation in neuroimaging studies of cognitive control is the response of dorsal ACC (dACC) to events that demand increased cognitive control (e.g., response conflicts and performance errors). This observation is apparently at odds with a comparably reliable association of the dACC with the subjective experience of negative affective states such as pain, fear, and anxiety. Whereas “affective” associates of the dACC are based on studies that explicitly manipulate and/or measure the subjective experience of negative affect, the “cognitive” associates of dACC are based on studies using tasks designed to manipulate the demand for cognitive control, such as the Stroop, flanker, and stop-signal tasks. Critically, extant neuroimaging research has not systematically considered the extent to which these cognitive tasks induce negative affective experiences and, if so, to what extent negative affect can account for any variance in the dACC response during task performance. While undergoing fMRI, participants in this study performed a stop-signal task while regularly reporting their experience of performance on several dimensions. We observed that within-subject variability in the dACC response to stop-signal errors tracked changes in subjective frustration throughout task performance. This association remained when controlling for within-subject variability in subjective reports of cognitive engagement and several performance-related variables indexing task difficulty. These results fit with existing models characterizing the dACC as a hub for monitoring ongoing behavior and motivating adjustments when necessary and further emphasize that such a function may be linked to the subjective experience of negative affect.

scholarly journals Hard to Resist?

2019 ◽  
Vol 31 (4) ◽  
pp. 214-225 ◽  
Author(s):  
Niklas Johannes ◽  
Harm Veling ◽  
Thijs Verwijmeren ◽  
Moniek Buijzen
Keyword(s):  
Young People ◽  
Task Performance ◽  
Response Inhibition ◽  
Sampling Design ◽  
Sequential Sampling ◽  
Stop Signal ◽  
Stop Signal Task ◽  
Impact Performance ◽  
Access Information ◽  
Prepotent Responses

Abstract. Because more and more young people are constantly presented with the opportunity to access information and connect to others via their smartphones, they report to be in a state of permanent alertness. In the current study, we define such a state as smartphone vigilance, an awareness that one can always get connected to others in combination with a permanent readiness to respond to incoming smartphone notifications. We hypothesized that constantly resisting the urge to interact with their phones draws on response inhibition, and hence interferes with students’ ability to inhibit prepotent responses in a concurrent task. To test this, we conducted a preregistered experiment, employing a Bayesian sequential sampling design, where we manipulated smartphone visibility and smartphone notifications during a stop-signal task that measures the ability to inhibit prepotent responses. The task was constructed such that we could disentangle response inhibition from action selection. Results show that the mere visibility of a smartphone is sufficient to experience vigilance and distraction, and that this is enhanced when students receive notifications. Curiously enough, these strong experiences were unrelated to stop-signal task performance. These findings raise new questions about when and how smartphones can impact performance.

Greater activation of the response inhibition network in females compared to males during stop signal task performance

2020 ◽  
Vol 386 ◽  
pp. 112586 ◽  
Author(s):  
Alexandra Gaillard ◽  
Susan L. Rossell ◽  
Sean P. Carruthers ◽  
Philip J. Sumner ◽  
Patricia T. Michie ◽  
...  
Keyword(s):  
Task Performance ◽  
Response Inhibition ◽  
Stop Signal ◽  
Stop Signal Task

Sustained brain activation supporting stop-signal task performance

2014 ◽  
Vol 39 (8) ◽  
pp. 1363-1369 ◽  
Author(s):  
M. E. Hughes ◽  
T. W. Budd ◽  
W. R. Fulham ◽  
S. Lancaster ◽  
W. Woods ◽  
...  
Keyword(s):  
Task Performance ◽  
Brain Activation ◽  
Stop Signal ◽  
Stop Signal Task

scholarly journals “Distinct roles of dorsal and ventral subthalamic neurons in action selection and cancellation.”

2020 ◽  
Author(s):  
Clayton P. Mosher ◽  
Adam N. Mamelak ◽  
Mahsa Malekmohammadi ◽  
Nader Pouratian ◽  
Ueli Rutishauser
Keyword(s):  
Cognitive Control ◽  
Subthalamic Nucleus ◽  
Action Selection ◽  
Stop Signal ◽  
Stop Signal Task ◽  
Single Neurons ◽  
Motor Programs ◽  
Behavioral Outcome ◽  
Motor Cortical ◽  
Subthalamic Neurons

AbstractThe subthalamic nucleus (STN) supports action selection by inhibiting all motor programs except the desired one. Recent evidence suggests that STN can also cancel an already selected action when goals change, a key aspect of cognitive control. However, there is little neurophysiological evidence for a dissociation between selecting and cancelling actions in the human STN. We recorded single neurons in the STN of humans performing a stop-signal task. Movement-related neurons suppressed their activity during successful stopping whereas stop-signal neurons activated at low-latencies regardless of behavioral outcome. In contrast, STN and motor-cortical beta-bursting occurred only later in the stopping process. Task-related neuronal properties varied by recording location from dorsolateral movement to ventromedial stop-signal tuning. Therefore, action selection and cancellation coexist in STN but are anatomically segregated. These results show that human ventromedial STN neurons carry fast stop-related signals suitable for implementing cognitive control.

scholarly journals Prediction of Human Inhibition Brain Function with Inter-Subject and Intra-Subject Variability

2020 ◽  
Vol 10 (10) ◽  
pp. 726
Author(s):  
Rupesh Kumar Chikara ◽  
Li-Wei Ko
Keyword(s):  
Discriminant Analysis ◽  
Response Inhibition ◽  
Classification System ◽  
Classification Accuracy ◽  
Stop Signal ◽  
Subject Classification ◽  
Stop Signal Task ◽  
Eeg Signals ◽  
Compulsive Disorder ◽  
Subject Variability

The stop signal task has been used to quantify the human inhibitory control. The inter-subject and intra-subject variability was investigated under the inhibition of human response with a realistic environmental scenario. In present study, we used a battleground scenario where a sniper-scope picture was the background, a target picture was a go signal, and a nontarget picture was a stop signal. The task instructions were to respond on the target image and inhibit the response if a nontarget image appeared. This scenario produced a threatening situation and endorsed the evaluation of how subject’s response inhibition manifests in a real situation. In this study, 32 channels of electroencephalography (EEG) signals were collected from 20 participants during successful stop (response inhibition) and failed stop (response) trials. These EEG signals were used to predict two possible outcomes: successful stop or failed stop. The inter-subject variability (between-subjects) and intra-subject variability (within-subjects) affect the performance of participants in the classification system. The EEG signals of successful stop versus failed stop trials were classified using quadratic discriminant analysis (QDA) and linear discriminant analysis (LDA) (i.e., parametric) and K-nearest neighbor classifier (KNNC) and Parzen density-based (PARZEN) (i.e., nonparametric) under inter- and intra-subject variability. The EEG activities were found to increase during response inhibition in the frontal cortex (F3 and F4), presupplementary motor area (C3 and C4), parietal lobe (P3 and P4), and occipital (O1 and O2) lobe. Therefore, power spectral density (PSD) of EEG signals (1-50Hz) in F3, F4, C3, C4, P3, P4, O1, and O2 electrodes were measured in successful stop and failed stop trials. The PSD of the EEG signals was used as the feature input for the classifiers. Our proposed method shows an intra-subject classification accuracy of 97.61% for subject 15 with QDA classifier in C3 (left motor cortex) and an overall inter-subject classification accuracy of 71.66% ± 9.81% with the KNNC classifier in F3 (left frontal lobe). These results display how inter-subject and intra-subject variability affects the performance of the classification system. These findings can be used effectively to improve the psychopathology of attention deficit hyperactivity disorder (ADHD), obsessive-compulsive disorder (OCD), schizophrenia, and suicidality.

scholarly journals Acute and chronic effects of cannabidiol on Δ⁹-tetrahydrocannabinol (Δ⁹-THC)-induced disruption in stop signal task performance.

2016 ◽  
Vol 24 (5) ◽  
pp. 320-330 ◽  
Author(s):  
David S. Jacobs ◽  
Stephen J. Kohut ◽  
Shan Jiang ◽  
Spyros P. Nikas ◽  
Alexandros Makriyannis ◽  
...  
Keyword(s):  
Task Performance ◽  
Stop Signal ◽  
Stop Signal Task ◽  
Chronic Effects ◽  
Acute And Chronic Effects
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