Working memory load but not multitasking eliminates the prepared reflex: further evidence from the adapted flanker paradigm

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

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

To err is human- to understand error-processing is divine: Contributions of working memory and anxiety to error-related brain and pupil responses

Both anxiety and working memory capacity appear to predict increased (more negative) error-related negativity (ERN) amplitudes, despite being inversely related to one another. Until the interactive effects of these variables on the ERN are clarified, there may be challenges posed to our ability to use the ERN as an endophenotype for anxiety, as some have suggested. The compensatory error monitoring hypothesis suggests that high trait-anxiety individuals have larger ERN amplitudes because they must employ extra, compensatory efforts to override the working memory demands of their anxiety. Yet, to our knowledge, no ERN study has employed direct manipulation of working memory demands in conjunction with direct manipulations of induced (state) anxiety. Furthermore, little is known about how these manipulations affect other measures of error processing, such as the error-related pupil dilation response and post-error behavioral adjustments. Therefore, we manipulate working memory load and anxiety in a 2 × 2 within-subjects design to examine the interactive effects of working memory load and anxiety on ERN amplitude, error-related pupil dilation response amplitude, and post-error behavior. There were no effects of our manipulations on ERN amplitude, suggesting a strong interpretation of compensatory error-processing theory. However, our worry manipulation affected post-error behavior, such that worry caused a reduction in post-error accuracy. Additionally, our working memory manipulation affected error-related PDR magnitude and the amplitude of the error-related positivity (Pe), such that increased working memory load decreased the amplitude of these responses. Implications of these results within the context of the compensatory error processing framework are discussed.

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.

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.

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.

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.

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.

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

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

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.

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.

Multiple priming instances increase the impact of practice-based but not verbal code-based stimulus-response associations

Stimulus-response (S-R) associations, the basis of learning and behavioral automaticity, are formed by the (repeated) co-occurrence of stimuli and responses and render stimuli able to automatically trigger associated responses. The strength and behavioral impact of these S-R associations increases with the number of priming instances (i.e., practice). Here we investigated whether multiple priming instances of a special form of instruction, verbal coding, also lead to the formation of stronger S-R associations in comparison to a single instance of priming. Participants either actively classified stimuli or passively attended to verbal codes denoting responses once or four times before S-R associations were probed. We found that whereas S-R associations formed on the basis of active task execution (i.e., practice) were strengthened by multiple priming instances, S-R associations formed on the basis of verbal codes (i.e., instruction) did not benefit from additional priming instances. These findings indicate difference in the mechanisms underlying the encoding and/or retrieval of previously executed and verbally coded S-R associations.

On the efficiency of instruction-based rule encoding

Instructions have long been considered a highly efficient route to knowledge acquisition especially compared to trial-and-error learning. We aimed at substantiating this claim by identifying boundary conditions for such an efficiency gain, including the influence of active learning intention, repeated instructions, and working memory load and span. Our experimental design allowed us to not only assess how well the instructed stimulus-response (S-R) rules were implemented later on, but also to directly measure prior instruction encoding processes. This revealed that instruction encoding was boosted by an active learning intention which in turn entailed better subsequent rule implementation. As should be expected, instruction-based learning took fewer trials than trial-and-error learning to reach a similar performance level. But more importantly, even when performance was measured relative to the identical number of preceding correct implementation trials, this efficiency gain persisted both in accuracy and in speed. This suggests that the naturally greater number of failed attempts in the initial phase of trial-and-error learning also negatively impacted learning in subsequent trials due to the persistence of erroneous memory traces established beforehand. A single instruction trial was sufficient to establish the advantage over trial-and-error learning but repeated instructions were better. Strategic factors and inter-individual differences in WM span - the latter exclusively affecting trial-and-error learning presumably due to the considerably more demanding working memory operations - could reduce or even abolish this advantage, but only in error rates. The same was not true for response time gains suggesting generally more efficient task automatization in instruction-based learning.

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).

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.

Learning through instructions vs. learning through practice: flanker congruency effects from instructed and applied S-R mappings

We compared flanker congruency effects (FCE) for flanker stimuli that were part of merely instructed S-R mappings or S-R mappings that had already been practiced. Four new S-R mappings were instructed before each block of trials. In applied flanker blocks, each instructed stimulus could appear as target and as flanker. In merely instructed flanker blocks, two stimuli only served as targets, whereas the other two exclusively appeared as flankers. Significant FCEs were observed for both flanker conditions even though the instruction-based FCE was (a) smaller than the FCE from applied mappings and (b) decreased with task practice. These results suggest that instructions alone can induce S-R associations that lead to automatic response activation when instructed stimuli appear as flankers. Execution of instructed rules seems to strengthen the instructed associations, leading to increased response conflict.

Congruency effects on the basis of instructed response-effect contingencies

Previous research indicated that stimulus-response congruency effects can be obtained in one task (the diagnostic task) on the basis of the instructed stimulus-response mappings of another task (the inducer task) and this without having executed the instructions of the inducer task once. A common interpretation of such finding is that instructed stimulus-response mappings are implemented into functional associations, which automatically trigger responses when being irrelevant and this without any practice. The present study investigated whether instruction-based congruency effects are also observed for a different type of instructions than instructed S-R mappings, namely instructed response-effect contingencies. In three experiments, instruction-based congruency effects were observed in the diagnostic task when the instructions of the inducer task specified response-effect contingencies. On the one hand, our results indicate that instruction-based congruency effects are not restricted to instructed S-R mappings. On the other hand, our results suggest that the representations that mediate these effects do not specify the nature of the relation between response and effect even though this relation was explicitly specified by the instructions.

Cue type affects preparatory influences on task inhibition

The present study investigates the influence of preparation on inhibitory effects in cued task switching. In three experiments, we assessed n - 2 repetition costs as marker of inhibition of the just executed and now irrelevant task by comparing performance in task sequences such as ABA (i.e., n - 2 repetitions, with A, B and C standing for different tasks) to task sequences such as CBA (i.e., n - 2 switches). Specifically, we varied the cue-target interval (CTI) to examine cue-based preparation effects. In addition, we manipulated cue type (i.e., abstract, verbal, and direct cues) across the three experiments. We obtained significant reductions of n - 2 repetition costs with prolonged CTI when using abstract cues (i.e., coloured frames) and task names (i.e., digit), but not when using the task-specific stimulus-response mapping as cue for the upcoming task. These data suggest that cue-based preparation is not a uniform process but depends on the information provided by the cue.

Instruction-based response activation depends on task preparation

An increasing number of studies have demonstrated that a response in one task can be activated automatically on the basis merely of instructed stimulus-response (S-R) mappings belonging to another task. Such instruction-based response activations are considered to be evidence for the formation of S-R associations on the basis of the S-R mappings for an upcoming, but not yet executed, task. A crucial but somewhat neglected assumption is that instructed S-R associations are formed only under conditions that impose a sufficient degree of task preparation. Accordingly, in the present study we investigated the relation between task preparation and the instruction-based task-rule congruency effect, which is an index of response activation on the basis of instructions. The results from two experiments demonstrated that merely instructed S-R mappings of a particular task only elicit instruction-based response activations when that task is prepared for to a sufficient degree. Implications are discussed for the representation of instructed S-R mappings in working memory.

Analogous mechanisms of selection and updating in declarative and procedural working memory: experiments and a computational model

The article investigates the mechanisms of selecting and updating representations in declarative and procedural working memory (WM). Declarative WM holds the objects of thought available, whereas procedural WM holds representations of what to do with these objects. Both systems consist of three embedded components: activated long-term memory, a central capacity-limited component for building structures through temporary bindings, and a single-element focus of attention. Five experiments test the hypothesis of analogous mechanisms in declarative and procedural WM, investigating repetition effects across trials for individual representations (objects and responses) and for sets (memory sets and task sets), as well as set-congruency effects. Evidence for analogous processes was obtained from three phenomena: (1) Costs of task switching and of list switching are reduced with longer preparation interval. (2) The effects of task congruency and of list congruency are undiminished with longer preparation interval. (3) Response repetition interacts with task repetition in procedural WM; here we show an analogous interaction of list repetition with item repetition in declarative WM. All three patterns were reproduced by a connectionist model implementing the assumed selection and updating mechanisms. The model consists of two modules, an item-selection module selecting individual items from a memory set, or responses from a task set, and a set-selection module for selecting memory sets or task sets. The model codes the matrix of binding weights in the item-selection module as a pattern of activation in the set-selection module, thereby providing a mechanism for building chunks in LTM, and for unpacking them as structures into working memory.

Frontostriatal mechanisms in instruction-based learning as a hallmark of flexible goal-directed behavior

The present review intends to provide a neuroscientific perspective on the flexible (here: almost instantaneous) adoption of novel goal-directed behaviors. The overarching goal is to sketch the emerging framework for examining instruction-based learning and how this can be related to more established research approaches to instrumental learning and goal-directed action. We particularly focus on the contribution of frontal and striatal brain regions drawing on studies in both, animals and humans, but with an emphasize put on human neuroimaging studies. In section one, we review and integrate a selection of previous studies that are suited to generally delineate the neural underpinnings of goal-directed action as opposed to more stimulus-based (i.e., habitual) action. Building on that the second section focuses more directly on the flexibility to rapidly implement novel behavioral rules as a hallmark of goal-directed action with a special emphasis on instructed rules. In essence, the current neuroscientific evidence suggests that the prefrontal cortex and associative striatum are able to selectively and transiently code the currently relevant relationship between stimuli, actions, and the effects of these actions in both, instruction-based learning as well as in trial-and-error learning. The premotor cortex in turn seems to form more durable associations between stimuli and actions or stimuli, actions and effects (but not incentive values) thus representing the available action possibilities. Together, the central message of the present review is that instruction-based learning should be understood as a prime example of goal-directed action, necessitating a closer interlacing with basic mechanisms of goal-directed action on a more general level.

When planning results in loss of control: intention-based reflexivity and working-memory

In this review, the authors discuss the seemingly paradoxical loss of control associated with states of high readiness to execute a plan, termed "intention-based reflexivity." The review suggests that the neuro-cognitive systems involved in the preparation of novel plans are different than those involved in preparation of practiced plans (i.e., those that have been executed beforehand). When the plans are practiced, intention-based reflexivity depends on the prior availability of response codes in long-term memory (LTM). When the plans are novel, reflexivity is observed when the plan is pending and the goal has not yet been achieved. Intention-based reflexivity also depends on the availability of working-memory (WM) limited resources and the motivation to prepare. Reflexivity is probably related to the fact that, unlike reactive control (once a plan is prepared), proactive control tends to be relatively rigid.