Disentangling the contribution of individual and social learning processes in human advice-taking behavior.

The study of social learning examines how individuals learn from others by means of observation, imitation, or compliance with advice. However, it still remains largely unknown whether social learning processes have a distinct contribution to behavior, independent from non-social trial-and-error learning that often occurs simultaneously. 153 participants completed a reinforcement learning task, where they were asked to make choices to gain rewards. Advice from an artificial teacher was presented in 60% of the trials, allowing us to compare choice behavior with and without advice. Results showed a strong and reliable tendency to follow advice (test-retest reliability ~0.73). Computational modeling suggested a unique contribution of three distinct learning strategies: (a) individual learning (i.e., learning the value of actions, independent of advice), (b) informed advice-taking (i.e., learning the value of following advice), and (c) non-informed advice-taking (i.e., a constant bias to follow advice regardless of outcome history). Comparing artificial and empirical data provided specific behavioral regression signatures to both informed and non-informed advice taking processes. We discuss the theoretical implications of integrating internal and external information during the learning process.

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.

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.

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.

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.

Formation of abstract task representations: Exploring dosage and mechanisms of working memory training effects.

Working memory is strongly involved in human reasoning, abstract thinking and decision making. Past studies have shown that working memory training generalizes to untrained working memory tasks with similar structure (near-transfer effect). Here, we focused on two questions: First, we ask how much training might be required in order to find a reliable near-transfer effect? Second, we ask which choice- mechanism might underlie training benefits? Participants were allocated to one of three groups: working-memory training (combined set-shifting and N-back task), active-control (visual search) and no-contact control. During pre/post testing, all participants completed tests tapping procedural and declarative working memory as well as reasoning. We found improved performance only in the procedural working-memory transfer tasks, a transfer task that shared a similar structure to that of the training task. Intermediate testing throughout the training period suggest that this effect emerged as soon as after 2 training sessions. We applied evidence accumulation modeling to investigate the choice process responsible for this near-transfer effect and found that trained participants, compared with active-controls had quicker retrieval of the action rules, and more efficient classification of the target. We conclude that participants were able to form abstract representations of the task procedure (i.e., stimulus-response rules) that was then ~applied to novel stimuli and responses.

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.

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.

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.

The role of working memory in rapid instructed task learning and intention-based reflexivity: An individual differences examination.

The ability to efficiently follow novel task instructions (Rapid Instructed Task Learning, RITL) appears late in evolution, is required for successful collaborative teamwork, and appears to involve maintaining instructions in working-memory (WM). RITL is indexed by the efficiency in which the instructions are performed (RITL success) and by whether the instructions operate automatically (intention-based reflexivity). Based on prior normative work employing WM-load manipulations, we predicted that individual differences in WM would positively correlate with these RITL indices. Participants (N=175) performed the NEXT paradigm, which is used to assess RITL, and tests of choice reaction time, intelligence, and WM. Confirmatory factor analyses showed that, contrary to our predictions, successful performance in WM tasks did not predict RITL performance. Tests tapping general-fluid intelligence and reaction time positively correlated with RITL success. However, contrary to our predictions, RITL success positively correlated with little intention-based reflexivity. We suggest that for a RITL paradigm to produce intention-based reflexivity, its WM demand must be low, and, thus, performance does not reflect individual differences in WM.

Reflexive activation of newly instructed stimulus-response rules: evidence from lateralized readiness potentials in no-go trials.

Previous behavioral and electrophysiological evidence has suggested that the instructions for a new choice task are processed even when they are not currently required, indicating intention-based reflexivity. Yet these demonstrations were found in experiments in which participants were set to execute a response (go). In the present experiment, we asked whether intention-based reflexivity would also be observed under unfavorable conditions in which participants were set not to respond (no-go). In each miniblock of our paradigm, participants received instructions for a task in which two new stimuli were mapped to right/left keys. Immediately after the instructions, a no-go phase began, which was immediately followed by a go phase. We found a significant stimulus-locked lateralized readiness potential in the first no-go trial, indicating reflexive operation of the new instructions. These results show that representing instructions in working memory provides sufficient conditions for stimuli to launch task processing, proceeding all the way until motor response-specific brain activation, which takes place even under unfavorable, no-go conditions.

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

Humans are characterized by an especially highly developed ability to use instructions to prepare toward upcoming events; yet, it is unclear just how powerful instructions can be. Although prior work provides evidence that instructions can be sufficiently powerful to proactively program working memory to execute stimulus-response (S-R) translations, in a reflexlike fashion (intention-based reflexivity [IBR]), the results to date have been equivocal. To overcome this shortcoming, we developed, and tested in 4 studies, a novel paradigm (the NEXT paradigm) that isolates IBR effects even prior to first task execution. In each miniblock, participants received S-R mapping instructions for a new task. Prior to implementing this mapping, responses were required to advance through screens during a preparatory (NEXT) phase. When the NEXT response was incompatible with the instructed S-R mapping, interference (IBR effect) was observed. This NEXT compatibility effect and performance in the implementation (GO) trials barely changed when prior practice of a few trials was provided. Finally, a manipulation that encouraged preparation resulted in relatively durable NEXT compatibility effects (indicating durable preparatory efforts) coupled with improved GO performance (indicating the success of these efforts). Together, these findings establish IBR as a marker of instructed proactive control.

Selective influence of working memory load on exceptionally slow reaction times.

The rate of exceptionally slow reaction times (RTs), described by the long tail of the RT distribution, was found to be amplified in a variety of special populations with cognitive deficits (e.g., early-stage Alzheimer's disease, attention-deficit/hyperactivity disorder, low intelligence, elderly). Previous individual differences studies found high correlations between working memory (WM) and parameters that characterize the magnitude of the long-RT tail. However, the causal direction remains unknown. In 3 choice-reaction task experiments, we examined this relationship by directly manipulating WM availability. In Experiment 1, the stimulus-response rules were either arbitrary (WM demanding) or nonarbitrary. In Experiment 2, the arbitrary rules were either novel (demanding) or practiced. In Experiment 3, WM was loaded with either declarative (stimulus-stimulus) or procedural (stimulus-response) arbitrary rules. Using an ex-Gaussian model fitting, we found across all experiments that WM demands uniquely influenced the τ parameter, mostly responsible for the long-RT distribution tail. Evidence accumulation modeling of the choice process indicated that WM load had little influence on the decision process itself and primarily affected the duration of an exponentially distributed nondecision component, assumed to reflect the process of rule retrieval. Theoretical interpretations and implications are discussed.