The Curve of Learning With and Without Instructions

In skill acquisition, instructing individuals the stimulus-response mappings indicating how to perform and act, yields better performance. Additionally, performance is helped by repeated practice. Whether providing instructions and repeated practice interact to achieve optimal performance remains debated. This paper addresses that question by analyzing the learning curves of individuals learning stimulus-response mappings of varying complexity. We particularly focus on the question whether instructions lead to improved performance in the longer run. Via evidence accumulation modeling, we find no evidence for this assertion. Instructions seem to provide individuals with a head start, leading to better initial performance in the early stages of learning, without long-lasting effects on behavior. We discuss the results in light of related studies that do report long-lasting effects of instructions, and propose that the complexity of a skill determines whether long-lasting benefits of initial instructions exist.

Eye did this! Sense of agency in eye movements

This study investigates the sense of agency (SoA) for saccades with implicit and explicit agency measures. In two eye tracking experiments, participants moved their eyes towards on-screen stimuli that subsequently changed color. Participants then either reproduced the temporal interval between saccade and color-change (Experiment 1) or reported the time points of these events with an auditory Libet clock (Experiment 2) to measure temporal binding effects as implicit indices of SoA. Participants were either made to believe to exert control over the color change or not (agency manipulation). Explicit ratings indicated that the manipulation of causal beliefs and hence agency was successful. However, temporal binding was only evident for caused effects, and only when a sufficiently sensitive procedure was used (auditory Libet clock). This suggests a feebler connection between temporal binding and SoA than previously proposed. The results also provide evidence for a relatively fast acquisition of sense of agency for previously never experienced types of action-effect associations. This indicates that the underlying processes of action control may be rooted in more intricate and adaptable cognitive models than previously thought. Oculomotor SoA as addressed in the present study presumably represents an important cognitive foundation of gaze-based social interaction (social sense of agency) or gaze-based human-machine interaction scenarios. PUBLIC SIGNIFICANCE STATEMENT: In this study, sense of agency for eye movements in the non-social domain is investigated in detail, using both explicit and implicit measures. Therefore, it offers novel and specific insights into comprehending sense of agency concerning effects induced by eye movements, as well as broader insights into agency pertaining to entirely newly acquired types of action-effect associations. Oculomotor sense of agency presumably represents an important cognitive foundation of gaze-based social interaction (social agency) or gaze-based human-machine interaction scenarios. Due to peculiarities of the oculomotor domain such as the varying degree of volitional control, eye movements could provide new information regarding more general theories of sense of agency in future research.

Characterizing Human Habits in the Lab

Habits pose a fundamental puzzle for those aiming to understand human behavior. They pervade our everyday lives and dominate some forms of psychopathology but are extremely hard to elicit in the lab. In this Registered Report, we developed novel experimental paradigms grounded in computational models, which suggest that habit strength should be proportional to the frequency of behavior and, in contrast to previous research, independent of value. Specifically, we manipulated how often participants performed responses in two tasks varying action repetition without, or separately from, variations in value. Moreover, we asked how this frequency-based habitization related to value-based operationalizations of habit and self-reported propensities for habitual behavior in real life. We find that choice frequency during training increases habit strength at test and that this form of habit shows little relation to value-based operationalizations of habit. Our findings empirically ground a novel perspective on the constituents of habits and suggest that habits may arise in the absence of external reinforcement. We further find no evidence for an overlap between different experimental approaches to measuring habits and no associations with self-reported real-life habits. Thus, our findings call for a rigorous reassessment of our understanding and measurement of human habitual behavior in the lab.

Dynamics of task preparation processes revealed by effect course analysis on response times and error rates

Cuing or executing a task impacts processing pathways for task-relevant information. While there is ample evidence that processing associated with task execution changes with practice, such evidence regarding cue-induced task preparation is scarce. Here we explored practice-related changes of processing pathways by task cuing in order to assess the plasticity of task preparation. We first developed and validated a new method for the study of practice-related changes, the effect course analysis. The effect course analysis is a model-free, non-parametric method designed to reveal effect changes within an experimental session on a continuous time scale. Then we applied this method to a new study in which cued task sets were supposed to remain activated during assessment of task-relevant pathways, as potential task execution was postponed at the end of the trial. The results showed that, with little practice, task cuing amplified task-relevant pathways, whereas this effect vanished with practice, suggesting that practice prompts fundamental changes of how task cues are used for task preparation. Hence, if one cannot be certain that cognitive processing is stationary, investigating the time course of experimental effects appears to be crucial to determine how cognitive processing is influenced by practice.

Task learning is subserved by a domain-general brain network

One of the most important human faculties is the ability to acquire not just new memories but the capacity to perform entirely new tasks. However, little is known about the brain mechanisms underlying the learning of novel tasks. Specifically, it is unclear to what extent learning of different tasks depends on domain-general and/or domain-specific brain mechanisms. Here human subjects (n = 45) learned to perform 6 new tasks while undergoing functional MRI. The different tasks required the engagement of perceptual, motor, and various cognitive processes related to attention, expectation, speed-accuracy tradeoff, and metacognition. We found that a bilateral frontoparietal network was more active during the initial compared with the later stages of task learning, and that this effect was stronger for task variants requiring more new learning. Critically, the same frontoparietal network was engaged by all 6 tasks, demonstrating its domain generality. Finally, although task learning decreased the overall activity in the frontoparietal network, it increased the connectivity strength between the different nodes of that network. These results demonstrate the existence of a domain-general brain network whose activity and connectivity reflect learning for a variety of new tasks, and thus may underlie the human capacity for acquiring new abilities.

Transfer of strategic task components across unique tasks that share some common structures

Flexible, adaptive behaviour depends on the application of prior learning to novel contexts (transfer). Transfer can take many forms, but the focus of the present study was on "task schemas"-learning strategies that guide the earliest stages of engaging in a novel task. The central aim was to examine the architecture of task schemas and determine whether strategic task components can expedite learning novel tasks that share some structural components with the training tasks. Groups of participants across two experiments were exposed to different training regimes centred around multiple unique tasks that shared some/all/none of the structural task components (the kinds of stimuli, classifications, and/or responses) but none of the surface features (the specific stimuli, classifications, and/or responses) with the test task (a dot-pattern classification task). Initial test performance was improved (to a degree) in all groups relative to a control group whose training did not include any of the structural components relevant to the test task. The strongest evidence of transfer was found in the motoric, perceptual + categorization, and full schema training groups. This observation indicates that training with some (or all) strategic task components expedited learning of a novel task that shared those components. That is, task schemas were found to be componential and were able to expedite learning a novel task where similar (learning) strategies could be applied to specific elements of the test task.

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).

Following Affirmative and Negated Rules

Rules are often stated in a negated manner ("no trespassing") rather than in an affirmative manner ("stay in your lane"). Here, we build on classic research on negation processing and, using a finger-tracking design on a touchscreen, we show that following negated rather than affirmative rules is harder as indicated by multiple performance measures. Moreover, our results indicate that practice has a surprisingly limited effect on negated rules, which are implemented more quickly with training, but this effect comes at the expense of reduced efficiency. Only affirmative rules are thus put into action efficiently, highlighting the importance of tailoring how rules are communicated to the peculiarities of the human mind.

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.

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.

Benefits and costs of self-paced preparation of novel task instructions

Rapidly executing novel instructions is a critical ability. However, it remains unclear whether longer preparation of novel instructions improves performance, and if so, whether this link is modulated by performance benefits and costs of preparation. Regarding the first question, we reanalysed previous data on novel instruction implementation and ran Experiment 1. Experiment 1 consisted of multiple mini-blocks, in which participants prepared four novel stimulus-response (S-R) mappings in a self-paced instruction phase. After participants indicated they were ready, one of the four stimuli was presented and they responded. The reanalysis and Experiment 1 showed that longer preparation indeed led to better performance. To examine if preparation was modulated when the benefits of preparation were reduced, we presented the correct response with the stimulus on some trials in Experiments 2 and 3. Preparation was shorter when the probability that the correct response was presented with the stimulus increased. In Experiment 4, we manipulated the costs of preparation by changing the S-R mappings between the instruction and execution phases on some trials. This had only limited effects on preparation time. In conclusion, self-paced preparation of novel instructions comes with performance benefits and costs, and participants adjust their preparation strategy to the task context.

Automatic effects of instructions: a tale of two paradigms

When examining rapid instructed task learning behaviorally, one out of two paradigms is usually used, the Inducer-Diagnostic (I-D) and the NEXT paradigm. Even though both paradigms are supposed to examine the same phenomenon of Automatic Effect of Instructions (AEI), there are some meaningful differences between them, notably in the size of the AEI. In the current work, we examined, in two pre-registered studies, the potential reasons for these differences in AEI size. Study 1 examined the influence of the data-analytic approach by comparing two existing relatively large data-sets, one from each paradigm (Braem et al., in Mem Cogn 47:1582–1591, 2019; Meiran et al., in Neuropsychologia 90:180–189, 2016). Study 2 focused on the influence of instruction type (concrete, as in NEXT, and abstract, as in I-D) and choice complexity of the task in which AEI-interference is assessed. We did that while using variants of the NEXT paradigm, some with modifications that approximated it to the I-D paradigm. Results from Study 1 indicate that the data-analytic approach partially explains the differences between the paradigms in terms of AEI size. Still, the paradigms remained different with respect to individual differences and with respect to AEI size in the first step following the instructions. Results from Study 2 indicate that Instruction type and the choice complexity in the phase in which AEI is assessed do not influence AEI size, or at least not in the expected direction. Theoretical and study-design implications are discussed.

Negative affordance effect: automatic response inhibition triggered by handle orientation of non-target object

Habituated response tendency associated with affordance of an object is automatically inhibited if this affordance cue is extracted from a non-target object. This study presents two go/no-go experiments investigating whether this response control operates in response selection processes and whether it is linked to conflict-monitoring mechanisms. In the first experiment, the participants performed responses with one hand, and in the second experiment, with two hands. In addition, both experiments consisted of two blocks with varying frequency of go conditions (25%-go vs. 75%-go). The non-target-related response inhibition effect was only observed in Experiment 2 when the task required selecting between two hands. Additionally, the results did not reveal patterns typically related to conflict monitoring when go-frequency is manipulated and when a stimulus-response compatibility effect is examined relative to congruency condition of the previous trial. The study shows that the non-target-related response inhibition assists hand selection and is relatively resistant to conflict-monitoring processes.

The Me-File: An Event-Coding Approach to Self-Representation

Numerous authors have taken it for granted that people represent themselves or even have something like “a self”, but the underlying mechanisms remain a mystery. How do people represent themselves? Here I propose that they do so not any differently from how they represent other individuals, events, and objects: by binding codes representing the sensory consequences of being oneself into a Me-File, that is, into an event file integrating all the codes resulting from the behaving me. This amounts to a Humean bundle-self theory of selfhood, and I will explain how recent extensions of the Theory of Event Coding, a general theory of human perception and action control, provide all the necessary ingredients for specifying the mechanisms underlying such a theory. The Me-File concept is likely to provide a useful mechanistic basis for more specific and more theoretically productive experimentation, as well as for the construction of artificial agents with human-like selves.

GOALIATH: a theory of goal-directed behavior

Commonsense and theorizing about action control agree in assuming that human behavior is (mainly) driven by goals, but no mechanistic theory of what goals are, where they come from, and how they impact action selection is available. Here I develop such a theory that is based on the assumption that GOALs guide Intentional Actions THrough criteria (GOALIATH). The theory is intended to be minimalist and parsimonious with respect to its assumptions, as transparent and mechanistic as possible, and it is based on representational assumptions provided by the Theory of Event Coding (TEC). It holds that goal-directed behavior is guided by selection criteria that activate and create competition between event files that contain action-effect codes matching one or more of the criteria-a competition that eventually settles into a solution favoring the best-matching event file. The criteria are associated with various sources, including biological drives, acquired needs (e.g., of achievement, power, or affiliation), and short-term, sometimes arbitrary, instructed aims. Action selection is, thus, a compromise that tries to satisfy various criteria related to different driving forces, which are also likely to vary in strength over time. Hence, what looks like goal-directed action emerges from, and represents an attempt to satisfy multiple constraints with different origins, purposes, operational characteristics, and timescales-which among other things does not guarantee a high degree of coherence or rationality of the eventual outcome. GOALIATH calls for a radical break with conventional theorizing about the control of goal-directed behavior, as it among other things questions existing cognitive-control theories and dual-route models of action control.

Learning the Abstract General Task Structure in a Rapidly Changing Task Content

The ability to learn abstract generalized structures of tasks is crucial for humans to adapt to changing environments and novel tasks. In a series of five experiments, we investigated this ability using a Rapid Instructed Task Learning paradigm (RITL) comprising short miniblocks, each involving two novel stimulus-response rules. Each miniblock included (a) instructions for the novel stimulus-response rules, (b) a NEXT phase involving a constant (familiar) intervening task (0–5 trials), (c) execution of the newly instructed rules (2 trials). The results show that including a NEXT phase (and hence, a prospective memory demand) led to relatively more robust abstract learning as indicated by increasingly faster responses with experiment progress. Multilevel modeling suggests that the prospective memory demand was just another aspect of the abstract task structure which has been learned.

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.

Research With Implicit Measures: Suggestions for a New Agenda of Sub-Personal Psychology

Research with implicit measures has been criticized for an unclear meaning of the term implicit and inadequate psychometric properties, as well as problems regarding internal validity and low predictive validity of implicit measures. To these criticisms, we add an overly restrictive theoretical focus and research agenda that is limited to the narrow dichotomy between associations versus propositional beliefs. In this article, we address the last problem by introducing a new perspective of a sub-personal psychology. This broad approach expands the conceptual horizon in order to make use of the full potential that experimental paradigms can offer for assessing, explaining, predicting, and modifying human functioning and behavior. Going beyond the analysis of associations and beliefs, we highlight the use of experimental paradigms to examine and modify motivational, environmental, and episodic memory factors that influence human action.

Erasing the Homunculus as an Ongoing Mission: A Reply to the Commentaries

In our recent article (Schmidt, Liefooghe, & De Houwer, 2020, this volume), we presented an adaptation of the Parallel Episodic Processing (PEP) model for simulating instruction following and task-switching behaviour. In this paper, we respond to five commentaries on our article: Monsell & McLaren (2020), Koch & Lavric (2020), Meiran (2020), Longman (2020), and Pfeuffer (2020). The commentaries discuss potential future modelling goals, deeper reflections on cognitive control, and some potential challenges for our theoretical perspective and associated model. We focus primarily on the latter. In particular, we clarify that we (a) acknowledge the role of cognitive control in task switching, and (b) are arguing that certain task-switching effects do not serve as a good measure of said cognitive control. We also discuss some ambiguities in terminological uses (e.g., the meaning of "task-set reconfiguration"), along with some future experimental and modelling research directions.

Investigating the effect of trustworthiness on instruction-based reflexivity

Unlike other species, humans are capable of rapidly learning new behavior from a single instruction. While previous research focused on the cognitive processes underlying the rapid, automatic implementation of instructions, the fundamentally social nature of instruction following has remained largely unexplored. Here, we investigated whether instructor trustworthiness modulates instruction implementation using both explicit and reflexive measures. In a first preregistered study, we validated a new paradigm to manipulate the perceived trustworthiness of two different virtual characters and showed that such a manipulation reliably induced implicit associations between the virtual characters and trustworthiness attributes. Moreover, we show that trustworthy instructors are followed more frequently and faster. In two additional preregistered experiments, we tested if trustworthiness towards the instructor influenced the cognitive processes underlying instruction implementation. While we show that verbally conveyed instructions led to automatic instruction implementation, this effect was not modulated by the trustworthiness of the instructor. Thus, we succeeded to design and validate a novel trustworthiness manipulation (Experiment 1) and to create a social variant of the instruction-based reflexivity paradigm (Experiments 2 and 3). However, this instruction-based reflexivity effect was not modulated by the instructors' trustworthiness.

Power of instructions for task implementation: superiority of explicitly instructed over inferred rules

"Power of instructions" originally referred to automatic response activation associated with instructed rules, but previous examination of the power of instructed rules in actual task implementation has been limited. Typical tasks involve both explicit aspects (e.g., instructed stimulus-response mapping rules) and implied, yet easily inferred aspects (e.g., be ready, attend to error beeps) and it is unknown if inferred aspects also become readily executable like their explicitly instructed counterparts. In each mini-block of our paradigm we introduced a novel two-choice task. In the instructions phase, one stimulus was explicitly mapped to a response; whereas the other stimulus' response mapping had to be inferred. Results show that, in most cases, explicitly instructed rules were implemented more efficiently than inferred rules, but this advantage was observed only in the first trial following instructions (though not in the first implementation of the rules), which suggests that the entire task set was implemented in the first trial. Theoretical implications are discussed.

On How Definitions of Habits Can Complicate Habit Research

The core message of this paper is that many of the challenges of habit research can be traced back to the presence of causal elements within the definition of habits. For instance, the idea that habits are stimulus-driven implies that habitual behavior is not causally mediated by goal-representations. The presence of these causal elements in the definition of habits leads to difficulties in establishing empirically whether behavior is habitual. Some of these elements can also impoverish theoretical thinking about the mechanisms underlying habitual behavior. I argue that habit research would benefit from eliminating any reference to specific S-R association formation theories from the definition of habits. Which causal elements are retained in the definition of habits depends on the goals of researchers. However, regardless of the definition that is selected, it is good to be aware of the implications of the definition of habits for empirical and theoretical research on habits.

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.

Working Memory and Attention - Response to Commentaries

This is a brief reply to the commentaries by Adam and deBettencourt (2019); Allen (2019); Kiyonaga (2019); Schneider (2019); and Van der Stigchel and Olivers (2019), focusing on four topics: (1) I defend the idea that attention need not be characterized as a limited resource. (2) I explain how I conceptualize the role of WM in cognitive control, and how recruitment of sensory processing networks contributes to control but not maintenance. (3) I discuss different ways in which information can be selectively prioritized during or after being encoded into WM, and the different consequences of these processes. (4) I argue that sustained attention to a task can be understood as the mind's ability to prioritize that task over task-unrelated representations.

Working Memory and Attention - A Conceptual Analysis and Review

There is broad agreement that working memory is closely related to attention. This article delineates several theoretical options for conceptualizing this link, and evaluates their viability in light of their theoretical implications and the empirical support they received. A first divide exists between the concept of attention as a limited resource, and the concept of attention as selective information processing. Theories conceptualizing attention as a resource assume that this resource is responsible for the limited capacity of working memory. Three versions of this idea have been proposed: Attention as a resource for storage and processing, a shared resource for perceptual attention and memory maintenance, and a resource for the control of attention. The first of these three is empirically well supported, but the other two are not. By contrast, when attention is understood as a selection mechanism, it is usually not invoked to explain the capacity limit of working memory - rather, researchers ask how different forms of attention interact with working memory, in two areas. The first pertains to attentional selection of the contents of working memory, controlled by mechanisms of filtering out irrelevant stimuli, and removing no-longer relevant representations from working memory. Within working memory contents, a single item is often selected into the focus of attention for processing. The second area pertains to the role of working memory in cognitive control. Working memory contributes to controlling perceptual attention - by holding templates for targets of perceptual selection - and controlling action - by holding task sets to implement our current goals.

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.

Theory of Mind Performance in Broad Autism Phenotype Groups: Between-Group Differences and Predictor Variables

Investigated between-group differences in cognitive/affective theory of mind (ToM) and predictors of cognitive ToM both within broad autism phenotype/non (BAP/Non-BAP) groups as well as across the sample. The BAP group (n = 45) performed worse than the Non-BAP group (n = 102) on the unexpected outcomes test (UOT), but groups were similar regarding reading the mind in the eyes test (RMET). Stepwise regression indicated RMET best predicted UOT for the BAP group; block design best predicted UOT in the Non-BAP group. BAP traits did not mediate the relation of RMET to UOT performance. While RMET and UOT appear similarly related in BAP/Non-BAP samples, use of emotion recognition abilities in a cognitive ToM task may reflect over-reliance on this skill in the BAP.

The instruction-based congruency effect predicts task execution efficiency: Evidence from inter- and intra-individual differences

In contrast to traditional conflict paradigms, which measure interference from (over)trained associations, recent paradigms have been introduced that investigate automatic interference from newly instructed, but never executed, associations. In these prospective-instruction paradigms, participants receive new task instructions (e.g., if cat press left, if dog press right), but before they have to apply the instructions, they are first presented with another task that measures the automatic interference from the instructed task information. The resulting instruction-based congruency (IBC) effect is assumed to reflect the strength with which instructions are encoded and maintained in view of their future application. If this assumption holds true, the IBC effect should be inversely related to the speed with which the task instructions are eventually executed. To test this hypothesis, we administered a prospective-instruction paradigm to a large sample of 184 participants and observed a negative correlation between the IBC effect and mean reaction time on the instructed task. Similarly, an analysis looking at within-subject variations in the IBC effect and instructed task reaction times showed the same negative relation. Finally, we also present additional analyses suggesting this effect is independent from standard (experience-based) interference effects, and report explorative analyses that tested possible correlations with personality trait questionaires. Together, these findings confirm a key assumption of the IBC effect in prospective-instruction paradigms, and further support the use of this paradigm in instruction research.

Rapid instructed task learning (but not automatic effects of instructions) is influenced by working memory load

The ability to efficiently perform actions immediately following instructions and without prior practice has previously been termed Rapid Instructed Task Learning (RITL). In addition, it was found that instructions are so powerful that they can produce automatic effects, reflected in activation of the instructions in an inappropriate task context. RITL is hypothesized to rely on limited working memory (WM) resources for holding not-yet implemented task rules. Similarly, automatic effects of instructions presumably reflect the operation of task rules kept in WM. Therefore, both were predicted to be influenced by WM load. However, while the involvement of WM in RITL is implicated from prior studies, evidence regarding WM involvement in instructions-based automaticity is mixed. In the current study, we manipulated WM load by increasing the number of novel task rules to be held in WM towards performance in the NEXT paradigm. In this task, participants performed a series of novel tasks presented in mini-blocks, each comprising a) instructions of novel task rules; b) a NEXT phase measuring the automatic activation of these instructed rules, in which participants advance the screen using a key-press; and c) a GO phase in which the new rules are first implemented and RITL is measured. In three experiments, we show a dissociation: While RITL (rule implementation) was impaired by increased WM load, the automatic effects of instructions were not robustly influenced by WM load. Theoretical implications are discussed.

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.

Incidental covariation learning leading to strategy change

As they approach a traffic light, drivers and pedestrians monitor the color (instructed stimulus feature) and/or the position of the signal (covarying stimulus feature) for response selection. Many studies have pointed out that instructions can effectively determine the stimulus features used for response selection in a task. This leaves open whether and how practice with a correlating alternative stimulus feature can lead to a strategy change from an instructed to a learned variant of performing the task. To address this question, we instructed participants to respond to the position of a stimulus within a reference frame, at the same time, during task performance, an unmentioned second stimulus feature, the color, covaried with stimulus position and allowed the use of an alternative response strategy. To assess the impact of the non-instructed stimulus feature of color on response selection throughout practice, the spatial position of the stimulus was ambiguous on some trials. Group average increases in color usage were based on a mixture of (1) participants who, despite extended practice on the covariation, exclusively relied on the instructed stimulus feature and (2) those who abruptly started to rely heavily on stimulus color to select responses in ambiguous trials. When the instructed and uninstructed feature predicted different actions, choices were still biased by the uninstructed color feature, albeit more weakly. A second experiment showed that the influence of color generalized across frequently and infrequently presented combinations of position and color. Strategy changes were accompanied by awareness in both experiments. The results suggest that incidental covariation learning can trigger spontaneous voluntary strategy change involving a re-configuration of the instructed task set.

Can we learn to learn? The influence of procedural working-memory training on rapid instructed-task-learning

Humans have the unique ability to efficiently execute instructions that were never practiced beforehand. In this Rapid Instructed-Task-Learning, not-yet-executed novel rules are presumably held in procedural working-memory (WM), which is assumed to hold stimulus-to-response bindings. In this study, we employed a computerized-cognitive training protocol targeting procedural WM to test this assumption and to examine whether the ability to rapidly learn novel rules can itself be learned. 175 participants were randomly assigned to one of three groups: procedural WM training (involving task-switching and N-back elements, all with novel rules; Shahar and Meiran in PLoS One 10(3):e0119992, 2015), active-control training (adaptive visual-search task), and no-contact control. We examined participants' rapid instructed-task-learning abilities before and after training, by administrating 55 novel choice tasks, and measuring their performance in the first two trials (where participants had no practice). While all participants showed shorter reaction-times in post vs. pretest, only participants in the procedural WM training group did not demonstrate an increased error rate at posttest. Evidence accumulation modelling suggested that this result stems from a reduction in decision threshold (the amount of evidence that needs to be gathered to reach a decision), which was more pronounced in the control groups; possibly accompanied by an increased drift-rate (the rate of evidence accumulation) only for the training group. Implication are discussed.

Getting a grip on cognitive flexibility

Cognitive flexibility refers to the ability to quickly reconfigure our mind, like when we switch between different tasks. This review highlights recent evidence showing that cognitive flexibility can be conditioned by simple incentives typically known to drive lower-level learning, such as stimulus-response associations. Cognitive flexibility can also become associated with, and triggered by, bottom-up contextual cues in our environment, including subliminal cues. Therefore, we suggest that the control functions that mediate cognitive flexibility are grounded in, and guided by, basic associative learning mechanisms, and abide by the same learning principles as more low-level forms of behavior. Such a learning perspective on cognitive flexibility offers new directions and important implications for further research, theory, and applications.

Encoding of Novel Verbal Instructions for Prospective Action in the Lateral Prefrontal Cortex: Evidence from Univariate and Multivariate Functional Magnetic Resonance Imaging Analysis

Verbal instructions are central to humans' capacity to learn new behaviors with minimal training, but the neurocognitive mechanisms involved in verbally instructed behaviors remain puzzling. Recent functional magnetic resonance imaging (fMRI) evidence suggests that the right middle frontal gyrus and dorsal premotor cortex (rMFG-dPMC) supports the translation of symbolic stimulus–response mappings into sensorimotor representations. Here, we set out to (1) replicate this finding, (2) investigate whether this region's involvement is specific to novel (vs. trained) instructions, and (3) study whether rMFG-dPMC also shows differences in its (voxel) pattern response indicative of general cognitive processes of instruction implementation. Participants were shown instructions, which they either had to perform later or merely memorize. Orthogonal to this manipulation, the instructions were either entirely novel or had been trained before the fMRI session. Results replicate higher rMFG-dPMC activation levels during instruction implementation versus memorization and show how this difference is restricted to novel, but not trained, instruction presentations. Pattern similarity analyses at the voxel level further reveal more consistent neural pattern responses in rMFG-dPMC during the implementation of novel versus trained instructions. In fact, this more consistent neural pattern response seemed to be specific to the first instruction presentation and disappeared after the instruction had been applied once. These results further support a role of rMFG-dPMC in the implementation of novel task instructions and highlight potentially important differences in studying this region's gross activation levels versus (the consistency of) its response patterns.

Structure and Implementation of Novel Task Rules: A Cross-Sectional Developmental Study

Rule-based performance improves remarkably throughout childhood. The present study examined how children and adolescents structured tasks and implemented rules when novel task instructions were presented in a child-friendly version of a novel instruction-learning paradigm. Each miniblock started with the presentation of new stimulus-response mappings for a go task. Before this mapping could be implemented, subjects had to make responses in order to advance through screens during a preparatory (" next") phase. Children (4-11 years old) and late adolescents (17-19 years old) responded more slowly during the next phase when the next response was incompatible with the instructed stimulus-response mapping. This instruction-based interference effect was more pronounced in young children than in older children. We argue that these findings are most consistent with age-related differences in rule structuring. We discuss the implications of our findings for theories of rule-based performance, instruction-based learning, and development.

Motor command inhibition and the representation of response mode during motor imagery

Research on motor imagery proposes that overt actions during motor imagery can be avoided by proactively signaling subthreshold motor commands to the effectors and by invoking motor-command inhibition. A recent study by Rieger, Dahm, and Koch (2017) found evidence in support of motor command inhibition, which indicates that MI cannot be completed on the sole basis of subthreshold motor commands. However, during motor imagery, participants know in advance when a covert response is to be made and it is thus surprising such additional motor-command inhibition is needed. Accordingly, the present study tested whether the demand to perform an action covertly can be proactively integrated by investigating the formation of task-specific action rules during motor imagery. These task-specific action rules relate the decision rules of a task to the mode in which these rules need to be applied (e.g., if smaller than 5, press the left key covertly). To this end, an experiment was designed in which participants had to switch between two numerical judgement tasks and two response modes: covert responding and overt responding. First, we observed markers of motor command inhibition and replicated the findings of Rieger and colleagues. Second, we observed evidence suggesting that task-specific action rules are created for the overt response mode (e.g., if smaller than 5, press the left key). In contrast, for the covert response mode, no task-specific action rules are formed and decision rules do not include mode-specific information (e.g., if smaller than 5, left).

Changing Deep-Rooted Implicit Evaluation in the Blink of an Eye: Negative Verbal Information Shifts Automatic Liking of Gandhi

It is often assumed that, once established, spontaneous or implicit evaluations are resistant to immediate change. Recent research contradicts this theoretical stance, showing that a person’s implicit evaluations of an attitude object can be changed rapidly in the face of new counterattitudinal information. Importantly, it remains unknown whether such changes can also occur for deep-rooted implicit evaluations of well-known attitude objects. We address this question by examining whether the acquisition of negative information changes implicit evaluations of a well-known positive historic figure: Mahatma Gandhi. We report three experiments showing rapid changes in implicit evaluations of Gandhi as measured with an affect misattribution procedure and evaluative priming task but not with an implicit association test (IAT). These findings suggest that implicit evaluations based on deep-rooted representations are subjective to rapid changes in the face of expectancy-violating information while pointing to limitations of the IAT for assessing such changes.