An official website of the United States government
Abstract Classic work using the stop-signal task has shown that humans can use inhibitory control to cancel already initiated movements. Subsequent work revealed that inhibitory control can be proactively recruited in anticipation of a potential stop-signal, thereby increasing the likelihood of successful movement cancellation. However, the exact neurophysiological effects of proactive inhibitory control on the motor system are still unclear. On the basis of classic views of sensorimotor β-band activity, as well as recent findings demonstrating the burst-like nature of this signal, we recently proposed that proactive inhibitory control is implemented by influencing the rate of sensorimotor β-bursts during movement initiation. Here, we directly tested this hypothesis using scalp EEG recordings of β-band activity in 41 healthy human adults during a bimanual RT task. By comparing motor responses made in two different contexts—during blocks with or without stop-signals—we found that premovement β-burst rates over both contralateral and ipsilateral sensorimotor areas were increased in stop-signal blocks compared to pure-go blocks. Moreover, the degree of this burst rate difference indexed the behavioral implementation of proactive inhibition (i.e., the degree of anticipatory response slowing in the stop-signal blocks). Finally, exploratory analyses showed that these condition differences were explained by a significant increase in β bursting that was already present during baseline period before the movement initiation signal. Together, this suggests that the strategic deployment of proactive inhibitory motor control is implemented by upregulating the tonic inhibition of the motor system, signified by increased sensorimotor β-bursting both before and after signals to initiate a movement.
more »
« less
Transcranial focused ultrasound to human rIFG improves response inhibition through modulation of the P300 onset latency
Response inhibition in humans is important to avoid undesirable behavioral action consequences. Neuroimaging and lesion studies point to a locus of inhibitory control in the right inferior frontal gyrus (rIFG). Electrophysiology studies have implicated a downstream event-related potential from rIFG, the fronto-central P300, as a putative neural marker of the success and timing of inhibition over behavioral responses. However, it remains to be established whether rIFG effectively drives inhibition and which aspect of P300 activity uniquely indexes inhibitory control—ERP timing or amplitude. Here, we dissect the connection between rIFG and P300 for inhibition by using transcranial-focused ultrasound (tFUS) to target rIFG of human subjects while they performed a Stop-Signal task. By applying tFUS simultaneously with different task events, we found behavioral inhibition was improved, but only when applied to rIFG simultaneously with a ‘stop’ signal. Improved inhibition through tFUS to rIFG was indexed by faster stopping times that aligned with significantly shorter N200/P300 onset latencies. In contrast, P300 amplitude was modulated during tFUS across all groups without a paired change in behavior. Using tFUS, we provide evidence for a causal connection between anatomy, behavior, and electrophysiology underlying response inhibition.
more »
« less
- Award ID(s):
- 2220677
- PAR ID:
- 10545239
- Publisher / Repository:
- eLife
- Date Published:
- Journal Name:
- eLife
- Volume:
- 12
- ISSN:
- 2050-084X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Although coming down with an illness or receiving a vaccine are both common experiences, the influence of such acute immune system activations on cognitive processes, such as inhibitory control, has received relatively little attention. We addressed that issue by assessing the effects of acute immune system activation on inhibitory control in a randomized controlled experiment, and by conducting a meta-analysis of similar studies in humans. In our experiment, we found—somewhat surprisingly—that influenza vaccination improved performance on both of our inhibitory control outcomes (i.e., stop-signal reaction times and flanker interference effects). At the meta-analytic level, we found that at a short delay (1.5–4 hours post-injection) between immune activation and inhibitory control assessment, such activation impaired multiple forms of inhibitory control, whereas after a longer delay (e.g., > 18 hours post-injection), such activation improved inhibitory control—consistent with our experiment. Moreover, proinflammatory cytokine activity predicted poorer interference control but better response inhibition, even with a long delay between injection and testing. Together, these results highlight nuanced, time-dependent, and—perhaps—multiple-mechanism-driven effects of acute immune system activity on inhibitory control.more » « less
-
The stop signal task (SST) is the gold standard experimental model of inhibitory control. However, neither SST condition–contrast (stop vs. go, successful vs. failed stop) purely operationalizes inhibition. Because stop trials include a second, infrequent signal, the stop versus go contrast confounds inhibition with attentional and stimulus processing demands. While this confound is controlled for in the successful versus failed stop contrast, the go process is systematically faster on failed stop trials, contaminating the contrast with a different noninhibitory confound. Here, we present an SST variant to address both confounds and evaluate putative neural indices of inhibition with these influences removed. In our variant, stop signals occurred on every trial, equating the noninhibitory demands of the stop versus go contrast. To entice participants to respond despite the impending stop signals, responses produced before stop signals were rewarded. This also reversed the go process bias that typically affects the successful versus failed stop contrast. We recorded scalp electroencephalography in this new version of the task (as well as a standard version of the SST with infrequent stop signal) and found that, even under these conditions, the properties of the frontocentral stop signal P3 ERP remained consistent with the race model. Specifically, in both tasks, the amplitude of the P3 was increased on stop versus go trials. Moreover, the onset of this P3 occurred earlier for successful compared with failed stop trials in both tasks, consistent with the proposal of the race model that an earlier start of the inhibition process will increase stopping success. Therefore, the frontocentral stop signal P3 represents a neural process whose properties are in line with the predictions of the race model of motor inhibition, even when the SST's confounds are controlled.more » « less
-
Background Inhibitory control, or inhibition, is one of the core executive functions of humans. It contributes to our attention, performance, and physical and mental well-being. Our inhibitory control is modulated by various factors and therefore fluctuates over time. Being able to continuously and unobtrusively assess our inhibitory control and understand the mediating factors may allow us to design intelligent systems that help manage our inhibitory control and ultimately our well-being. Objective The aim of this study is to investigate whether we can assess individuals’ inhibitory control using an unobtrusive and scalable approach to identify digital markers that are predictive of changes in inhibitory control. Methods We developed InhibiSense, an app that passively collects the following information: users’ behaviors based on their phone use and sensor data, the ground truths of their inhibition control measured with stop-signal tasks (SSTs) and ecological momentary assessments (EMAs), and heart rate information transmitted from a wearable heart rate monitor (Polar H10). We conducted a 4-week in-the-wild study, where participants were asked to install InhibiSense on their phone and wear a Polar H10. We used generalized estimating equation (GEE) and gradient boosting tree models fitted with features extracted from participants’ phone use and sensor data to predict their stop-signal reaction time (SSRT), an objective metric used to measure an individual’s inhibitory control, and identify the predictive digital markers. Results A total of 12 participants completed the study, and 2189 EMAs and SST responses were collected. The results from the GEE models suggest that the top digital markers positively associated with an individual’s SSRT include phone use burstiness (P=.005), the mean duration between 2 consecutive phone use sessions (P=.02), the change rate of battery level when the phone was not charged (P=.04), and the frequency of incoming calls (P=.03). The top digital markers negatively associated with SSRT include the standard deviation of acceleration (P<.001), the frequency of short phone use sessions (P<.001), the mean duration of incoming calls (P<.001), the mean decibel level of ambient noise (P=.007), and the percentage of time in which the phone was connected to the internet through a mobile network (P=.001). No significant correlation between the participants’ objective and subjective measurement of inhibitory control was found. Conclusions We identified phone-based digital markers that were predictive of changes in inhibitory control and how they were positively or negatively associated with a person’s inhibitory control. The results of this study corroborate the findings of previous studies, which suggest that inhibitory control can be assessed continuously and unobtrusively in the wild. We discussed some potential applications of the system and how technological interventions can be designed to help manage inhibitory control.more » « less
-
null (Ed.)Despite the well-defined behavioral criteria for posttraumatic stress disorder (PTSD), clinical care is com- plicated by the heterogeneity of biological factors underly- ing impairment. Eye movement tasks provide an opportunity to assess the relationships between aberrant neurobiological function and non-volitional performance metrics that are not dependent on self-report. A recent study using an emotional variant of the antisaccade task demonstrated attentional control biases that interfered with task performance in Veterans with PTSD. Here we present a neuroanatomically-inspired com- putational model based on gated attractor networks that is designed to replicate oculomotor behavior on an affective anti- saccade task. The model includes the putative neural circuitry underlying fear response (amygdala) and top-down inhibitory control (prefrontal cortex), and is capable of generating testable predictions about the causal implications of changes in this circuitry on task performance and neural activation associated with PTSD. Calibrating the model with the results of behavioral and neuroimaging studies on patient populations yields a pattern of connectivity changes characterized by increased amygdala sensitivity and reduced top-down prefrontal control that is consistent with the fear conditioning model of PTSD. In addition, the model makes experimentally verifiable predictions about the consequences of increased prefrontal connectivity associated with cognitive reappraisal training. Keywords: posttraumatic stress disorder, antisaccade task, inhibitory control deficits, attentional bias, cognitive control.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.7554/eLife.86190
