Episodic knowledge and implicit learning

By Carrot or by Stick: The Influence of Encouraging and Discouraging Facial Feedback on Implicit Rule Learning

Implicit learning refers to the process of unconsciously learning complex knowledge through feedback. Previous studies investigated the influences of different types of feedback (e.g., social and non-social feedback) on implicit learning. This study focused on the social information presented in the learning situation and tried to explore the effects of different social feedback on implicit rule learning. We assigned participants randomly into an encouraging facial feedback group (happy expression for correct answer, neutral but not negative expression for incorrect answer) and a discouraging facial feedback group (neutral but not happy expression for correct answer, negative expression for incorrect answer). The implicit learning task included four difficulty levels, and social feedback was presented in the learning phase but not the testing phase in two experiments. The only difference between the two experiments was that the sad face used as negative feedback in Experiment 1 was replaced with an angry face in Experiment 2 to enhance the ecological validity of the discouraging facial feedback group. These two experiments yielded consistent results: the performances in the encouraging facial feedback group were more accurate in both the learning and the testing phases at all difficulty levels. These findings indicated that the influence of encouraging social feedback for a better implicit learning achievement was stable and established a new groundwork for future research on incentive-based education, making it critical to investigate the impact of various forms of encouraging-based education on 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.

Effects of Noise on the Behavioral and Neural Categorization of Speech

We investigated whether the categorical perception (CP) of speech might also provide a mechanism that aids its perception in noise. We varied signal-to-noise ratio (SNR) [clear, 0 dB, -5 dB] while listeners classified an acoustic-phonetic continuum (/u/ to /a/). Noise-related changes in behavioral categorization were only observed at the lowest SNR. Event-related brain potentials (ERPs) differentiated category vs. category-ambiguous speech by the P2 wave (~180-320 ms). Paralleling behavior, neural responses to speech with clear phonetic status (i.e., continuum endpoints) were robust to noise down to -5 dB SNR, whereas responses to ambiguous tokens declined with decreasing SNR. Results demonstrate that phonetic speech representations are more resistant to degradation than corresponding acoustic representations. Findings suggest the mere process of binning speech sounds into categories provides a robust mechanism to aid figure-ground speech perception by fortifying abstract categories from the acoustic signal and making the speech code more resistant to external interferences.

Asymmetrical effects of control on the expression of implicit sequence learning

As an automatic process, implicit learning effects have been characterized as inflexible and largely tied to the reinstatement of the acquisition context. However, implicit learning transfer has been observed under certain conditions, depending on the changes introduced between training and transfer. Here, we assess the hypothesis that transfer is specifically hindered by those changes that increase the control demands required by the orienting task with respect to those faced over training. Following on previous results by Jiménez et al. (J Exp Psychol Learn Memory Cognit 32(3):475-490, 2006), which showed that the learning acquired over a standard serial reaction time task was not transferred to conditions requiring a more demanding search task, we explored the impact of symmetrical training and transfer conditions, and showed that sequence learning survived such transfer. Four additional experiments designed to assess transfer to either lower or higher control demands confirmed that the expression of learning was selectively hindered by those transfer conditions requiring higher levels of control demands. The results illustrate how implicit sequence learning can be indirectly subjected to cognitive control.

Implicit learning: news from the front

Can we learn without awareness? While the current consensus is most likely to be `no', there is, however, considerable ongoing debate about the role that consciousness plays in cognition and about the nature of consciousness itself. In this article, we review recent advances in the field of implicit learning, based on three perspectives: empirical findings (including neuropsychological evidence), methodological issues, and theoretical positions (including computational models). The overall picture that emerges is complex and reflects a field that is very much in flux: while it seems undeniable that cognition involves some form of unconscious processing, it is as yet unclear how to best separate conscious and unconscious influences on learning, and how to best think about the status of the `cognitive unconscious'. We suggest that implicit learning is best construed as a complex form of priming taking place in continuously learning neural systems, and that the distributional knowledge so acquired can be causally efficacious in the absence of awareness that this knowledge was acquired or that it is currently influencing processing, that is, in the absence of metaknowledge.

Applying an exemplar model to the artificial-grammar task: inferring grammaticality from similarity

We present three artificial-grammar experiments. The first used position constraints, and the second used sequential constraints. The third varied both the amount of training and the degree of sequential constraint. Increasing both the amount of training and the redundancy of the grammar benefited participants' ability to infer grammatical status; nevertheless, they were unable to describe the grammar. We applied a multitrace model of memory to the task. The model used a global measure of similarity to assess the grammatical status of the probe and captured performance both in our experiments and in three classic studies from the literature. The model shows that retrieval is sensitive to structure in memory, even when individual exemplars are encoded sparsely. The work ties an understanding of performance in the artificial-grammar task to the principles used to understand performance in episodic-memory tasks.

Incidental learning of secondary attentional cueing

Subjects instructed to detect targets following moderately valid location cues started being presented at some point in the course of the experiment, without having been informed about it, with a color secondary cue on all invalidly cued trials. In Experiment 1 most subjects quickly learned to use the secondary cue, ending in latency cost being eliminated or even turned negative. The effect failed to manifest only when the secondary cue appeared outside the object serving as imperative cue. Experiment 2 showed that performance with a secondary cue differed significantly from the performance in two control conditions in which colors were not correlated with validity or were not presented at all. On the other hand, it resembled performance of subjects informed beforehand about the secondary cue. Awareness of the contingency as well as of its effect on behavior was probed by a post-test questionnaire. An effect of learning without awareness was not observed in Experiment 1, but was found in Experiment 3, where awareness was probed more shortly after the emergence of incidental learning. Conceivably, subjects first learn to use the contingencies implicitly, and only later do they become aware of the outcome of that learning. Apparently, the attentional system might incidentally learn contingencies detected while being engaged in another task and use them for orienting despite a partial conflict with the following as instructed endogenous cues.

Context-specific learning and control: the roles of awareness, task relevance, and relative salience

The processes mediating dynamic and flexible responding to rapidly changing task-environments are not well understood. In the present research we employ a Stroop procedure to clarify the contribution of context-sensitive control processes to online performance. In prior work Stroop interference varied as a function of probe location context, with larger Stroop interference occurring for contexts associated with a high proportion of congruent items [Crump, M. J., Gong, Z., & Milliken, B. (2006). The context-specific proportion congruent stroop effect: location as a contextual cue. Psychonomic Bulletin &Review, 13, 316-321.] Here, we demonstrate that this effect does not depend on awareness of the context manipulation, but that it can depend on attention to the predictive context dimension, and on the relative salience of the target and predictive context dimensions. We discuss the implications of our results for current theories of cognitive control.

First- and third-person approaches in implicit learning research

How do we find out whether someone is conscious of some information or not? A simple answer is "We just ask them"! However, things are not so simple. Here, we review recent developments in the use of subjective and objective methods in implicit learning research and discuss the highly complex methodological problems that their use raises in the domain.

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.

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 Influence of Grammatical, Local, and Organizational Redundancy on Implicit Learning: An Analysis Using Information Theory

People behave as if they know the structure of their environment. Because people rarely study that structure explicitly, several theorists have postulated an implicit learning system that abstracts that structure automatically. An alternative view is that people respond to local structure that derives from global structure. Measures are developed that quantify structure in a set of stimuli, in individual stimuli, and in encoded stimuli. The authors apply the measures to examine serial recall for sequences of colors generated using a stationary Markov grammar. They demonstrate that the 3 kinds of redundancy are confounded and show that the memorial advantage for grammatical stimuli reflects participants' use of local expressions of grammatical structure to aid learning.

Implicit preferences: The role(s) of familiarity in the structural mere exposure effect

In four experiments using an artificial grammar (AG) learning procedure, the authors examined the links between the "classic" mere exposure effect [heightened affect for previously encountered stimulus items (Bornstein, 1989; Zajonc, 1968)] and the "structural" mere exposure effect [greater hedonic appreciation for novel stimuli that conform to an implicitly acquired underlying rule system (Gordon & Holyoak, 1983)]. After learning, participants: (a) classified stimuli according to whether they conformed to the principles of the grammar and, (b) rated them in terms of how much they liked them. In some experiments unusual and unfamiliar symbols were used to instantiate the AG, in others highly familiar characters were used. In all cases participants showed standard AG learning. However, whether the two exposure effects emerged was dependent on symbol familiarity. Symbols with high a priori familiarity produced a structural mere exposure effect. Moderately familiar symbols produced only the classic, but not the structural, mere exposure effect. Highly unfamiliar symbols produced neither exposure effect. Results are discussed in the context of implicit learning theory and implications for a general theory of aesthetics are presented.

Is implicit learning spared in amnesia? Rule abstraction and item familiarity in artificial grammar learning

We examined implicit learning of an artificial grammar in amnesic and control participants. The "biconditional" grammar used to generate study and test strings allows two potential sources of judgements in artificial grammar learning to be unconfounded: participants could either learn the abstract biconditional rules or could learn about the distributional statistics of the surface elements (e.g. bigrams) composing the study items. Test strings varied these two sources orthogonally. We found no evidence of abstract rule learning either in the control or amnesic groups. In contrast, both groups learned about the surface elements and tended to call test strings "grammatical" when they were composed of familiar bigrams. However, this sensitivity to bigram familiarity was significantly reduced in the amnesic compared to the control group. The results challenge the claim that implicit learning is intact in amnesia.

Generate and test: an alternative route to knowledge elicitation in an implicit learning task

Three experiments are reported, which examine generation of knowledge in the McGeorge and Burton (1990) invariant learning task. In this task, participants are exposed to 30 four-digit numbers containing an invariant "3". Following this participants then demonstrate a preference for novel numbers containing this invariant over numbers without it. Despite above-chance performance on this pseudo-memory test, participants appear unable to verbalize anything pertinent to the invariant. Here we introduce a novel version of this task, relying on generation of items rather than a preference test. We argue that this new task engages different processing resources, resulting in different patterns of performance. In Experiment 1, invariant learning was demonstrated using a novel fragment completion test. Experiment 2 found that suppressing articulation inhibited learning, implying that this test task accesses phonological knowledge. It is suggested that using the fragment completion test engages different processing resources during test from those in a preference test. Experiment 3 reinforces this position by demonstrating that knowledge appears to transfer across surface features, a result that seems to contradict recent findings by Stadler, Warren, and Lesch (2000). A resolution is offered, drawing on episodic accounts of implicit learning.

The formation of structurally relevant units in artificial grammar learning

A total of 78 adult participants were asked to read a sample of strings generated by a finite state grammar and, immediately after reading each string, to mark the natural segmentation positions with a slash bar. They repeated the same task after a phase of familiarization with the material, which consisted, depending on the group involved, of learning items by rote, performing a short-term matching task, or searching for the rules of the grammar. Participants formed the same number of cognitive units before and after the training phase, thus indicating that they did not tend to form increasingly large units. However, the number of different units reliably decreased, whatever the task that participants had performed during familiarization. This result indicates that segmentation was increasingly consistent with the structure of the grammar. A theoretical account of this phenomenon, based on ubiquitous principles of associative memory and learning, is proposed. This account is supported by the ability of a computer model implementing those principles, PARSER, to reproduce the observed pattern of results. The implications of this study for developmental theories aimed at accounting for how children become able to parse sensory input into physically and linguistically relevant units are discussed.

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.

Can sequence learning be implicit? New evidence with the process dissociation procedure

Can we learn without awareness? Although this issue has been extensively explored through studies of implicit learning, there is currently no agreement about the extent to which knowledge can be acquired and projected onto performance in an unconscious way. The controversy, like that surrounding implicit memory, seems to be at least in part attributable to unquestioned acceptance of the unrealistic assumption that tasks are process-pure--that is, that a given task exclusively involves either implicit or explicit knowledge. Methods such as the process dissociation procedure (PDP, Jacoby, 1991) have been developed to overcome the conceptual limitations of the process purity assumption but have seldom been used in the context of implicit learning research. In this paper, we show how the PDP can be applied to a free generation task so as to disentangle explicit and implicit sequence learning. Our results indicate that subjects who are denied preparation to the next stimulus nevertheless exhibit knowledge of the sequence through their reaction time performance despite remaining unable (1) to project this knowledge in a recognition task and (2) to refrain from expressing their knowledge when specifically instructed to do so. These findings provide strong evidence that sequence learning can be unconscious.

Abstractionist and processing accounts of implicit learning

Five experiments evaluated the contributions of rule, exemplar, fragment, and episodic knowledge in artificial grammar learning using memorization versus hypothesis-testing training tasks. Strings of letters were generated from a biconditional grammar that allows different sources of responding to be unconfounded. There was no evidence that memorization led to passive abstraction of rules or encoding of whole training exemplars. Memorizers instead used explicit fragment knowledge to identify the grammatical status of test items, although this led to chance performance. Successful hypothesis-testers classified at near-perfect levels by processing training and test stimuli according to their rule structure. The results support the episodic-processing account of implicit and explicit learning.

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.

Wie nützlich sind Sequenzlernaufgaben? Zum theoretischen Status und der empirischen Befundlage eines Forschungsparadigmas

Zusammenfassung. Sequenzlernaufgaben sind äußerst einfache Wahlreaktionsaufgaben, die in der kognitionspsychologischen Lernforschung inzwischen erstaunlich populär geworden sind. Wir analysieren mögliche Ursachen dieser Popularität, indem wir den theoretischen Status dieses Aufgabentyps betrachten, und skizzieren überblicksartig die einschlägigen Forschungsbemühungen. Letztere lassen sich grob in zwei Kategorien einteilen. Zum einen sollen mit Sequenzlernaufgaben Dissoziationen zwischen qualitativ verschiedenen expliziten (oft als “bewußt” bezeichneten) und impliziten (oft als “unbewußt” bezeichneten) Lernprozessen untersucht werden. Zum anderen wird versucht, durch direkte Manipulationen der Lernbedingungen Hypothesen über Mechanismen zu prüfen, die dem Sequenzlernen zugrunde liegen sollen. Wir resümieren, daß der Dissoziationsanspruch bis heute nicht überzeugend eingelöst worden ist, daß aber die Beschäftigung mit Sequenzlernaufgaben unabhängig davon wertvolle Beiträge zum Verständnis von Sequenzlernen per se erbringt.

DOS-based exercises that demonstrate classic studies in human memory

Ten exercises are described that demonstrate some classic experiments in human memory and cognition. The studies, prepared in MEL Professional V1.0, have been incorporated in an undergraduate class taught by the author for a number of years. Survey data from students completing the course indicate that the exercises promote understanding of class material. Availability of the programs is described.

Two tests of instance-based and abstract rule-based accounts of invariant learning

Two manipulations are argued to distinguish between instance-based and abstract rule-based accounts of invariant learning. Three experiments examined the effects of manipulating the type of invariant feature in the learning set, and the type of training schedules prior to test. In line with traditional research, selection bias at test was present when the invariant was the consistent inclusion of a stimulus item in the learning set. However, the degree of bias was identical when the invariant was the consistent exclusion of the stimulus item. In addition, negative transfer of training was observed when subjects were trained on one learning set and then shifted training to the opposite learning set, but no positive transfer of training was observed when subjects were trained on one learning set and then continued training using the same learning set. These results are argued to be evidence for instance-based accounts of invariant learning.

The role of implicit memory in controlling a dynamic system

The relationship between implicit memory and implicit learning is explored. Dienes and Fahey (1995) showed that learning to control a dynamic system was mediated by a look-up table consisting of previously successful responses to specific situations. The experiment reported in this paper showed that facilitated performance on old situations was independent of the subjects' ability to recognize those situations as old, suggesting that memory was implicit. Further analyses of the Dienes and Fahey data replicated this independence of control performance on recognition. However, unlike the implicit memory revealed on fragment completion tasks, successful performance on the dynamic control tasks was remarkably resilient to modality shifts. The results are discussed in terms of models of implicit learning and the nature of implicit memory.

Induction of relational schemas: common processes in reasoning and complex learning

Five experiments were performed to test whether participants induced a coherent representation of the structure of a task, called a relational schema, from specific instances. Properties of a relational schema include: An explicit symbol for a relation, a binding that preserves the truth of a relation, potential for higher-order relations, omnidirectional access, potential for transfer between isomorphs, and ability to predict unseen items in isomorphic problems. However relational schemas are not necessarily coded in abstract form. Predictions from relational schema theory were contrasted with predictions from configural learning and other nonstructural theories in five experiments in which participants were taught a structure comprised of a set of initial-state,operator-->end-state instances. The initial-state,operator pairs were presented and participants had to predict the correct end-state. Induction of a relational schema was achieved efficiently by adult participants as indicated by ability to predict items of a new isomorphic problem. The relational schemas induced showed the omnidirectional access property, there was efficient transfer to isomorphs, and structural coherence had a powerful effect on learning. The "learning to learn" effect traditionally associated with the learning set literature was observed, and the long-standing enigma of learning set acquisition is explained by a model composed of relational schema induction and structure mapping. Performance was better after reversal of operators than after shift to an alternate structure, even though the latter entailed more overlap with previously learned tasks in terms of the number of configural associations that were preserved. An explanation for the reversal shift phenomenon in terms of induction and mapping of a relational schema is proposed. The five experiments provided evidence supporting predictions from relational schema theory, and no evidence was found for configural or nonstructural learning theories.