Automatic effects of instructions do not require the intention to execute these instructions

Concurrent response and action effect representations across the somatomotor cortices during novel task preparation

Instructions allow us to fulfill novel and complex tasks on the first try. This skill has been linked to preparatory brain signals that encode upcoming demands in advance, facilitating novel performance. To deepen insight into these processes, we explored whether instructions pre-activated task-relevant motoric and perceptual neural states. Critically, we addressed whether these representations anticipated activity patterns guiding overt sensorimotor processing, which could reflect that internally simulating novel tasks facilitates the preparation. To do so, we collected functional magnetic resonance imaging data while female and male participants encoded and implemented novel stimulus-response associations. Participants also completed localizer tasks designed to isolate the neural representations of the mappings-relevant motor responses, perceptual consequences, and stimulus categories. Using canonical template tracking, we identified whether and where these sensorimotor representations were pre-activated. We found that response-related templates were encoded in advance in regions linked with action control, entailing not only the instructed responses but also their somatosensory consequences. This result was particularly robust in primary motor and somatosensory cortices. While, following our predictions, we found a systematic decrease in the irrelevant stimulus templates' representational strength compared to the relevant ones, this difference was due to below-zero estimates linked to the irrelevant category activity patterns. Overall, our findings reflect that instruction processing relies on the sensorimotor cortices to anticipate motoric and kinesthetic representations of prospective action plans, suggesting the engagement of motor imagery during novel task preparation. More generally, they stress that the somatomotor system could participate with higher-level frontoparietal regions during anticipatory task control.

Instructing somebody else to act: motor co-representations in the instructor

Instructions enable humans to perform novel tasks quickly. This is achieved by creating and activating the instruction representation for upcoming tasks, which can then modulate ongoing task behaviour in an almost 'reflexive' manner, an effect called instruction-based reflexivity. While most research has focused on understanding how verbal instructions are represented within the 'instructed' (i.e. the person receiving instructions), here we focus on how the instructor's (i.e. the person giving instructions) behaviour is affected through instructing. In a series of three experiments and one pooled analysis, we extended the classical instruction-based reflexivity paradigm to a novel social variant in which the instructions are given by an instructor (rather than visual computer-generated instructions). We found an instruction-based reflexivity effect for the instructor, that is, the instructor's task performance was better on congruent compared to incongruent trials (i.e. Experiments 1 and 2, pooled analysis). This suggests that the instructor represents the instructions of the instructed in an action-oriented format. However, this did not depend on the specific task of the instructed (i.e. Experiment 1), nor is it exclusively social (i.e. Experiment 3).

Instructional load induces functional connectivity changes linked to task automaticity and mnemonic preference

Learning new rules rapidly and effectively via instructions is ubiquitous in our daily lives, yet the underlying cognitive and neural mechanisms are complex. Using functional magnetic resonance imaging we examined the effects of different instructional load conditions (4 vs. 10 stimulus-response rules) on functional couplings during rule implementation (always 4 rules). Focusing on connections of lateral prefrontal cortex (LPFC) regions, the results emphasized an opposing trend of load-related changes in LPFC-seeded couplings. On the one hand, during the low-load condition LPFC regions were more strongly coupled with cortical areas mostly assigned to networks such as the fronto-parietal network and the dorsal attention network. On the other hand, during the high-load condition, the same LPFC areas were more strongly coupled with default mode network areas. These results suggest differences in automated processing evoked by features of the instruction and an enduring response conflict mediated by lingering episodic long-term memory traces when instructional load exceeds working memory capacity limits. The ventrolateral prefrontal cortex (VLPFC) exhibited hemispherical differences regarding whole-brain coupling and practice-related dynamics. Left VLPFC connections showed a persistent load-related effect independent of practice and were associated with 'objective' learning success in overt behavioral performance, consistent with a role in mediating the enduring influence of the initially instructed task rules. Right VLPFC's connections, in turn, were more susceptible to practice-related effects, suggesting a more flexible role possibly related to ongoing rule updating processes throughout rule implementation.

Associative Learning from Verbal Action-Effect Instructions: A Replication and Investigation of Underlying Mechanisms

According to the ideomotor principle, repeated experience with an action and its perceivable consequences (effects) establish action-effect associations. Research on verbal instructions indicates that such associations are also acquired from verbal information. In the present experiment (N = 651), first, we aimed to replicate unintentional response-priming effects from verbal action-effect instructions (direct replication; Condition 1). Second, we investigated the involvement of perceptual processes in the verbally induced response-priming effect by perceptually presenting (Condition 1) versus not presenting (Condition 2) the color that was subsequently named as an effect in the instructions. Third, we tested a saliency-based explanation of the verbally induced response-priming effect by highlighting all components (action and effect) without an association between them (Condition 3). Overall, we found the predicted response-priming effect following verbal action-effect instructions (overall conditions and in the replication Condition 1). Condition 2, which did not include perceptual information in the instructions, still showed a significant response-priming effect but was descriptively weaker compared to the effect of the replication Condition 1. Condition 3, which merely highlighted the action and effect component without endorsing an association, did not show a significant effect. In sum, our study provides further solid evidence that verbal instructions lead to unintentional response-priming effects. Other conclusions must be considered preliminary: The between-condition comparisons were descriptively in the predicted direction-perceptual aspects are relevant, and a saliency-based account can be excluded-but the differences in accuracy between conditions were not statistically significant.

Unintentional response priming from verbal action-effect instructions

Action-effect learning is based on a theoretical concept that actions are associated with their perceivable consequences through bidirectional associations. Past research has mostly investigated how these bidirectional associations are formed through actual behavior and perception of the consequences. The present research expands this idea by investigating how verbally formulated action-effect instructions contribute to action-effect learning. In two online experiments (Exp. 1, N = 41, student sample; Exp. 2, N = 349, non-student sample), participants memorized a specific action-effect instruction before completing a speeded categorization task. We assessed the consequences of the instructions by presenting the instructed effect as an irrelevant stimulus in the classification task and compared response errors and response times for instruction-compatible and instruction-incompatible responses. Overall, we found evidence that verbal action-effect instructions led to associations between an action and perception (effect) that are automatically activated upon encountering the previously verbally presented effect. In addition, we discuss preliminary evidence suggesting that the order of the action-effect components plays a role; only instructions in a perception-action order showed the expected effect. The present research contributes evidence to the idea that action-effect learning is not exclusively related to actual behavior but also achievable through verbally formulated instructions, thereby providing a flexible learning mechanism that does not rely on specific actual experiences.

Articulatory suppression during instruction encoding impedes performance in choice reaction time tasks

Theories of instruction following assume that language contributes to our ability to understand and implement instructions. The two experiments reported here investigated that assumption. Participants (total N = 96) were required to learn a series of novel tasks, with each task consisting of six arbitrary stimulus-response rules. All tasks were preceded by an instruction phase (a visual depiction of the correct stimulus-response rules for each task), during which participants performed a verbal distractor task (articulatory suppression), a non-verbal distractor task (foot tapping) or no distractor task. Additionally, the duration of the instruction phase was varied so that it was either long (60 s) or short (30 s in Experiment 1, or 10 s in Experiment 2). In both experiments participants made more errors when they had performed articulatory suppression during the instruction interval, compared to the foot tapping and no distractor task conditions. Furthermore, Experiment 2 found that this detrimental effect of articulatory suppression was especially pronounced with a very short instruction duration. These findings demonstrate that language plays a crucial role in the encoding of novel task instructions, especially when instructions are encoded under time pressure.

Instructing item-specific switch probability: expectations modulate stimulus-action priming

Both active response execution and passive listening to verbal codes (a form of instruction) in single prime trials lead to item-specific repetition priming effects when stimuli re-occur in single probe trials. This holds for task-specific classification (stimulus-classification, SC priming, e.g., apple-small) and action (stimulus-action, SA priming, e.g., apple-right key press). To address the influence of expectation on item-specific SC and SA associations, we tested if item-specific SC and SA priming effects were modulated by the instructed probability of re-encountering individual SC or SA mappings (25% vs. 75% instructed switch probability). Importantly, the experienced item-specific switch probability was always 50%. In Experiment 1 (N = 78), item-specific SA/SC switch  expectations affected SA, but not SC priming effects exclusively following active response execution. Experiment 2 (N = 40) was designed to emphasize SA priming by only including item-specific SC repetitions. This yielded stronger SA priming for 25% vs. 75% expected switch probability, both following response execution as in Experiment 1 and also following verbally coded SA associations. Together, these results suggest that SA priming effects, that is, the encoding and retrieval of SA associations, is modulated by item-specific switch expectation. Importantly, this expectation effect cannot be explained by item-specific associative learning mechanisms, as stimuli were primed and probed only once and participants experienced item-specific repetitions/switches equally often across stimuli independent of instructed switch probabilities. This corroborates and extends previous results by showing that SA priming effects are modulated by  expectation not only based on experienced item-specific switch probabilities, but also on mere instruction.

Associations do not energize behavior: on the forgotten legacy of Kurt Lewin

Hundred years ago, Kurt Lewin published a series of articles in which he vehemently argued against the idea that associations between stimuli and responses motivate behavior. This article reviews his empirical work and theory and the cogency of Lewin's conclusion according to modern standards. We conclude that Lewin's criticism of the contiguity principle of associationism is still valid, and is now supported by a broad range of theories on learning, motivation, and action control. Implications for modern dual-system theory and modern theories on motivated action and (instructed) task sets are discussed.

Exploring the Link between Novel Task Proceduralization and Motor Simulation

Our ability to generate efficient behavior from novel instructions is critical for our adaptation to changing environments. Despite the absence of previous experience, novel instructed content is quickly encoded into an action-based or procedural format, facilitating automatic task processing. In the current work, we investigated the link between proceduralization and motor simulation, specifically, whether the covert activation of the task-relevant responses is used during the assembly of action-based instructions representations. Across three online experiments, we used a concurrent finger-tapping task to block motor simulation during the encoding of novel stimulus-response (S-R) associations. The overlap between the mappings and the motor task at the response level was manipulated. We predicted a greater impairment at mapping implementation in the overlapping condition, where the mappings' relevant response representations were already loaded by the motor demands, and thus, could not be used in the upcoming task simulation. This hypothesis was robustly supported by the three datasets. Nonetheless, the overlapping effect was not modulated by further manipulations of proceduralization-related variables (preparation demands in Exp.2, mapping novelty in Exp.3). Importantly, a fourth control experiment ruled out that our results were driven by alternative accounts as fatigue or negative priming. Overall, we provided strong evidence towards the involvement of motor simulation during anticipatory task reconfiguration. However, this involvement was rather general, and not restricted to novelty scenarios. Finally, these findings can be also integrated into broader models of anticipatory task control, stressing the role of the motor system during preparation.

Role of verbal working memory in rapid procedural acquisition of a choice response task

How quickly are instructions for a task translated into an effective task-set? If declarative working memory (dWM) is used to maintain a task's S-R rules until practice compiles them adequately into procedural memory, variables that affect retrieval from dWM should influence task performance while it is still dependent on dWM. Participants were trained on a series of 6-choice RT tasks, with a 1:1 mapping from object pictures to keys. In Experiments 1 and 2, an instruction phase - presentation of the S-R rules one by one -was followed by test trials. The phonological similarity of the objects' names significantly affected performance only during the first few encounters with the stimuli. Serial position effects were also consistent with retrieval from verbal dWM during those early trials. In Experiment 3, instruction onon the S-R rules was omitted, so participants had to learn the S-R mappings by trial and error alone; the effect of phonological similarity lasted longer, but still disappeared after a dozen encounters with each stimulus. Experiment 4 showed that instructions and just four trials of practice per S-R rule were sufficient to form a persisting representation of the S-R rules robust enough to interfere with later acquisition of a competing S-R rule after several minutes spent acquiring other task-sets. An effective and lasting task-set is rapidly compiled into procedural memory through instruction and early feedback; verbal dWM plays little role thereafter.

Automatic effects of covert practice

Automatic behaviour is supposedly underlain by the unintentional retrieval of processing episodes, which are stored during the repeated overt practice of a task or activity. In the present study, we investigated whether covertly practicing a task (e.g., repeatedly imagining responding to a stimulus) also leads to the storage of processing episodes and thus to automatic behaviour. Participants first either responded overtly or covertly to stimuli according to a first categorization task in a practice phase. We then measured the presence of automatic response-congruency effects in a subsequent test phase that involved a different categorization task but the same stimuli and responses. Our results indicate that covert practice can lead to a response-congruency effect. We conclude that covert practice can lead to automatic behaviour and discuss the different components of covert practice, such as motor imagery, visual imagery, and inner speech, that contribute to the formation of processing episodes in memory.

Neural oscillations track the maintenance and proceduralization of novel instructions

Humans are capable of flexibly converting symbolic instructions into novel behaviors. Previous evidence and theoretical models suggest that the implementation of a novel instruction requires the reformatting of its declarative content into an action-oriented code optimized for the execution of the instructed behavior. While neuroimaging research focused on identifying the brain areas involved in such a process, the temporal and electrophysiological mechanisms remain poorly understood. These mechanisms, however, can provide information about the specific cognitive processes that characterize the proceduralization of information. In the present study, we recorded EEG activity while we asked participants to either simply maintain declaratively the content of novel S-R mappings or to proactively prepare for their implementation. By means of time-frequency analyses, we isolated the oscillatory features specific to the proceduralization of instructions. Implementation of the instructed mappings elicited stronger theta activity over frontal electrodes and suppression in mu and beta activity over central electrodes. On the contrary, activity in the alpha band, which has been shown to track the attentional deployment to task-relevant items, showed no differences between tasks. Together, these results support the idea that proceduralization of information is characterized by specific component processes such as orchestrating complex task settings and configuring the motor system that are not observed when instructions are held in a declarative format.

The Magnitude Effect on Tactile Spatial Representation: The Spatial-Tactile Association for Response Code (STARC) Effect

The human brain uses perceptual information to create a correct representation of the external world. Converging data indicate that the perceptual processing of, space, and quantities frequently is based on a shared mental magnitude system, where low and high quantities are represented in the left and right space, respectively. The present study explores how the magnitude affects spatial representation in the tactile modality. We investigated these processes using stimulus-response (S-R) compatibility tasks (i.e., sensorimotor tasks that present an association/dissociation between the perception of a stimulus and the required action, generally increasing/decreasing accuracy and decreasing/increasing reaction times of the subject). In our study, the participant performed a discrimination task between high- and low-frequency vibrotactile stimuli, regardless of the stimulation’s spatial position. When the response code was incompatible with the mental magnitude line (i.e., left button for high-frequency and right button for low-frequency responses), we found that the participants bypassed the spatial congruence, showing a magnitude S-R compatibility effect. We called this phenomenon the Spatial–Tactile Association of Response Codes (STARC) effect. Moreover, we observed that the internal frame of reference embodies the STARC effect. Indeed, the participants’ performance reversed between uncrossed- and crossed-hands posture, suggesting that spatial reference frames play a role in the process of expressing mental magnitude, at least in terms of the tactile modality.

Social learning of action-effect associations: Modulation of action control following observation of virtual action's effects

A core assumption of ideomotor theory is that learned bidirectional associations between actions and their effects enable agents to select and initiate actions by anticipating their sensory consequences. Although the acquisition of bidirectional action-effect (A-E) associations built on the experience of one's own movements has received considerable empirical support, the available evidence for A-E learning through the observation of others' actions and their effects remains limited. In two experiments, we tested whether A-E associations could be acquired through social learning in an experimental setup involving observation of virtual actions. In an acquisition phase, participants repeatedly observed finger movements on a screen, and each movement was consistently followed by a specific effect tone. In the subsequent test phase, tones were presented as imperative stimuli in a reaction-time task. In both experiments, reaction times were shorter when tones required the same response with which they had been linked in the preceding observation phase, compared with when they required a different response, revealing the impact of A-E associations acquired through observation. Similar results were obtained whether the movements observed during the acquisition phase were spatially aligned (Experiment 1) or not (Experiment 2) with participants' responses in the test phase, ruling out the possibility that the results merely reflect spatial compatibility effects. Our findings add new evidence for an acquisition of A-E associations through observation. Importantly, we generalize this acquisition process to the observation of virtual actions. These findings further confirm effect-based action control, as proposed by ideomotor theory.

The effects of declaratively maintaining and proactively proceduralizing novel stimulus-response mappings

Working memory (WM) allows for the maintenance and manipulation of information when carrying out ongoing tasks. Recent models propose that representations in WM can be either in a declarative format (as content of thought) or in a procedural format (in an action-oriented state that drives the cognitive operation to be performed). Current views on the implementation of novel instructions also acknowledge this distinction, assuming these are first encoded as declarative content, and then reformatted into an action-oriented procedural representation upon task demands. Although it is widely accepted that WM has a limited capacity, little is known about the reciprocal costs of maintaining instructions in a declarative format and transforming them in an action code. In a series of three experiments, we asked participants to memorize two or four S-R mappings (i.e., declarative load), and then selected a subset of them by means of a retro-cue to trigger their reformatting into an action-oriented format (i.e., procedural load). We measured the performance in the implementation of the proceduralized mapping and in the declarative recall of the entire set of memorized mappings, to test how the increased load on one component affected the functioning of the other. Our results showed a strong influence of declarative load on the processing of the procedural component, but no effects in the opposite direction. This pattern of results suggests an asymmetry in the costs of maintenance and manipulation in WM, at least when procedural representations cannot be retrieved from long term memory and need to be reformatted online. The available resources seem to be first deployed for the maintenance of all the task-relevant declarative content, and proceduralization takes place to the extent the system can direct attention to the relevant instruction.

Neural representation of newly instructed rule identities during early implementation trials

By following explicit instructions, humans instantaneously get the hang of tasks they have never performed before. We used a specially calibrated multivariate analysis technique to uncover the elusive representational states during the first few implementations of arbitrary rules such as ‘for coffee, press red button’ following their first-time instruction. Distributed activity patterns within the ventrolateral prefrontal cortex (VLPFC) indicated the presence of neural representations specific of individual stimulus-response (S-R) rule identities, preferentially for conditions requiring the memorization of instructed S-R rules for correct performance. Identity-specific representations were detectable starting from the first implementation trial and continued to be present across early implementation trials. The increasingly fluent application of novel rule representations was channelled through increasing cooperation between VLPFC and anterior striatum. These findings inform representational theories on how the prefrontal cortex supports behavioral flexibility specifically by enabling the ad-hoc coding of newly instructed individual rule identities during their first-time implementation.

On the Assimilation of Instructions: Stimulus-response Associations are Implemented but not Stimulus-task Associations

The assimilation of instructions consists of two stages. First, a task model is formed on the basis of instructions. Second, this model is implemented, resulting in highly accessible representations, which enable reflexive behavior that guides the application of instructions. Research frequently demonstrated that instructions can lead to automatic response activation, which indicates that stimulus-response associations can be implemented on the basis of a task model. However, instructions not only indicate how to respond (stimulus-response mappings) but also when (i.e., the conditions under which mappings apply). Accordingly, we tested whether instruction implementation leads both to the activation of stimulus-response associations and of associations between stimuli and the context or task in which the instructed stimulus-response mappings are relevant (i.e., stimulus-task associations). In four experiments, we measured if implementing newly instructed stimulus-response mappings also leads to bivalence costs (i.e., shorter latencies when a stimulus can only occur in one task compared to when it can occur in two tasks), which indicate the presence of stimulus-task associations. We consistently observed automatic response activation on the basis of instructions, but no bivalence costs. A discrepancy thus exists between information conveyed in an instructed task model and the elements of that task model that are implemented. We propose that future research on automatic effects of instructions should broaden its scope and focus both on the formation of an instructed task model and its subsequent implementation.

Execution-based and verbal code-based stimulus-response associations: proportion manipulations reveal conflict adaptation processes in item-specific priming

Stimulus-response (S-R) associations consist of two independent components: Stimulus-classification (S-C) and stimulus-action (S-A) associations. Here, we examined whether these S-C and S-A associations were modulated by cognitive control operations. In two item-specific priming experiments, we systematically manipulated the proportion of trials in which item-specific S-C and/or S-A mappings repeated or switched between the single encoding (prime) and single retrieval (probe) instance of each stimulus (i.e., each stimulus appeared only twice). Thus, we assessed the influence of a list-level proportion switch manipulation on the strength of item-specific S-C and S-A associations. Participants responded slower and committed more errors when item-specific S-C or S-A mappings switched rather than repeated between prime and probe (i.e., S-C/S-A switch effects). S-C switch effects were larger when S-C repetitions rather than switches were frequent on the list-level. Similarly, S-A switch effects were modulated by S-A switch proportion. Most importantly, our findings rule out contingency learning and temporal learning as explanations of the observed results and point towards a conflict adaptation mechanism that selectively adapts the encoding and/or retrieval for each S-R component. Finally, we outline how cognitive control over S-R associations operates in the context of item-specific priming.

How Does the (Re)Presentation of Instructions Influence Their Implementation?

Instructions are so effective that they can sometimes affect performance beyond the instructed context. Such 'automatic' effects of instructions (AEI) have received much interest recently. It has been argued that AEI are restricted to relatively simple and specific S-R tasks or action plans. The present study put this idea further to the test. In a series of experiments based on the NEXT paradigm (Meiran, Pereg, Kessler, Cole, & Braver, 2015a) we investigated the specificity of AEI. In Experiment 1, we presented category-response instructions instead of S-R instructions. Nevertheless, we observed AEI for novel stimuli from the instructed category (Experiment 1a), and abstractness of the category did not modulate the size of the NEXT effect (Experiment 1b). However, Experiment 2 revealed specificity at the response level: AEI were much smaller in conditions where the instructed GO response is semantically related to, but procedurally different from the required NEXT response, compared to a condition where the NEXT and GO responses were the same. Combined, these findings indicate that AEI can occur when S(C)-R instructions are abstract at the stimulus level, arguing against previous proposals. However, AEI does seem to require specificity at the response level. We discuss implications for recent theories of instruction-based learning and AEI.