Implicit knowledge and motor skill: What people who know how to catch don’t know

Unconscious knowledge of rewards guides instrumental behaviors via conscious judgments

The demonstration that unconscious learning supports instrumental behaviors (i.e., choosing the stimuli that lead to rewards) is central for the tenet that unconscious cognition sustains human adaptation. Recent studies, using reliable subliminal conditioning paradigms and improved awareness measurements have found evidence against unconscious knowledge sustaining accurate instrumental responses. The present preregistered study proposes a paradigm, in which unconscious processing is stimulated not by subliminally exposing the predictive (conditioned) stimuli, but by employing predictive regularities that are complex and difficult to detect consciously. Participants (N = 211) were exposed to letter strings that, unknown to them, were built from two complex artificial grammars: a "rewarded" or a "non-rewarded" grammar. On each trial, participants memorized a string, and subsequently had to discriminate the memorized string from a distractor. Correct discriminations were rewarded only when the identified string followed the rewarded grammar, but not when it followed the non-rewarded grammar. In a subsequent test phase, participants were presented with new strings from the rewarded and from the unrewarded grammar. Their task was now to directly choose the strings from the rewarded grammar, in order to collect more rewards. A trial-by-trial awareness measure revealed that participants accurately choose novel strings from the rewarded grammar when they had no conscious knowledge of the grammar. The awareness measure also showed that participants were accurate only when the unconsciously learned grammar led to conscious judgments. The present study shows that unconscious knowledge can guide instrumental responses, but only to the extent it supports conscious judgments.

Implicit learning of regularities followed by realistic body movements in virtual reality

The existence of implicit (unconscious) learning has been demonstrated in several laboratory paradigms. Researchers have also suggested that it plays a role in complex real-life human activities. For instance, in social situations, we may follow unconscious behaviour scripts or intuitively anticipate the reaction of familiar persons based on nonconscious cues. Still, it is difficult to make inferences about the involvement of implicit learning in realistic contexts, given that this phenomenon has been demonstrated, almost exclusively, using simple artificial stimuli (e.g., learning structured patterns of letters). In addition, recent analyses show that the amount of unconscious knowledge learned in these tasks has been overestimated by random measurement error. To overcome these limitations, we adapted the artificial grammar learning (AGL) task, and exposed participants (N = 93), in virtual reality, to a realistic agent that executed combinations of boxing punches. Unknown to participants, the combinations were structured by a complex artificial grammar. In a subsequent test phase, participants accurately discriminated novel grammatical from nongrammatical combinations, showing they had acquired the grammar. For measuring awareness, we used trial-by-trial subjective scales, and an analytical method that accounts for the possible overestimation of unconscious knowledge due to regression to the mean. These methods conjointly showed strong evidence for implicit and for explicit learning. The present study is the first to show that humans can implicitly learn, in VR, knowledge regarding realistic body movements, and, further, that implicit knowledge extracted in AGL is robust when accounting for its possible inflation by random measurement error.

Tips From the Top: Do the Best Performers Really Give the Best Advice?

Everyone knows that if you want to learn how to do something, you should get advice from people who do it well. But is everyone right? In a series of studies (N = 8,693), adult participants played a game after receiving performance advice from previous participants. Although advice from the best-performing advisors was no more beneficial than advice from other advisors, participants believed that it had been-and they believed this despite the fact that they were told nothing about their advisors' performance. Why? The best performers did not give better advice, but they did give more of it, and participants apparently mistook quantity for quality. These studies suggest that performing and advising may often be unrelated skills and that in at least some domains, people may overvalue advice from top performers.

Gravity and Known Size Calibrate Visual Information to Time Parabolic Trajectories

Catching a ball in a parabolic flight is a complex task in which the time and area of interception are strongly coupled, making interception possible for a short period. Although this makes the estimation of time-to-contact (TTC) from visual information in parabolic trajectories very useful, previous attempts to explain our precision in interceptive tasks circumvent the need to estimate TTC to guide our action. Obtaining TTC from optical variables alone in parabolic trajectories would imply very complex transformations from 2D retinal images to a 3D layout. We propose based on previous work and show by using simulations that exploiting prior distributions of gravity and known physical size makes these transformations much simpler, enabling predictive capacities from minimal early visual information. Optical information is inherently ambiguous, and therefore, it is necessary to explain how these prior distributions generate predictions. Here is where the role of prior information comes into play: it could help to interpret and calibrate visual information to yield meaningful predictions of the remaining TTC. The objective of this work is: (1) to describe the primary sources of information available to the observer in parabolic trajectories; (2) unveil how prior information can be used to disambiguate the sources of visual information within a Bayesian encoding-decoding framework; (3) show that such predictions might be robust against complex dynamic environments; and (4) indicate future lines of research to scrutinize the role of prior knowledge calibrating visual information and prediction for action control.

Inferences on enacted understanding: using immersive technologies to assess intuitive physical science knowledge

Purpose

This study aims to advance the proposal to use immersive virtual learning environments to stimulate and reveal deep-seated knowledge about science, giving instructors and researchers unique possibilities for assessing and identifying intuitive physical science knowledge. Aside from the ability to present rich and dynamic stimuli, these environments afford bodily enactment of people’s understanding, which draws less from declarative knowledge stores and more from everyday experiences with the physical world.

Design/methodology/approach

The authors ground their proposal in a critical review of the impact of stimulus and task characteristics of traditional physics inventories. Using a grounded theory approach, the authors present classifications and interpretations of observed bodily enactments of physics understandings in a study where participants enacted their understanding of force and motion of space in an immersive, interactive mixed reality (MR) environment.

Findings

The authors find that instances of these action categories can be interpreted as relating to underlying knowledge, often identified by other studies. The authors thus replicate a number of prior findings, which provide evidence to establish validation for using MR simulation as a tool for identifying people’s physical intuitions.

Research limitations/implications

This study targeted only a few specific physical science scenarios. Further, while a number of key insights about student knowledge came from the analysis, many of the observations are mere leads in need of further investigation and interpretation rather than core findings.

Originality/value

Immersive digital learning environments are primarily used for instruction. The authors propose to use and design them for assessment as well. This paper should prompt more research and development in this direction.

Perceptual judgments of duration of parabolic motions

In a 2-alternative forced-choice protocol, observers judged the duration of ball motions shown on an immersive virtual-reality display as approaching in the sagittal plane along parabolic trajectories compatible with Earth gravity effects. In different trials, the ball shifted along the parabolas with one of three different laws of motion: constant tangential velocity, constant vertical velocity, or gravitational acceleration. Only the latter motion was fully consistent with Newton’s laws in the Earth gravitational field, whereas the motions with constant velocity profiles obeyed the spatio-temporal constraint of parabolic paths dictated by gravity but violated the kinematic constraints. We found that the discrimination of duration was accurate and precise for all types of motions, but the discrimination for the trajectories at constant tangential velocity was slightly but significantly more precise than that for the trajectories at gravitational acceleration or constant vertical velocity. The results are compatible with a heuristic internal representation of gravity effects that can be engaged when viewing projectiles shifting along parabolic paths compatible with Earth gravity, irrespective of the specific kinematics. Opportunistic use of a moving frame attached to the target may favour visual tracking of targets with constant tangential velocity, accounting for the slightly superior duration discrimination.

Implicit learning of symmetry of human movement and gray matter density: Evidence against pure domain general and pure domain specific theories of implicit learning

Theories of the neural basis of implicit learning postulated that specific regions were responsible for specific structures (e.g., supra-finite state) regardless of domain (e.g., vision, movement); others assumed that implicit learning was the adaptation that occurred within neural regions dealing with each domain. We explored whether people could implicitly learn to detect symmetry in biological motion, and if so, based on voxel-based morphometry (VBM), whether the learning was associated with language-related regions involved with supra-finite state grammars (such as symmetry) or motor-related regions. To explore the relevance of motor-related regions, we investigated brain structural changes in athletes compared with non-athletes and the advantage of athletes in implicit learning of action symmetry. Further, we examined whether motor imagery ability could account for the role of motor-related regions in this learning. Participants passively observed and memorized a number of biological motion sequences instantiating a symmetry rule and then judged new sequences as grammatical or not. Behaviorally, the implicit acquisition of symmetry could extend to process biological motion. Athletes showed superior classification accuracy and kinesthetic imagery ability, and gave more familiarity attributions. VBM results showed that athletes exhibited greater gray matter density in the right cerebellum, as well as the left lingual gyrus, the left precuneus, the left calcarine gyrus, and the right thalamus. Correlation analysis showed that the cerebellar gray matter density was positively associated with classification accuracy, which was mediated by kinesthetic imagery ability. Moreover, gray matter density of the left inferior frontal cortex was also positively associated with classification accuracy, indicating the involvement of regions related to symmetry learning across domains. The study provides initial evidence that implicit learning involves both adaptation within brain regions responsible for the specific domain as well as brain regions processing the same structure across domains, at least in a case of supra-finite state grammars.

The geometry of consciousness

Conscious experience implies a reference-frame or vantage, which is often important in scientific models. Control models of ball-interception are used as an example. Models that use viewer-dependent egocentric reference-frames are contrasted with viewer-independent allocentric ones. Allocentric reference-frames serve well for models like Newtonian physics, which utilize static coordinate-systems that allow forces and object-movements to be compartmentalized. In contrast, egocentric reference-frames are natural for modeling mobile organisms or robots when controlling perception-action behavior. Lower-level perception-action behavior is often characterized using egocentric coordinate-systems that optimize processing-speed, while higher-level cognitive-processes use allocentric frames that provide a stationary spatial reference. Brain-behavior models like the Ventral-Stream What System, and Dorsal-Stream Where-How System, also respectively utilize allocentric and egocentric reference-frames. Reference-frame clarification can resolve disputes about models of control-tasks like running to catch baseballs, and can provide insights for biomimetic-robots. Confusion regarding geometry and reference-frames contributes to a lack of clarity between how and when egocentric versus allocentric geometries are imposed, with perception-actions generally being more egocentric and conscious experience more allocentric.

Learning to exploit a hidden predictor in skill acquisition: Tight linkage to conscious awareness

It is often assumed that implicit learning of skills based on predictive relationships proceeds independently of awareness. To test this idea, four groups of subjects played a game in which a fast-moving "demon" made a brief appearance at the bottom of the computer screen, then disappeared behind a V-shaped occluder, and finally re-appeared briefly on either the upper-left or upper-right quadrant of the screen. Points were scored by clicking on the demon during the final reappearance phase. Demons differed in several visible characteristics including color, horn height and eye size. For some subjects, horn height perfectly predicted which side the demon would reappear on. For subjects not told the rule, the subset who demonstrated at the end of the experiment that they had spontaneously discovered the rule showed strong evidence of exploiting it by anticipating the demon's arrival and laying in wait for it. Those who could not verbalize the rule performed no better than a control group for whom the demons moved unpredictably. The implications of this tight linkage between conscious awareness and implicit skill learning are discussed.

Scaling sporting equipment for children promotes implicit processes during performance

This study investigated whether children who used scaled equipment compared to full size equipment during a motor task demonstrated reduced conscious involvement in performance. Children (9-11 years) performed a tennis hitting task in two attention conditions (single-task and dual-task) using two types of equipment (scaled and full size). A more skilled group and a less skilled group were formed using hitting performance scores. The more skilled group displayed greater working memory capacity than the less skilled group. For both groups, hitting performance and technique were better when scaled equipment was used. Hitting performance when using scaled equipment was not disrupted in either group by a cognitively demanding secondary task; however, performance was disrupted in the less skilled group when using full size equipment. We conclude that equipment scaling may reduce working memory engagement in motor performance and discuss the findings in the context of implicit motor learning theory.

Modelling unsupervised online-learning of artificial grammars: linking implicit and statistical learning

Humans rapidly learn complex structures in various domains. Findings of above-chance performance of some untrained control groups in artificial grammar learning studies raise questions about the extent to which learning can occur in an untrained, unsupervised testing situation with both correct and incorrect structures. The plausibility of unsupervised online-learning effects was modelled with n-gram, chunking and simple recurrent network models. A novel evaluation framework was applied, which alternates forced binary grammaticality judgments and subsequent learning of the same stimulus. Our results indicate a strong online learning effect for n-gram and chunking models and a weaker effect for simple recurrent network models. Such findings suggest that online learning is a plausible effect of statistical chunk learning that is possible when ungrammatical sequences contain a large proportion of grammatical chunks. Such common effects of continuous statistical learning may underlie statistical and implicit learning paradigms and raise implications for study design and testing methodologies.

Authors' response: the primacy of conscious decision making

The target article sought to question the common belief that our decisions are often biased by unconscious influences. While many commentators offer additional support for this perspective, others question our theoretical assumptions, empirical evaluations, and methodological criteria. We rebut in particular the starting assumption that all decision making is unconscious, and that the onus should be on researchers to prove conscious influences. Further evidence is evaluated in relation to the core topics we reviewed (multiple-cue judgment, deliberation without attention, and decisions under uncertainty), as well as priming effects. We reiterate a key conclusion from the target article, namely, that it now seems to be generally accepted that awareness should be operationally defined as reportable knowledge, and that such knowledge can only be evaluated by careful and thorough probing. We call for future research to pay heed to the different ways in which awareness can intervene in decision making (as identified in our lens model analysis) and to employ suitable methodology in the assessment of awareness, including the requirements that awareness assessment must be reliable, relevant, immediate, and sensitive.

Supra-personal cognitive control and metacognition

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We propose a ‘dual systems’ framework for thinking about metacognition.

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System 1 metacognition is for ‘intra-personal’ cognitive control.

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System 2 metacognition is for ‘supra-personal’ cognitive control.

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The latter allows agents to share metacognitive representations.

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This sharing creates benefits for the group and facilitates cumulative culture.

The human mind is extraordinary in its ability not merely to respond to events as they unfold but also to adapt its own operation in pursuit of its agenda. This ‘cognitive control’ can be achieved through simple interactions among sensorimotor processes, and through interactions in which one sensorimotor process represents a property of another in an implicit, unconscious way. So why does the human mind also represent properties of cognitive processes in an explicit way, enabling us to think and say ‘I’m sure’ or ‘I’m doubtful’? We suggest that ‘system 2 metacognition’ is for supra-personal cognitive control. It allows metacognitive information to be broadcast, and thereby to coordinate the sensorimotor systems of two or more agents involved in a shared task.

The nature of the memory buffer in implicit learning: learning Chinese tonal symmetries

Previous research has established that people can implicitly learn chunks, which (in terms of formal language theory) do not require a memory buffer to process. The present study explores the implicit learning of nonlocal dependencies generated by higher than finite-state grammars, specifically, Chinese tonal retrogrades (i.e. centre embeddings generated from a context-free grammar) and inversions (i.e. cross-serial dependencies generated from a mildly context-sensitive grammar), which do require buffers (for example, last in-first out and first in-first out, respectively). People were asked to listen to and memorize artificial poetry instantiating one of the two grammars; after this training phase, people were informed of the existence of rules and asked to classify new poems, while providing attributions of the basis of their judgments. People acquired unconscious structural knowledge of both tonal retrogrades and inversions. Moreover, inversions were implicitly learnt more easily than retrogrades constraining the nature of the memory buffer in computational models of implicit learning.

Implicit learning of recursive context-free grammars

Context-free grammars are fundamental for the description of linguistic syntax. However, most artificial grammar learning experiments have explored learning of simpler finite-state grammars, while studies exploring context-free grammars have not assessed awareness and implicitness. This paper explores the implicit learning of context-free grammars employing features of hierarchical organization, recursive embedding and long-distance dependencies. The grammars also featured the distinction between left- and right-branching structures, as well as between centre- and tail-embedding, both distinctions found in natural languages. People acquired unconscious knowledge of relations between grammatical classes even for dependencies over long distances, in ways that went beyond learning simpler relations (e.g. n-grams) between individual words. The structural distinctions drawn from linguistics also proved important as performance was greater for tail-embedding than centre-embedding structures. The results suggest the plausibility of implicit learning of complex context-free structures, which model some features of natural languages. They support the relevance of artificial grammar learning for probing mechanisms of language learning and challenge existing theories and computational models of implicit learning.