Planning on Autopilot? Associative Contributions to Proactive Control

Proactive cognitive control is thought to rely on the active maintenance of goals or contextual information in working memory. It is often measured using the AX-CPT, in which antecedent cues (A/B) are used to proactively prepare a response to a subsequently-presented probe (X/Y). Although control in this task purportedly requires active maintenance of information in working memory, it also provides conditions in which learning the contingencies between relevant events could influence performance via associative learning. We tested this hypothesis using a dot-pattern expectancy version of the AX-CPT whereby a set of new rules (test phase) for responding changed the control operations required for some previously trained cues, while keeping the operations the same for others, allowing us to measure associative interference. We also tested the relationship between associative interference and working memory capacity (operation span; Experiments 1-3) and tested the effect of applying working memory load during the initial acquisition period (Experiment 2) and during the test phase (Experiment 3). We found robust evidence of interference after the rule change based on previously learnt contingencies, suggesting that learnt contingencies come to influence proactive planning, even when they are task-irrelevant. This associative effect had no relationship with working memory capacity or load, based on a load manipulation commonly used in executive control tasks. The findings suggest that proactive control does not always require active maintenance of current goals and environmental cues in working memory. Instead, proactive control may run on autopilot if the individual can rely upon stable relationships in the environment to trigger planning and preparation. SIGNIFICANCE: Navigating daily life requires us to anticipate future events and plan our thoughts and actions accordingly to achieve our goals. This forward planning, or proactive control, is thought to be a resource-intensive and metabolically costly process that recruits higher-order cognitive functions, such as working memory, where relevant thoughts and actions have to be maintained online. The current study challenged this notion by finding that proactive control can be incrementally relegated to simpler processes based on one's learning of stable relationships in the environment, thereby reducing the need to actively maintain information online. Individuals can come to rely on underlying contingencies in stimuli associated with proactive control, even when it is detrimental to their goals.

TMS reveals distinct patterns of proactive and reactive inhibition in motor system activity

Response inhibition is our ability to suppress or cancel actions when required. Deficits in response inhibition are linked with a range of psychopathological disorders including addiction and OCD. Studies on response inhibition have largely focused on reactive inhibition-stopping an action when explicitly cued. Less work has examined proactive inhibition-preparation to stop ahead of time. In the current experiment, we studied both reactive and proactive inhibition by adopting a two-step continuous performance task (e.g., "AX"-CPT) often used to study cognitive control. By combining a dot pattern expectancy (DPX) version of this task with transcranial magnetic stimulation (TMS), we mapped changes in reactive and proactive inhibition within the motor system. Measured using motor-evoked potentials, we found modulation of corticospinal excitability at critical timepoints during the DPX when participants were preparing in advance to inhibit a response (at step 1: during the cue) and while inhibiting a response (at step 2: during the probe). Notably, motor system activity during early timepoints was predicted by a behavioural index of proactive capacity and could predict whether participants would later successfully inhibit their response. Our findings demonstrate that combining TMS with a two-step CPT such as the DPX can be useful for studying reactive and proactive inhibition, and reveal that successful inhibition is determined earlier than previously thought.

Working memory load reduces corticospinal suppression to former go and trained no-go cues

Environmental cues associated with an action can prime the motor system, decreasing response times and activating motor regions of the brain. However, when task goals change, the same responses to former go-associated cues are no longer required and motor priming needs to be inhibited to avoid unwanted behavioural errors. The present study tested whether the inhibition of motor system activity to presentations of former go cues is reliant on top-down, goal-directed cognitive control processes using a working memory (WM) load manipulation. Applying transcranial magnetic stimulation over the primary motor cortex to measure motor system activity during a Go/No-go task, we found that under low WM, corticospinal excitability was suppressed to former go and trained no-go cues relative to control cues. Under high WM, the cortical suppression to former go cues was reduced, suggesting that the underlying mechanism required executive control. Unexpectedly, we found a similar result for trained no-go cues and showed in a second experiment that the corticospinal suppression and WM effects were unrelated to local inhibitory function as indexed by short-interval intracortical inhibition. Our findings reveal that the interaction between former response cues and WM is complex and we discuss possible explanations of our findings in relation to models of response inhibition.

Sensory attenuation is modulated by the contrasting effects of predictability and control

Self-generated stimuli have been found to elicit a reduced sensory response compared with externally-generated stimuli. However, much of the literature has not adequately controlled for differences in the temporal predictability and temporal control of stimuli. In two experiments, we compared the N1 (and P2) components of the auditory-evoked potential to self- and externally-generated tones that differed with respect to these two factors. In Experiment 1 (n = 42), we found that increasing temporal predictability reduced N1 amplitude in a manner that may often account for the observed reduction in sensory response to self-generated sounds. We also observed that reducing temporal control over the tones resulted in a reduction in N1 amplitude. The contrasting effects of temporal predictability and temporal control on N1 amplitude meant that sensory attenuation prevailed when controlling for each. Experiment 2 (n = 38) explored the potential effect of selective attention on the results of Experiment 1 by modifying task requirements such that similar levels of attention were allocated to the visual stimuli across conditions. The results of Experiment 2 replicated those of Experiment 1, and suggested that the observed effects of temporal control and sensory attenuation were not driven by differences in attention. Given that self- and externally-generated sensations commonly differ with respect to both temporal predictability and temporal control, findings of the present study may necessitate a re-evaluation of the experimental paradigms used to study sensory attenuation.

Expected TMS excites the motor system less effectively than unexpected stimulation

The brain's response to sensory input is modulated by prediction. For example, sounds that are produced by one's own actions, or those that are strongly predicted by environmental cues, elicit an attenuated N1 component in the auditory evoked potential. It has been suggested that this form of sensory attenuation to stimulation produced by one's own actions is the reason we are unable to tickle ourselves. Here we examined whether the neural response to direct stimulation of the brain is attenuated by prediction in a similar manner. Transcranial magnetic stimulation (TMS) applied over primary motor cortex can be used to gauge the excitability of the motor system. Motor-evoked potentials (MEPs), elicited by TMS and measured in peripheral muscles, are larger when actions are being prepared and smaller when actions are voluntarily suppressed. We tested whether the amplitude of MEPs was attenuated under circumstances where the TMS pulse can be reliably predicted, even though control of the relevant motor effector was never required. Self-initiation of the TMS pulse and reliable cuing of the TMS pulse both produced attenuated MEP amplitudes, compared to those generated programmatically in an unpredictable manner. These results suggest that predictive coding may be governed by domain-general mechanisms responsible for all forms predictive learning. The findings also have important methodological implications for designing TMS experiments that control for the predictability of TMS pulses.

The impact of implicit and explicit suggestions that 'there is nothing to learn' on implicit sequence learning

We can sometimes efficiently pick up statistical regularities in our environment in the absence of clear intentions or awareness, a process typically referred to as implicit sequence learning. In the current study, we tried to address the question whether suggesting participants that there is nothing to learn can impact this form of learning. If a priori predictions or intentions to learn are important in guiding implicit learning, we reasoned that suggesting participants that there is nothing to learn in a given context should hamper implicit learning. We introduced participants to random contexts that indicated that there was nothing to learn, either implicitly (i.e., by presenting blocks of random trials in "Experiment 1"), or explicitly (i.e., by explicitly instructing them in "Experiment 2"). Next, in a subsequent learning phase, participants performed an implicit sequence learning task. We found that these implicit or explicit suggestions that 'there was nothing to learn' did not influence the emergence of implicit knowledge in the subsequent learning phase. Although these findings seem consistent with simple associative or Hebbian learning accounts of implicit sequence learning (i.e., not steered by predictions), we discuss potential limitations that should inform future studies on the role of a priori predictions in implicit learning.