Unsuccessful Stop Research Articles

On the Role of the Striatum in Response Inhibition

BackgroundStopping a manual response requires suppression of the primary motor cortex (M1) and has been linked to activation of the striatum. Here, we test three hypotheses regarding the role of the striatum in stopping: striatum activation during successful stopping may reflect suppression of M1, anticipation of a stop-signal occurring, or a slower response build-up.Methodology/Principal FindingsTwenty-four healthy volunteers underwent functional magnetic resonance imaging (fMRI) while performing a stop-signal paradigm, in which anticipation of stopping was manipulated using a visual cue indicating stop-signal probability, with their right hand. We observed activation of the striatum and deactivation of left M1 during successful versus unsuccessful stopping. In addition, striatum activation was proportional to the degree of left M1 deactivation during successful stopping, implicating the striatum in response suppression. Furthermore, striatum activation increased as a function of stop-signal probability and was to linked to activation in the supplementary motor complex (SMC) and right inferior frontal cortex (rIFC) during successful stopping, suggesting a role in anticipation of stopping. Finally, trial-to-trial variations in response time did not affect striatum activation.Conclusions/SignificanceThe results identify the striatum as a critical node in the neural network associated with stopping motor responses. As striatum activation was related to both suppression of M1 and anticipation of a stop-signal occurring, these findings suggest that the striatum is involved in proactive inhibitory control over M1, most likely in interaction with SMC and rIFC.

Interactions between cognition and motivation during response inhibition

A growing number of studies have investigated how motivation interacts with particular cognitive functions, including attention, working memory, and other executive functions. In these studies, the emphasis has been on understanding how motivation impacts brain regions that contribute to improving behavioral performance. Less is understood about how positive incentives may actually impair behavioral performance. Here, we were interested in investigating a situation in which reward would be potentially deleterious to behavioral performance. Specifically, we hypothesized that rewarding participants for correct going would impair stopping performance. Critically, we hypothesized that the effects on inhibition would be specific, namely, not simply attributable to a speeding-up of reaction time during go trials. To investigate the interaction between inhibition and motivation, participants performed a stop-signal task during two conditions, namely, during a neutral, control condition and during a rewarded condition during which they were rewarded for correct go performance. Behaviorally, participants exhibited longer stop-signal reaction times during the reward relative to the control condition, indicating that it was harder to inhibit their responses during the former condition. Neuroimaging findings revealed that a host of brain regions were involved in stop-signal inhibition, as indexed via the contrast of successful and unsuccessful stop trials. Critically, a subset of these regions, which included the right inferior frontal gyrus, the left precentral gyrus, and bilateral putamen, exhibited significant inhibition by condition interactions, demonstrating that cognitive and motivational signals interact in the brain during inhibitory control.

Intracranial EEG Reveals a Time- and Frequency-Specific Role for the Right Inferior Frontal Gyrus and Primary Motor Cortex in Stopping Initiated Responses

Inappropriate response tendencies may be stopped via a specific fronto/basal ganglia/primary motor cortical network. We sought to characterize the functional role of two regions in this putative stopping network, the right inferior frontal gyrus (IFG) and the primary motor cortex (M1), using electocorticography from subdural electrodes in four patients while they performed a stop-signal task. On each trial, a motor response was initiated, and on a minority of trials a stop signal instructed the patient to try to stop the response. For each patient, there was a greater right IFG response in the beta frequency band ( approximately 16 Hz) for successful versus unsuccessful stop trials. This finding adds to evidence for a functional network for stopping because changes in beta frequency activity have also been observed in the basal ganglia in association with behavioral stopping. In addition, the right IFG response occurred 100-250 ms after the stop signal, a time range consistent with a putative inhibitory control process rather than with stop-signal processing or feedback regarding success. A downstream target of inhibitory control is M1. In each patient, there was alpha/beta band desynchronization in M1 for stop trials. However, the degree of desynchronization in M1 was less for successfully than unsuccessfully stopped trials. This reduced desynchronization on successful stop trials could relate to increased GABA inhibition in M1. Together with other findings, the results suggest that behavioral stopping is implemented via synchronized activity in the beta frequency band in a right IFG/basal ganglia network, with downstream effects on M1.

Cortical activity during manual response inhibition guided by color and orientation cues

It has been suggested that the right inferior frontal gyrus (IFG) plays a critical role in manual response inhibition, although neuroimaging studies of healthy adults have also reported widespread activations in other cortical regions during a variety of response inhibition tasks. We conducted a functional magnetic resonance imaging (fMRI) experiment to examine whether the activation of the IFG is dependent on the type of visuo-motor associations during response inhibition by varying the feature of the stop signal (color vs. orientation) in the stop-signal task. Results from 12 subjects showed that the bilateral ventral posterior IFG, anterior insula, inferior frontal junction (IFJ), middle temporal gyrus (MTG) and fusiform gyrus (FG) are active during response inhibition cued by both color and orientation stop signals. While only the MTG showed differential activity to the two stop signals, both MTG and FG showed significantly stronger activity during successful than unsuccessful stopping of unwanted responses cued by orientation and color, respectively. Our findings suggest that the right ventral posterior IFG may play a more general role in response inhibition regardless of the feature of the visual signal, while successful inhibition may depend on efficient processing of the signal.

Sensory MEG Responses Predict Successful and Failed Inhibition in a Stop-Signal Task

In the present study magnetoencephalographic recordings were performed to investigate the neural mechanisms underlying the stopping of manual responses. Subjects performed in a Stop-signal task in which Go-stimuli (S1), requiring a rapid motor response, were sometimes rapidly followed by a Stop-stimulus (S2) indicating to withhold the already initiated response to S1. Success of stopping strongly depended on the early perceptual processing of S1 and S2 reflected by the magnetic N1 component. Enhanced processing of S1 facilitated the execution of the movement, whereas enhanced processing of S2 favored its inhibition. This suggests that the processing resources for the subsequent stimuli are limited and need to be shared. This sharing of resources appeared to arise from adjustments made on a trial-by-trial basis, in that systematic reaction time prolongations on Go-trials following Stop-trials versus following Go-trials were accompanied by attenuated sensory processing to the Go-stimulus similar to that seen in successful versus unsuccessful stopping in Stop-trials.

A failure to stop and attention fluctuations: An evoked oscillations study of the stop-signal paradigm

ObjectiveIt is not always clear whether inhibition or attention deficit underlies a failure to stop a prepared motor response. One possible way to approach this question is to resort to measures of evoked oscillations since functional correlates of different frequency oscillations are relatively well understood. MethodsThe present study examined event-related oscillations during a stop-signal task in non-clinical adults. In 25% of trials of an auditory discrimination tasks subjects had to refrain from a prepared motor response. ResultsIn successful stop trials, the Go N2 peaked later and the Stop N2 peaked earlier than in failed stop trials. Relative to successful, failed stop trials were associated with a larger N1–N2 and Go P3, and a smaller Stop P3 in the central and posterior cortical regions. The latter effect was exclusively determined by evoked delta oscillations, whereas all other frequency bands contributed to enhanced responses in failed comparative to successful stop trials. ConclusionsThe sum of presented evidence seems to show that success or failure to stop mostly depends on how the subject prepares for the Go and Stop stimuli in advance. If attention is more directed towards the Stop signal, the stopping succeeds, otherwise it fails. SignificanceThese data may contribute to understanding the cognitive basis of successful and unsuccessful stopping performance.

Long-term aftereffects of response inhibition: Memory retrieval, task goals, and cognitive control.

Cognitive control theories attribute control to executive processes that adjust and control behavior online. Theories of automaticity attribute control to memory retrieval. In the present study, online adjustments and memory retrieval were examined, and their roles in controlling performance in the stop-signal paradigm were elucidated. There was evidence of short-term response time adjustments after unsuccessful stopping. In addition, it was found that memory retrieval can slow responses for 1-20 trials after successful inhibition, which suggests the automatic retrieval of task goals. On the basis of these findings, the authors concluded that cognitive control can rely on both memory retrieval and executive processes.

Effects of stop-signal modality on the N2/P3 complex elicited in the stop-signal paradigm

The principal aim of the present study was to clarify how stop-signal modality affected the speed and efficacy of stopping, using ERP components as converging measures of stop processes. Both performance and ERP latency findings suggested faster processing of stop signals in the auditory than visual version of the stop task. The effects of successful versus unsuccessful stopping on the amplitude and topography of N2/P3 components elicited by the stop signals appeared to be largely independent of the modality of the stop signals. Stop signals elicited a fronto-central N2 that was much larger on unsuccessful than successful stop trials in stimulus-locked waveforms. N2 was followed by a P3 component that showed a fronto-central distribution on successful stop trials. P3 elicited on unsuccessful stop trials showed a posterior-parietal focus, but this topography was manifested more clearly in response-locked than stimulus-locked waveforms. A dipole source analyses confirmed these topographical differences of P3, and further showed that the location of the corresponding dipoles remained largely identical across the visual and auditory versions of the stop-signal task. Taken together, the present findings support the suggestion that ERP components in the stop task reflect endogenous aspects of stop-signal processing, such as effective inhibition of responses on successful stop trials and detection of errors on failed inhibition trials.

Predictors of Difficulty When Discontinuing Postmenopausal Hormone Therapy

In Brief OBJECTIVE To describe the experiences of postmenopausal women who try to stop hormone therapy and to identify characteristics associated with inability to stop. METHODS We conducted telephone interviews with 377 randomly selected female members of the Kaiser Foundation Health Plan, aged 50–69 years, who regularly used hormone therapy for at least 1 year before July 1, 2002 and had attempted to stop between July 2002 and March 2003. RESULTS Of the 377 women, 280 (74%) successfully stopped and 97 (26%) resumed taking hormone therapy. The major predictor of resuming hormone therapy use was the development of troublesome withdrawal symptoms (odds ratio 8.8; 95% confidence interval 4.9, 16.0). Report of hysterectomy, hormone therapy prescribed by a nongynecologist, and perception of high risk of hip or spine fracture were independently associated with a higher likelihood of unsuccessful stopping. Women with a hysterectomy who had used hormone therapy for 10 or more years and who started hormone therapy mainly for reasons other than health promotion were more likely (P < .001) to be unsuccessful in quitting (44%) compared with those with one or two (25%) or none (9%) of these three characteristics. Most successful stoppers (71%) stopped hormone therapy abruptly, but 29% tapered off hormone therapy; there was no difference in the incidence of troublesome withdrawal symptoms or successful quitting between these two groups. CONCLUSION Approximately one quarter of women who try to stop report that they are unable to discontinue postmenopausal hormone therapy, primarily because they develop troublesome withdrawal symptoms. Effective approaches to reducing hormone therapy withdrawal symptoms should be a priority for future research. Among postmenopausal women who tried to stop hormone therapy, 26% resumed treatment within a median time of 5.7 months, primarily because of troublesome withdrawal symptoms.

Predictors of difficulty when discontinuing postmenopausal hormone therapy

Objective To describe the experiences of postmenopausal women who try to stop hormone therapy and to identify characteristics associated with inability to stop. Methods We conducted telephone interviews with 377 randomly selected female members of the Kaiser Foundation Health Plan, aged 50–69 years, who regularly used hormone therapy for at least 1 year before July 1, 2002 and had attempted to stop between July 2002 and March 2003. Results Of the 377 women, 280 (74%) successfully stopped and 97 (26%) resumed taking hormone therapy. The major predictor of resuming hormone therapy use was the development of troublesome withdrawal symptoms (odds ratio 8.8; 95% confidence interval 4.9, 16.0). Report of hysterectomy, hormone therapy prescribed by a nongynecologist, and perception of high risk of hip or spine fracture were independently associated with a higher likelihood of unsuccessful stopping. Women with a hysterectomy who had used hormone therapy for 10 or more years and who started hormone therapy mainly for reasons other than health promotion were more likely ( P < .001) to be unsuccessful in quitting (44%) compared with those with one or two (25%) or none (9%) of these three characteristics. Most successful stoppers (71%) stopped hormone therapy abruptly, but 29% tapered off hormone therapy; there was no difference in the incidence of troublesome withdrawal symptoms or successful quitting between these two groups. Conclusion Approximately one quarter of women who try to stop report that they are unable to discontinue postmenopausal hormone therapy, primarily because they develop troublesome withdrawal symptoms. Effective approaches to reducing hormone therapy withdrawal symptoms should be a priority for future research.

ERP components associated with successful and unsuccessful stopping in a stop-signal task.

The primary aim of this study was to examine how response inhibition is reflected in components of the event-related potential (ERP), using the stop-signal paradigm as a tool to manipulate response inhibition processes. Stop signals elicited a sequence of N2/P3 components that partly overlapped with ERP components elicited by the reaction stimulus. N2/P3 components were more pronounced on stop-signal trials than on no-stop-signal trials. At Cz, the stop-signal P3 peaked earlier on successful than on unsuccessful stop trials. This finding extends the horse race model by demonstrating that the internal response to the stop signal (as reflected in stop-signal P3) is not constant, but terminates at different moments in time on successful and unsuccessful stop trials. In addition, topographical distributions and dipole analysis of high density EEG recordings indicated that different cortical generators were involved in P3s elicited on successful and unsuccessful stop-signal trials. The latter results suggest that P3 on successful stop-signal trials not only reflects stop-signal processing per se, but also efficiency of inhibitory control.

Neural substrates of successful versus unsuccessful stopping in a cognitively challenging event related stop task

Neural substrates of successful versus unsuccessful stopping in a cognitively challenging event related stop task

2206 Neuronal activity in the inferior prefrontal cortex of the monkey during conditional visuomotor learning

The abilities to inhibit impulses and withdraw certain responses are critical for human's survival in a fast-changing environment. These processes happen fast, in a complex manner, and sometimes are difficult to capture with fMRI or mean electrophysiological brain signal alone. Therefore, an alternative measure that can reveal the efficiency of the neural mechanism across multiple timescales is needed for the investigation of these brain functions. The present study employs a new approach to analyzing electroencephalography (EEG) signal: the multiscale entropy (MSE), which groups data points with different timescales to reveal any occurrence of repeated patterns, in order to theoretically quantify the complexity (indicating adaptability and efficiency) of neural systems during the process of inhibitory control. From this MSE perspective, EEG signals of successful stop trials are more complex and information rich than that of unsuccessful stop trials. We further applied transcranial direct current stimulation (tDCS), with anodal electrode over presupplementary motor area (preSMA), to test the relationship between behavioral modification with the complexity of EEG signals. We found that tDCS can further increase the EEG complexity of the frontal lobe. Furthermore, the MSE pattern was found to be different between high and low performers (divided by their stop-signal reaction time), where the high-performing group had higher complexity in smaller scales and less complexity in larger scales in comparison to the low-performing group. In addition, this between-group MSE difference was found to interact with the anodal tDCS, where the increase of MSE in low performers benefitted more from the anodal tDCS. Together, the current study demonstrates that participants who suffer from poor inhibitory control can efficiently improve their performance with 10 min of electrical stimulation, and such cognitive improvement can be effectively traced back to the complexity within the EEG signals via MSE analysis, thereby offering a theoretical basis for clinical intervention via tDCS for deficits in inhibitory control.