The power of instructions: Proactive configuration of stimulus-response translation

The P300 wave is decomposed into components reflecting response selection and automatic reactivation of stimulus-response links

The parietal P300 wave of event-related potentials (ERPs) has been associated with various psychological operations in numerous laboratory tasks. This study aims to decompose the P3 wave of ERPs into subcomponents and link them with behavioral parameters, such as the strength of stimulus-response (S-R) links and GO/NOGO responses. EEGs (31 channels), referenced to linked ears, were recorded from 172 healthy adults (107 women) who participated in two cued GO/NOGO tasks, where the strength of S-R links was manipulated through instructions. P300 waves were observed in active conditions in response to cues, GO/NOGO stimuli, and in passive conditions when no manual response was required. Utilizing a combination of current source density transformation and blind source separation methods, we decomposed the P300 wave into two distinct components, purportedly originating from different parts of the parietal lobules. The amplitude of the parietal midline component (with current sources around Pz) closely mirrored the strength of the S-R link across proactive, reactive, and passive conditions. The amplitude of the lateral parietal component (with current sources around P3 and P4) resembled the push-pull activity of the output nuclei of the basal ganglia in action selection-inhibition operations. These findings provide insights into the neural mechanisms underlying action selection processes and the reactivation of S-R links.

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.

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.

Using position rather than color at the traffic light - Covariation learning-based deviation from instructions in attention deficit/hyperactivity disorder

Based on instructions people can form task representations that shield relevant from seemingly irrelevant information. It has been documented that instructions can tie people to a particular way of performing a task despite that in principle a more efficient way could be learned and used. Since task shielding can lead to persistence of inefficient variants of task performance, it is relevant to test whether individuals with attention deficit/hyperactivity disorder (ADHD) - characterized by less task shielding - are more likely and quicker to escape a suboptimal instructed variant of performing a task. The paradigm used in this online study builds on the observation that in many environments different covarying features could be used to determine the appropriate response. For instance, 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, more efficient in case of reduced color sight). Similarly, we instructed participants to respond to the color of a stimulus without mentioning that color covaried with the position of the stimulus. In order to assess whether with practice participants would use the non-instructed feature position to an increasing extent, we compared reaction times and error rates for standard trials to trials in which color was either ambiguous or did not match the usual covariation. Results showed that the covariation learning task can be administered online to adult participants with and without ADHD. Performance differences suggested that with practice ADHD participants (n = 43 out of a total N = 245) might increase attention to non-instructed stimulus features. Yet, they used the non-instructed covarying stimulus feature to a similar extent as other participants. Together the results suggest that participants with ADHD do not lag behind in abandoning instructed task processing in favor of a learned alternative strategy.

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.

Goal-Based Binding of Irrelevant Stimulus Features for Action Slips

Abstract. Binding between representations of stimuli and actions and later retrieval of these compounds provide efficient shortcuts in action control. Recent observations indicate that these mechanisms are not only effective when action episodes go as planned, but they also seem to be at play when actions go awry. Moreover, the human cognitive system even corrects traces of error commission on the fly because it binds the intended but not actually executed response to concurrent task-relevant stimuli, thus enabling retrieval of a correct, but not actually executed response when encountering the stimulus again. However, a plausible alternative interpretation of this finding is that error commission triggers selective strengthening of the instructed stimulus–response mapping instead, thus promoting its efficient application in the future. The experiment presented here makes an unequivocal case for episodic binding and retrieval in erroneous action episodes by showing binding between task-irrelevant stimuli and correct responses.

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.

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.

Autism - A Comprehensive Array of Prominent Signs and Symptoms

BACKGROUND

Autism Spectrum Disorder (ASD) is a multifaceted neurodevelopmental condition characterized by multiple psychological and physiological impairments in young children. According to the recent reports, 1 out of every 58 newly-born children is suffering from autism. The aetiology of the disorder is complex and poorly understood, hindering the adaptation of targeted and effective therapies. There are no well- established diagnostic biomarkers for autism. Hence the analysis of symptoms by the pediatricians plays a critical role in the early intervention.

METHODS

In the present report, we have emphasized 24 behavioral, psychological and clinical symptoms of autism.

RESULTS

Impaired social interaction, restrictive and narrow interests, anxiety, depression; aggressive, repetitive, rigid and self-injurious behavior, lack of consistency, short attention span, fear, shyness and phobias, hypersensitivity and rapid mood alterations, high level of food and toy selectivity; inability to establish friendships or follow the instructions; fascination by round spinning objects and eating non-food materials are common psychological characteristics of autism. Speech or hearing impairments, poor cognitive function, gastrointestinal problems, weak immunity, disturbed sleep and circadian rhythms, weak motor neuromuscular interaction, lower level of serotonin and neurotransmitters, headache and body pain are common physiological symptoms.

CONCLUSION

A variable qualitative and quantitative impact of this wide range of symptoms is perceived in each autistic individual, making him/her distinct, incomparable and exceptional. Selection and application of highly personalized medical and psychological therapies are therefore recommended for the management and treatment of autism.

Proactive and reactive metacontrol in task switching

While cognitive control enables the selection of goal-relevant responses, metacontrol enables the selection of context-appropriate control operations. In task switching, metacontrol modulates task-switching efficiency by retrieving the associations between a contextual cue and a particular cognitive control demand. While the automatic retrieval of cognitive control is appealing due to its time and energy efficiency, the effects of different contextual cues have been shown in separate studies and appear to have different characteristics. Here, we devised a single task-switching paradigm to test whether we can observe both list-wide and item-specific metacontrol within subjects. In two experiments, we demonstrated reduced switch costs in lists associated with a high probability of switching as compared with lists with a low probability of switching (i.e., a list-wide switch probability [LWSP] effect). Similarly, we observed an analogous item-specific switch probability (ISSP) effect such that items associated with a high probability of switching incurred smaller switch costs as compared with items associated with a low probability of switching. We also confirmed that both list-wide and item-specific switch probability effects were not dependent on lower-level stimulus-response associations. However, the LWSP and the ISSP effects were uncorrelated, suggesting a lack of dependence. Together, these findings suggest that there are two distinct modes of metacontrol that are deployed in a context-sensitive manner in order to adapt to specific cognitive demands.

Frontoparietal action-oriented codes support novel instruction implementation

A key aspect of human cognitive flexibility concerns the ability to convert complex symbolic instructions into novel behaviors. Previous research proposes that this transformation is supported by two neurocognitive states: an initial declarative maintenance of task knowledge, and an implementation state necessary for optimal task execution. Furthermore, current models predict a crucial role of frontal and parietal brain regions in this process. However, whether declarative and procedural signals independently contribute to implementation remains unknown. We report the results of an fMRI experiment in which participants executed novel instructed stimulus-response associations. We then used a pattern-tracking procedure to quantify the contribution of format-unique signals during instruction implementation. This revealed independent procedural and declarative representations of novel S-Rs in frontoparietal areas, prior to execution. Critically, the degree of procedural activation predicted subsequent behavioral performance. Altogether, our results suggest an important contribution of frontoparietal regions to the neural architecture that regulates cognitive flexibility.

Large EEG amplitude effects are highly similar across Necker cube, smiley, and abstract stimuli

The information available through our senses is noisy, incomplete, and ambiguous. Our perceptual systems have to resolve this ambiguity to construct stable and reliable percepts. Previous EEG studies found large amplitude differences in two event-related potential (ERP) components 200 and 400 ms after stimulus onset when comparing ambiguous with disambiguated visual information ("ERP Ambiguity Effects"). These effects so far generalized across classical ambiguous figures from different visual categories at lower (geometry, motion) and intermediate (Gestalt perception) levels. The present study aimed to examine whether these ERP Effects are restricted to ambiguous figures or whether they also occur for different degrees of visibility. Smiley faces with low and high visibility of emotional expressions, as well as abstract figures with low and high visibility of a target curvature were presented. We thus compared ambiguity effects in geometric cube stimuli with visibility in emotional faces, and with visibility in abstract figures. ERP Effects were replicated for the geometric stimuli and very similar ERP Effects were found for stimuli with emotional face expressions but also for abstract figures. Conclusively, the ERP amplitude effects generalize across fundamentally different stimulus categories and show highly similar effects for different degrees of stimulus ambiguity and stimulus visibility. We postulate the existence of a high-level/meta-perceptual evaluation instance, beyond sensory details, that estimates the certainty of a perceptual decision. The ERP Effects may reflect differences in evaluation results.

Attention for future reward

When stimuli are consistently paired with reward, attention toward these stimuli becomes biased (e.g., Abrahamse, Braem, Notebaert & Verguts, et al., Psychological Bulletin 142:693-728, 2016, https://doi.org/10.1037/bul0000047). An important premise is that participants need to repeatedly experience stimulus-reward pairings to obtain these effects (e.g., Awh, Belopolsky & Theeuwes, Trends in Cognitive Sciences 16:437-443, 2012, https://doi.org/10.1016/j.tics.2012.06.010). This idea is based on associative learning theories (e.g., Pearce & Bouton, Annual Review of Psychology 52:111-139, 2001) that suggest that exposure to stimulus-reward pairings leads to the formation of stimulus-reward associations, and a transfer of salience of the reward to the neutral stimulus. However, novel learning theories (e.g., De Houwer, Learning and Motivation 53:7-23, 2009, https://doi.org/10.1016/j.lmot.2015.11.001) suggest such effects are not necessarily the result of associative learning, but can be caused by complex knowledge and expectancies as well. In the current experiment, we first instructed participants that a correct response to one centrally presented stimulus would be followed by a high reward, whereas a correct response to another centrally presented stimulus would be paired with a low reward. Before participants executed this task, they performed a visual probe task in which these stimuli were presented as distractors. We found that attention was drawn automatically toward high-reward stimuli relative to low-reward stimuli. This implies that complex inferences and expectancies can cause automatic attentional bias, challenging associative learning models of attentional control (Abrahamse et al., 2016; Awh et al., 2012).

Aftereffects and deactivation of completed prospective memory intentions: A systematic review

Prospective memory, the ability to perform an intended action in the future, is an essential aspect of goal-directed behavior. Intentions influence our behavior and shape the way we process and interact with our environment. One important question for research on prospective memory and goal-directed behavior is whether this influence stops after the intention has been completed successfully. Are intention representations deactivated from memory after their completion, and if so, how? Here, we systematically review 20 years of research on intention deactivation and so-called aftereffects of completed intentions across different research fields to offer an integrative perspective on this topic. We first introduce the currently dominant accounts of aftereffects (inhibition vs. retrieval) and illustrate the paradigms, findings, and interpretations that these accounts developed from. We then review the evidence for each account based on the extant research in these paradigms. While early studies proposed a rapid deactivation or even inhibition of completed intentions, more recent studies mostly suggested that intentions continue to be retrieved even after completion and interfere with subsequent performance. Although these accounts of aftereffects seem mutually exclusive, we will show that they might be two sides of the same coin. That is, intention deactivation and the occurrence of aftereffects are modulated by a multitude of factors that either foster a rapid deactivation or lead to continued retrieval of completed intentions. Lastly, we outline future directions and novel experimental procedures for research on mechanisms and modulators of intention deactivation and discuss practical implications of our findings. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

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 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.

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.

Deterministic response strategies in a trial-and-error learning task

Trial-and-error learning is a universal strategy for establishing which actions are beneficial or harmful in new environments. However, learning stimulus-response associations solely via trial-and-error is often suboptimal, as in many settings dependencies among stimuli and responses can be exploited to increase learning efficiency. Previous studies have shown that in settings featuring such dependencies, humans typically engage high-level cognitive processes and employ advanced learning strategies to improve their learning efficiency. Here we analyze in detail the initial learning phase of a sample of human subjects (N = 85) performing a trial-and-error learning task with deterministic feedback and hidden stimulus-response dependencies. Using computational modeling, we find that the standard Q-learning model cannot sufficiently explain human learning strategies in this setting. Instead, newly introduced deterministic response models, which are theoretically optimal and transform stimulus sequences unambiguously into response sequences, provide the best explanation for 50.6% of the subjects. Most of the remaining subjects either show a tendency towards generic optimal learning (21.2%) or at least partially exploit stimulus-response dependencies (22.3%), while a few subjects (5.9%) show no clear preference for any of the employed models. After the initial learning phase, asymptotic learning performance during the subsequent practice phase is best explained by the standard Q-learning model. Our results show that human learning strategies in the presented trial-and-error learning task go beyond merely associating stimuli and responses via incremental reinforcement. Specifically during initial learning, high-level cognitive processes support sophisticated learning strategies that increase learning efficiency while keeping memory demands and computational efforts bounded. The good asymptotic fit of the Q-learning model indicates that these cognitive processes are successively replaced by the formation of stimulus-response associations over the course of learning.

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.

Learning in the absence of overt practice: a novel (previously unseen) stimulus can trigger retrieval of an unpracticed response

Skilled performance is traditionally thought to develop via overt practice. Recent research has demonstrated that merely instructed stimulus-response (S-R) bindings can influence later performance and readily transfer across response modalities. In the present study, we extended this to include instructed category-response (C-R) associations. That is, we investigated whether merely instructed C-R bindings can trigger an unpracticed response (in a different modality) on perception of a novel (previously unseen) stimulus. In a learning-test design, participants had to classify stimuli by comparing them to perceptual category templates (Experiment 1) or semantic category descriptions (Experiment 2) presented prior to each block. During learning blocks, participants had to respond manually, respond vocally, or listen passively to the correct response being spoken. A manual response was always required at test. In test blocks, the categories could either be novel or repeated from the learning block, whereas half of the stimuli were always novel and half were always repeated from the learning block. Because stimulus and category repetitions were manipulated orthogonally, it was possible to directly compare the relative contribution of S-R and C-R associations to performance. In Experiment 1, test performance was enhanced by repeating the C-R bindings independently of the stimulus. In Experiment 2, there was also evidence of an S-R repetition benefit independent of the classification. Critically, instructed associations formed in one response modality were robust to changes in the required response, even when no overt response was required during training, indicating the need to update the traditional view of associative learning.

Frequency of prospective use modulates instructed task-set interference

Recent studies have demonstrated that keeping an instructed task set in working memory (WM) for prospective use can interfere with behavior on an intervening task that employs shared stimuli-the prospective task-set-interference effect. One open question is whether people have strategic control over prospective task-set interference based on their expectations of whether task instructions will have to be implemented or recalled. To answer this question, we conducted two experiments that varied the likelihood with which a set of prospective task instructions would have to be implemented or recalled. Based on the hypothesis that participants are able to strategically modulate the manner in which a prospective task set is encoded in WM, we predicted that, as the frequency of implementing task instructions increased, so too would the magnitude of the prospective task-set-interference effect. We found that task instructions held in WM caused significant task-set interference, even in mostly recall conditions, but-crucially-that this interference effect scaled positively with the likelihood of having to implement the prospective set. These data suggest that task instructions are obligatorily encoded as a procedural task set, but that the degree to which this set impinges on ongoing stimulus processing is subject to some strategic control, possibly via modulation of the associations between declarative and procedural WM contents. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

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.

Learning and transfer of working memory gating policies

knowledge about the tasks we encounter enables us to rapidly and flexibly adapt to novel task contexts. Previous research has focused primarily on abstract rules that leverage shared structure in stimulus-response (S-R) mappings as the basis of such task knowledge. Here we provide evidence that working memory (WM) gating policies - a type of control policy required for internal control of WM during a task - constitute a form of abstract task knowledge that can be transferred across contexts. In two experiments, we report specific evidence for the transfer of selective WM gating policies across changes of task context. We show that this transfer is not tied to shared structure in S-R mappings, but instead in the dynamic structure of the task. Collectively, our results highlight the importance of WM gating policies in particular, and control policies in general, as a key component of the task knowledge that supports flexible behavior and task generalization.

You Are Right!

In the social Simon task, two participants perform a spatial compatibility task together, each of them responding to only one stimulus (e.g., one participant reacts to red, the other to green stimuli). Participants show joint spatial compatibility effects (SCEs), that is, they respond faster when their go-stimulus appears on their half of the screen. Effects are absent when the same go/no-go task is performed without a coactor. Joint SCEs were originally explained in terms of shared task representations, but recent research suggests that effects result from spatial response coding: in joint go/no-go tasks, participants perceive themselves as the right/left participant operating a right/left response key. While previous research showed that the spatial alignment of keys and seats influences the effect, the present research demonstrates that merely instructing participants to be the right/left participant operating a right/left response key instead of labeling participants and keys with arbitrary numbers substantially increases joint SCEs.

Cognitive control over prospective task-set interference

Recent studies have demonstrated that maintaining task-sets in working memory (WM) for prospective implementation can interfere with performance on an intervening task when the same stimulus requires incompatible responses in the ongoing versus the prospective task. This prospective task-set interference effect has previously been conceptualized as an obligatory process, resulting from instruction-based reflexivity (IBR). However, the extent to which strategic control can be exerted over interference in ongoing behavior from prospective task-sets held in WM has heretofore not been tested directly. To probe for strategic control over this effect, the authors conducted 3 experiments using a common inducer-diagnostic task design that manipulated the proportion compatibility of trials in the ongoing task. They hypothesized that if prospective task-set interference were malleable by control, participants would suppress the influence of the prospective set on ongoing processing when incompatible trials are frequent. Consistent with this prediction, the results show that prospective task-set interference is subject to modulation by strategic control such that the magnitude of interference is reduced, eliminated, or reversed in the presence of frequent incompatible trials. Thus, the influence on ongoing behavior of a prospective task-set held in WM is not obligatory, but subject to strategic control. (PsycINFO Database Record

Powerful Instructions: Automaticity Without Practice

Automaticity is widely assumed to reflect hardwired tendencies or the outcome of prior practice. Recent research on automatic effects of instruction (AEIs), however, indicates that newly instructed tasks can become immediately automatic without ever having been practiced. This research shows that the representations underlying AEIs need not always be directly linked to an overt response but must be highly accessible for future use and involve bidirectional links between stimuli and responses. AEIs were also found to decrease with increasing intellectual abilities among young adults and from childhood to young adulthood, possibly because of improved abstract cognitive control. We argue that AEIs are based on the unintentional retrieval of episodic memories that encode instructions.

The task novelty paradox: Flexible control of inflexible neural pathways during rapid instructed task learning

Rapid instructed task learning (RITL) is one of the most remarkable human abilities, when considered from both computational and evolutionary perspectives. A key feature of RITL is that it enables new goals to be immediately pursued (and shared) following formation of task representations. Although RITL is a form of cognitive control that engenders immense flexibility, it also seems to produce inflexible activation of action plans in inappropriate contexts. We argue that this "prepared reflex" effect arises because RITL is implemented in the brain via a "flexible hub" mechanism, in which top-down influences from the frontoparietal control network reroute pathways among procedure-implementing brain areas (e.g., perceptual and motor areas). Specifically, we suggest that RITL-based proactive control - the preparatory biasing of task-relevant functional network routes - results in inflexible associative processing, demanding compensation in the form of increased reactive (in-the-moment) control. Thus, RITL produces a computational trade-off, in which the top-down influences of flexible hubs increase overall cognitive flexibility, but at the cost of temporally localized inflexibility (the prepared reflex effect).

A Contextual Behavior Science Framework for Understanding How Behavioral Flexibility Relates to Anxiety

There is a growing literature focusing on the emerging idea that behavioral flexibility, rather than particular emotion regulation strategies per se, provides greater promise in predicting and influencing anxiety-related psychopathology. Yet this line of research and theoretical analysis appear to be plagued by its own challenges. For example, middle-level constructs, such as behavioral flexibility, are difficult to define, difficult to measure, and difficult to interpret in relation to clinical interventions. A key point that some researchers have made is that previous studies examining flexible use of emotion regulation strategies (or, more broadly, coping) have failed due to a lack of focus on context. That is, examining strategies in isolation of the context in which they are used provides limited information on the suitability, rigid adherence, or effectiveness of a given strategy in that situation. Several of these researchers have proposed the development of new models to define and measure various types of behavioral flexibility. We would like to suggest that an explanation of the phenomenon already exists and that we can go back to our behavioral roots to understand this phenomenon rather than focusing on defining and capturing a new process. Indeed, thorough contextual behavioral analyses already yield a useful account of what has been observed. We will articulate a model explaining behavioral flexibility using a functional, contextual framework, with anxiety-related disorders as an example.

Neural Coding for Instruction-Based Task Sets in Human Frontoparietal and Visual Cortex

Task preparation has traditionally been thought to rely upon persistent representations of instructions that permit their execution after delays. Accumulating evidence suggests, however, that accurate retention of task knowledge can be insufficient for successful performance. Here, we hypothesized that instructed facts would be organized into a task set; a temporary coding scheme that proactively tunes sensorimotor pathways according to instructions to enable highly efficient "reflex-like" performance. We devised a paradigm requiring either implementation or memorization of novel stimulus-response mapping instructions, and used multivoxel pattern analysis of neuroimaging data to compare neural coding of instructions during the pretarget phase. Although participants could retain instructions under both demands, we observed striking differences in their representation. To-be-memorized instructions could only be decoded from mid-occipital and posterior parietal cortices, consistent with previous work on visual short-term memory storage. In contrast, to-be-implemented instructions could also be decoded from frontoparietal "multiple-demand" regions, and dedicated visual areas, implicated in processing instructed stimuli. Neural specificity in the latter moreover correlated with performance speed only when instructions were prepared, likely reflecting the preconfiguration of instructed decision circuits. Together, these data illuminate how the brain proactively optimizes performance, and help dissociate neural mechanisms supporting task control and short-term memory storage.

Evidence for instructions-based updating of task-set representations: the informed fadeout effect

The cognitive system can be updated rapidly and efficiently to maximize performance in cognitive tasks. This paper used a task-switching task to explore updating at the level of the plausible task-sets held for future performance. Previous research suggested a "fadeout effect", performance improvement when moving from task-switching context to single-task context, yet this effect could reflect passive learning rather than intentional control. In a novel "informed fadeout paradigm", one of two tasks was canceled for a certain number of trials and participants were informed or uninformed regarding task cancelation. The "informed fadeout effect" indicates better performance in the informed than uninformed fadeout after one informed trial had been executed. However, the results regarding the first trial were inconclusive. Possible underlying mechanisms are discussed.

Automatic Retrieval of Newly Instructed Cue-Task Associations Seen in Task-Conflict Effects in the First Trial after Cue-Task Instructions

Abstract. Novel stimulus-response associations are retrieved automatically even without prior practice. Is this true for novel cue-task associations? The experiment involved miniblocks comprising three phases and task switching. In the INSTRUCTION phase, two new stimuli (or familiar cues) were arbitrarily assigned as cues for up-down/right-left tasks performed on placeholder locations. In the UNIVALENT phase, there was no task cue since placeholder’s location afforded one task but the placeholders were the stimuli that we assigned as task cues for the following BIVALENT phase (involving target locations affording both tasks). Thus, participants held the novel cue-task associations in memory while executing the UNIVALENT phase. Results show poorer performance in the first univalent trial when the placeholder was associated with the opposite task (incompatible) than when it was compatible, an effect that was numerically larger with newly instructed cues than with familiar cues. These results indicate automatic retrieval of newly instructed cue-task associations.

Integration and segregation of large-scale brain networks during short-term task automatization

The human brain is organized into large-scale functional networks that can flexibly reconfigure their connectivity patterns, supporting both rapid adaptive control and long-term learning processes. However, it has remained unclear how short-term network dynamics support the rapid transformation of instructions into fluent behaviour. Comparing fMRI data of a learning sample (N=70) with a control sample (N=67), we find that increasingly efficient task processing during short-term practice is associated with a reorganization of large-scale network interactions. Practice-related efficiency gains are facilitated by enhanced coupling between the cingulo-opercular network and the dorsal attention network. Simultaneously, short-term task automatization is accompanied by decreasing activation of the fronto-parietal network, indicating a release of high-level cognitive control, and a segregation of the default mode network from task-related networks. These findings suggest that short-term task automatization is enabled by the brain's ability to rapidly reconfigure its large-scale network organization involving complementary integration and segregation processes.

Humans can quickly learn to efficiently execute tasks yet how the brain activity is dynamically reconfigured during this process remains unknown. Here the authors demonstrate that large-scale functional brain networks are reorganized flexibly to support rapid task automation.