Distinguishing implicit and explicit learning

1-Back reinforcement symbolic-matching by humans: How do they learn it?

For humans, a distinction has been made between implicit and explicit learning. Implicit learning is thought to involve automatic processes of the kind involved in much Pavlovian conditioning, while explicit learning is thought to involve conscious hypothesis testing and rule formation, in which the subject's statement of the rule has been taken as evidence of explicit learning. Various methods have been used to determine if nonverbal animals are able to learn a task explicitly - among these is the 1-back reinforcement task in which feedback from performance on the current conditional discrimination trial is provided only after completion of the following trial. We propose that it is not whether an organism can learn the task, but whether they learn it rapidly, all-or-none, that provides a better distinction between the two kinds of learning. We had humans learn a symbolic matching, 1-back reinforcement task. Almost half of the subjects failed to learn the task, and of those who did, none described the 1-back rule. Thus, it is possible to learn this task without learning the 1-back rule. Furthermore, the backward learning functions for humans differ from those of pigeons. Human subjects who learned the task did so all-or-none, suggesting explicit learning. In earlier research with pigeons, they too showed significant learning of this task; however, backward learning functions suggested that they did so gradually over the course of several sessions of training and to a lower level of asymptotic accuracy than the humans, a result suggesting implicit learning was involved.

Additional cognitive load decreases performance but not adaptation to a visuomotor transformation

Dual-task paradigms are procedures for investigating interference with two tasks performed simultaneously. Studies that previously addressed dual-task paradigms within a visuomotor reaching task yielded mixed results. While some of the studies found evidence of cognitive interference, called dual-task costs, other studies did not. We assume that dual-task costs only manifest themselves within the explicit component of adaptation, as it involves cognitive resources for processing. We suspect the divergent findings to be due to the lack of differentiation between the explicit and implicit component. In this study, we aimed to investigate how a cognitive secondary task affects visuomotor adaptation overall and its different components, both during and after adaptation. In a series of posttests, we examined the explicit and implicit components separately. Eighty participants performed a center-outward reaching movement with a 30° cursor perturbation. Participants were either assigned to a single task group (ST) or a dual-task group (DT) with an additional auditory 1-back task. To further enhance our predicted effect of dual-task interference on the explicit component, we added a visual feedback delay condition to both groups (ST/DT_DEL). In the other condition, participants received visual feedback immediately after movement termination (ST/DT_NoDEL). While there were clear dual-task costs during the practice phase, there were no dual-task effects on any of the posttest measures. On one hand, our findings suggest that dual-task costs in visuomotor adaptation tasks can occur with sufficient cognitive demand, and on the other hand, that cognitive constraints may affect motor performance but not necessarily motor adaptation.

1-Back reinforcement matching and mismatching by pigeons: Implicit or explicit learning?

In human learning a distinction has been made between implicit and explicit learning. Implicit learning is thought involve automatic processes of the kind involved in Pavlovian conditioning, while explicit learning is thought to involve conscious hypothesis testing and rule formation, in which the ability to report the rule used to learn the task is taken as evidence. Because non-verbal animals cannot provide such evidence, several indirect methods have been proposed. One of these methods is faster learning by humans of certain explicitly learned tasks than implicitly learned tasks, but pigeons do not show a similar difference. Another method involves the 1-back-reinforcement conditional discrimination (if A choose X, if B choose Y) in which feedback following the conditional response is delayed until the next trial. It has been argued that implicit learning cannot occur over the delay between the conditional response and the reinforcer on the next trial, yet, it has been found that monkeys can learn this 1-back reinforcement task. We have argued that such learning can occur implicitly. We have found that pigeons, a species not thought to learn explicitly, can show significant learning of both 1-back reinforcement matching and 1-back reinforcement mismatching, two versions of the 1-back-reinforcement conditional discrimination. We propose that the evidence for explicit learning by non-verbal animals suffers from alternative simpler accounts because the rationale for explicit learning is based on assumptions that likely are not correct.

The art gallery maze: a novel tool to assess human navigational abilities

Humans differ widely in their ability to navigate effectively through the environment and in spatial memory skills. Navigation in the environment requires the analysis of many spatial cues, the construction of internal representations, and the use of various strategies. We present a novel tool to assess individual differences in human navigation, consisting of a virtual radial-arm maze presented as an art gallery to explore whether different sets of instructions (intentional or incidental) affect subjects' navigation performance. We furthermore tested the effect of the instructions on exploration strategies during both place learning and recall. We evaluated way-finding ability in 42 subjects, and individual differences in navigation were assessed through the analysis of navigational paths, which permitted the isolation and definition of a few strategies adopted by the incidental and intentional instructions groups. Our results showed that the intentional instruction group performed better than the other group: these subjects correctly paired each central statue and the two paintings in the adjacent arms, and they made less working and reference memory errors. Our analysis of path lengths showed that the intentional instruction group spent more time in the maze (thus being slower), specifically in the central hall, and covered more distance; the time spent in the main hall was, therefore, indicative of the quality of the following performance. Studying how environmental representations and the relative navigational strategies vary among "intentional" and "incidental" groups provides a new window into the acknowledgment of possible strategies to help subjects construct more efficient approaches in human navigation.

Herding in human groups is related to high autistic traits

Herding is ubiquitous throughout all social life forms, providing beneficial outcomes. Here, we examine whether herding emerges spontaneously in human groups and whether it adheres to the core principles of herding observed in the animal kingdom. Using a computerized paradigm involving the movements of circles, we tested the emergence of spontaneous and intentional herding of 136 participants assigned into groups of four participants. Herding was assessed by measuring directional synchrony in the movements of the circles, level of cohesion, and separation between circles. We found that human groups tend to spontaneously herd, particularly in terms of directional synchrony, supporting the notion of a human herding instinct. We further asked whether individuals with high traits of Autism Spectrum Disorder (ASD) exhibit differences in their herding tendencies. Results indicated that individuals with high ASD traits showed greater social separation from the group, compared to individuals with low ASD traits. Moreover, we found diminished spontaneous synchrony, but intact instructed synchrony in the high vs. the low ASD traits group. We contend that humans spontaneously herd with their group and suggest that the spontaneous tendency to synchronize with others is diminished in individuals with high ASD traits, though it is recovered when synchronization is intentional.

Assessing explicit strategies in force field adaptation

In recent years, it has become increasingly clear that a number of learning processes are at play in visuomotor adaptation tasks. In addition to implicitly adapting to a perturbation, learners can develop explicit knowledge allowing them to select better actions in responding to it. Advances in visuomotor rotation experiments have underscored the important role of such "explicit learning" in shaping adaptation to kinematic perturbations. Yet, in adaptation to dynamic perturbations, its contribution has been largely overlooked. We therefore sought to approach the assessment of explicit learning in adaptation to dynamic perturbations, by developing two novel modifications of a force field experiment. First, we asked learners to abandon any cognitive strategy before selected force channel trials to expose consciously accessible parts of overall learning. Here, learners indeed reduced compensatory force compared with standard Catch channels. Second, we instructed a group of learners to mimic their right hand's adaptation by moving with their naïve left hand. While a control group displayed negligible left hand force compensation, the mimicking group reported forces that approximated right hand adaptation but appeared to under-report the velocity component of the force field in favor of a more position-based component. Our results highlight the viability of explicit learning as a potential contributor to force field adaptation, though the fraction of learning under participants' deliberate control on average remained considerably smaller than that of implicit learning, despite task conditions favoring explicit learning. The methods we employed provide a starting point for investigating the contribution of explicit strategies to force field adaptation.NEW & NOTEWORTHY While the contribution of explicit learning has been increasingly studied in visuomotor adaptation, its contribution to force field adaptation has not been studied extensively. We employed two novel methods to assay explicit learning in a force field adaptation task and found that learners can voluntarily control aspects of compensatory force production and manually report it with their untrained limb. This supports the general viability of the contribution of explicit learning also in force field adaptation.

The effects of ordinal load on incidental temporal learning

How can we grasp the temporal structure of events? A few studies have indicated that representations of temporal structure are acquired when there is an intention to learn, but not when learning is incidental. Response-to-stimulus intervals, uncorrelated temporal structures, unpredictable ordinal information, and lack of metrical organization have been pointed out as key obstacles to incidental temporal learning, but the literature includes piecemeal demonstrations of learning under all these circumstances. We suggest that the unacknowledged effects of ordinal load may help reconcile these conflicting findings, ordinal load referring to the cost of identifying the sequence of events (e.g., tones, locations) where a temporal pattern is embedded. In a first experiment, we manipulated ordinal load into simple and complex levels. Participants learned ordinal-simple sequences, despite their uncorrelated temporal structure and lack of metrical organization. They did not learn ordinal-complex sequences, even though there were no response-to-stimulus intervals nor unpredictable ordinal information. In a second experiment, we probed learning of ordinal-complex sequences with strong metrical organization, and again there was no learning. We conclude that ordinal load is a key obstacle to incidental temporal learning. Further analyses showed that the effect of ordinal load is to mask the expression of temporal knowledge, rather than to prevent learning.

A Dissociation of Implicit and Explicit Spatial Sequence Learning in a Group of Students With Learning Difficulties

Traditionally, research on learning difficulties focuses on deficits in explicit learning processes. However, the impact of implicit (incidental, unconscious, and unaware) learning has sparsely been investigated. Hence, this study aims to dissociate implicit and explicit learning abilities in a group of 50 students with severe and persisting learning difficulties and compares their learning performance to non-impaired students. Individuals accomplished two different versions of a computerized serial reaction time task (SRTT) as a measure of implicit and explicit learning. Analyses revealed that (a) both learning processes can be dissociated by psychometric IQ; (b) students with learning difficulties have deficits in both implicit and explicit learning processes; and (c) it is possible to identify subgroups of adolescents with implicit and explicit learning difficulties. Theoretical as well as educational implications are discussed.

Qualitative differences between implicit and explicit sequence learning

Four experiments investigate the differences between implicit and explicit sequence learning concerning their resilience to structural and superficial task changes. A superficial change that embedded the SRT task in the context of a selection task, while maintaining the sequence, did selectively hinder the expression of implicit learning. In contrast, a manipulation that maintained the task surface, but decreased the sequence validity, affected the expression of learning specifically when it was explicit. These results are discussed in the context of a dynamic framework (Cleeremans & Jiménez, 2002), which assumes that implicit knowledge is specially affected by contextual factors and that, as knowledge becomes explicit, it allows for the development of relevant metaknowledge that modulates the expression of explicit knowledge.

Implicit perceptual training: how, when, and why?

The perceptual skills underlying anticipatory movement in sport have been the focus of much research over the past 20 years. Methods for training such skills have tended to emphasise explicit specification of discriminative cues and the rules linking changes in the perceptual field with required responses. Recently, researchers have begun to examine less prescriptive methods of training. In the present paper, we examine conceptual, methodological, and practical issues associated with whether such skills can or indeed should be trained implicitly. The implications of two ways of conceptualising the explicit-implicit distinction for the methods used to promote implicit learning and the tests used to assess the nature of learning are considered. Finally, potential advantages of implicitly learned skills relating to task complexity and robustness under stress are discussed.

The neural correlates of implicit and explicit sequence learning: Interacting networks revealed by the process dissociation procedure

In two H2(15)O PET scan experiments, we investigated the cerebral correlates of explicit and implicit knowledge in a serial reaction time (SRT) task. To do so, we used a novel application of the Process Dissociation Procedure, a behavioral paradigm that makes it possible to separately assess conscious and unconscious contributions to performance during a subsequent sequence generation task. To manipulate the extent to which the repeating sequential pattern was learned explicitly, we varied the pace of the choice reaction time task-a variable that is known to have differential effects on the extent to which sensitivity to sequence structure involves implicit or explicit knowledge. Results showed that activity in the striatum subtends the implicit component of performance during recollection of a learned sequence, whereas the anterior cingulate/mesial prefrontal cortex (ACC/MPFC) supports the explicit component. Most importantly, we found that the ACC/MPFC exerts control on the activity of the striatum during retrieval of the sequence after explicit learning, whereas the activity of these regions is uncoupled when learning had been essentially implicit. These data suggest that implicit learning processes can be successfully controlled by conscious knowledge when learning is essentially explicit. They also supply further evidence for a partial dissociation between the neural substrates supporting conscious and nonconscious components of performance during recollection of a learned sequence.

Methods for studying unconscious learning

One has to face numerous difficulties when trying to establish a dissociation between conscious and unconscious knowledge. In this paper, we review several of these problems as well as the different methodological solutions that have been proposed to address them. We suggest that each of the different methodological solutions offered refers to a different operational definition of consciousness, and present empirical examples of sequence learning studies in which these different procedures were applied to differentiate between implicit and explicit knowledge acquisition. We also show how the use of a sensitive behavioral method, the process dissociation procedure, confers a distinctive advantage in brain-imaging studies when aiming to delineate the neural correlates of conscious and unconscious processes in sequence learning.

The role of taxonomies in the study of human memory

The idea that memory is not unitary but is instead composed of multiple systems has a long history and has been debated with particular vigor in the last 20 years. Nevertheless, whether or not there are multiple memory systems remains unsettled. In this article, we suggest that psychologists wishing to classify memory can learn from biological systematics, the discipline that creates taxonomies of species. In so doing, we suggest that psychologists have made two assumptions in classifying memory: that features of memory are perfectly correlated, and that there is a straightforward mapping between taxonomy and theory. We argue that these assumptions are likely to be incorrect, but we also argue that there is a place for taxonomy in the study of memory. Taxonomies of memory are organizational schemes for data--they are descriptive, not explanatory--and so can inspire theory, although they cannot serve as theories themselves.

Finite mixture distribution models of simple discrimination learning

Through the application of finite mixture distribution models, we investigated the existence of distinct modes of behavior in learning a simple discrimination. The data were obtained in a repeated measures study in which subjects aged 6 to 10 years carried out a simple discrimination learning task. In contrast to distribution models of exclusively rational learners or exclusively incremental learners, a mixture distribution model of rational learners and slow learners was found to fit the data of all measurement occasions and all age groups. Hence, the finite mixture distribution analysis provides strong support for the existence of distinct modes of learning behavior. The results of a second experiment support this conclusion by crossvalidation of the models that fit the data of the first experiment. The effect of verbally labeling the values on the relevant stimulus dimension and the consistency of behavior over measurement occasions are related to the mixture model estimates.

Is there cross-format transfer in implicit invariance learning?

Three experiments investigated cross-form transfer in the invariance learning paradigm introduced by McGeorge and Burton (1990). The results suggest that the transfer observed by McGeorge and Burton depended on subjects' ability to use a response strategy discovered by Wright and Burton (1995). When that strategy was denied to subjects (Experiments 1 and 2), no cross-form transfer was observed; when the strategy was made available (Experiment 3), cross-form transfer re-emerged. These results suggest that this form of learning, like many other forms of implicit learning and memory, is hyperspecific.

Memory and learning for a novel written style

Subjects read and recalled a series of five short stories in one of four plot and style combinations. The stories were written in one of two styles that consisted of opposing clause orders (i.e., independent-dependent vs. dependent-independent), tense forms (i.e., past vs. present), and descriptor forms (modifier modifier vs. modifier as a noun). The subjects incorporated both plot and style characteristics into their recalls. Other subjects, who, after five recalls, either generated a new story or listed the rules that had been followed by the stories read, included the marked forms of the characteristics they learned more often, except for tense. The subjects read and recalled four stories of the same plot and style and then read and recalled a fifth story of the same plot and style or of one of the other three plot/style combinations. Ability to switch style depended on both the characteristic and the markedness.