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 the premovement baseline period in stop blocks. 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.
By stopping actions even after their initiation, humans can flexibly adapt ongoing behavior to changing circumstances. The neural processes underlying the inhibition of movement during action-stopping are still controversial. In the 1990s, a fronto-central event-related potential (ERP) was discovered in the human EEG response to stop-signals in the classic stop-signal task, alongside a proposal that this "stop-signal P3" reflects an inhibitory process. Indeed, both amplitude and onset of the stop-signal P3 relate to overt behavior and movement-related EEG activity in ways predicted by the dominant models of action-stopping. However, neither EEG nor behavior allow direct inferences about the presence or absence of neurophysiological inhibition of the motor cortex, making it impossible to definitively relate the stop-signal P3 to inhibition. Here, we therefore present a multi-method investigation of the relationship between the stop-signal P3 and GABAergic signaling in primary motor cortex, as indexed by paired-pulse transcranial magnetic stimulation. In detail, we measured short-interval intracortical inhibition (SICI, a marker of inhibitory GABAa activity in M1) in a group of 41 human participants who also performed the stop-signal task while undergoing EEG recordings. In line with the P3-inhibition hypothesis, we found that subjects with stronger inhibitory GABA activity in M1 also showed both faster onsets and larger amplitudes of the stop-signal P3. This provides direct evidence linking the properties of this ERP to a true physiological index of motor system inhibition. We discuss these findings in the context of recent theoretical developments and empirical findings regarding the neural implementation of motor inhibition.
During goal-directed behavior, humans purportedly form and retrieve so-called event files, conjunctive representations that link context-specific information about stimuli, their associated actions, and the expected action outcomes. The automatic formation, and later retrieval, of such conjunctive representations can substantially facilitate efficient action selection. However, recent behavioral work suggests that these event files may also adversely affect future behavior, especially when action requirements have changed between successive instances of the same task context (e.g., during task switching). Here, we directly tested this hypothesis with a recently developed method for measuring the strength of the neural representations of context-specific stimulus–action conjunctions (i.e., event files). Thirty-five male and female adult humans performed a task switching paradigm while undergoing EEG recordings. Replicating previous behavioral work, we found that changes in action requirements between two spaced repetitions of the same task incurred a significant reaction time cost. By combining multivariate pattern analysis and representational similarity analysis of the EEG recordings with linear mixed-effects modeling of trial-to-trial behavior, we then found that the magnitude of this behavioral cost was directly proportional to the strength of the conjunctive representation formed during the most recent previous exposure to the same task, that is, the most recent event file. This confirms that the formation of conjunctive representations of specific task contexts, stimuli, and actions in the brain can indeed adversely affect future behavior. Moreover, these findings demonstrate the potential of neural decoding of complex task set representations toward the prediction of behavior beyond the current trial.SIGNIFICANCE STATEMENTUnderstanding how the human brain organizes individual components of complex tasks is paramount for understanding higher-order cognition. During complex tasks, the brain forms conjunctive representations that link individual task features (contexts, stimuli, actions), which aids future performance of the same task. However, this can have adverse effects when the required sequence of actions within a task changes. We decoded conjunctive representations from electroencephalographic recordings during a task that included frequent changes to the rules determining the response. Indeed, stronger initial conjunctive representations predicted significant future response-time costs when task contexts repeated with changed response requirements. Showing that the formation of conjunctive task representations can have negative future effects generates novel insights into complex behavior and cognition, including task switching, planning, and problem solving.
By stopping actions even after their initiation, humans can adapt their ongoing behavior rapidly to changing environmental circumstances. The neural processes underlying the implementation of rapid action-stopping are still controversially discussed. In the early 1990s, a fronto-central P3 event-related potential (ERP) was identified in the human EEG response following stop-signals in the classic stop-signal task, accompanied by the proposal that this ERP reflects the “inhibitory” side of the purported horse-race underlying successful action-stopping. Later studies have lent support to this interpretation by finding that the amplitude and onset of the stop-signal P3 relate to both overt behavior and to movement-related EEG activity in ways predicted by the race model. However, such studies are limited by the ability of EEG to allow direct inferences about the presence (or absence) of true, physiologically inhibitory signaling at the neuronal level. To address this, we here present a cross-modal individual differences investigation of the relationship between the features stop-signal P3 ERP and GABAergic neurotransmission in primary motor cortex (M1, as measured by paired-pulse transcranial magnetic stimulation). Following recent work, we measured short-interval intracortical inhibition (SICI), a marker of inhibitory GABAa activity in M1, in a group of 41 human participants who also performed the stop-signal task while undergoing EEG recordings. In line with the P3-inhibition hypothesis, we found that subjects with stronger inhibitory GABA activity in M1 also showed both faster onsets and larger amplitudes of the stop-signal P3. This provides direct evidence linking the properties of this ERP to a true physiological index of motor system inhibition. We discuss these findings in the context of recent theoretical developments and empirical findings regarding the neural implementation of inhibitory control during action-stopping.
During goal-directed behavior, humans purportedly form and retrieve so called 'event files' - conjunctive representations that link context-specific information about stimuli, their associated actions, and the expected action-outcomes. The automatic formation - and later retrieval - of such conjunctive 'event file' representations can substantially facilitate efficient action selection. However, recent behavioral work suggests that these event-files may also adversely affect future behavior, especially when action requirements have changed between successive instances of the same task context (e.g., during task-switching). Here, we directly tested this hypothesis through a recently developed method that allows measuring the strength of the neural representations of context-specific stimulus-action conjunctions (i.e., event files). Thirty-five male and female adult humans performed a task-switching paradigm while undergoing EEG recordings. Replicating previous behavioral work, we found that changes in action requirements between two spaced repetitions of the same task incurred a significant reaction time cost. By combining multi-variate pattern analysis and representational similarity analysis of the EEG recordings with linear mixed-effects modeling of trial-to-trial behavior, we then found that the magnitude of this behavioral cost was directly proportional to the strength of the conjunctive representation formed during the most recent previous exposure to the same task - i.e., the most recent 'event file'. This confirms that the formation of conjunctive representations of specific task contexts, stimuli, and actions in the brain can indeed adversely affect future behavior. Moreover, these findings demonstrate the potential of neural decoding of complex task set representations towards the prediction of behavior beyond the current trial.
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