Implicit learning of a repeated segment in continuous tracking: a reappraisal

Several prior studies (e.g., Shea, Wulf, Whitacre, & Park, 2001; Wulf & Schmidt, 1997) have apparently demonstrated implicit learning of a repeated segment in continuous-tracking tasks. In two conceptual replications of these studies, we failed to reproduce the original findings. However, these findings were reproduced in a third experiment, in which we used the same repeated segment as that used in the Wulf et al. studies. Analyses of the velocity and the acceleration of the target suggests that this repeated segment could be easier to track than the random segments serving as control, accounting for the results of Wulf and collaborators. Overall these experiments suggest that learning a repeated segment in continuous-tracking tasks may be much more difficult than learning from a repeated sequence in conventional serial reaction time tasks. A possible explanation for this difference is outlined.     

Implicit sequence learning in a continuous pursuit-tracking task

Assessing implicit learning in the continuous pursuit-tracking task usually concerns a repeated segment of target displacements masked by two random segments, as referred to as Pew’s paradigm. Evidence for segment learning in this paradigm is scanty and contrasts with robust sequence learning in discrete tracking tasks. The present study investigates this issue with two experiments in which participants (N = 56) performed a continuous tracking task. Contrary to Pew’s paradigm, participants were presented with a training sequence that was continuously cycled during 14 blocks of practice, but Block 12 in which a transfer sequence was introduced. Results demonstrate sequence learning in several conditions except in the condition that was obviously the most similar to previous studies failing to induce segment learning. Specifically, it is shown here that a target moving too slowly combined with variable time at which target reversal occurs prevents sequence learning. In addition, data from a post-experimental recognition test indicate that sequence learning was associated with explicit perceptual knowledge about the repetitive structure. We propose that learning repetition in a continuous tracking task is conditional on its capacity to (1) allow participants to detect the repeated regularities and (2) restrict feedback-based tracking strategies.     

Implicit versus explicit learning processes in a probabilistic, continuous fine-motor catching task

We compared the influences of explicit instruction and uninstructed implicit learning of correlations among visual events, in a fine-motor task. The task required visual tracking of a small "ball" of light and "catching" it by means of joystick manipulation. A general pattern of improvement with practice for instructed and "noninstructed" conditions was found. Additionally, both instructed and noninstructed conditions evidenced use of the predictive relationships among stimulus events. The improvement in overall performance caused by explicit verbal instructions was less than the improvement seen with the implicit learning condition. Further, instructed and noninstructed conditions showed different patterns of joystick activity. These findings suggest a qualitatively different approach to visual information processing and task performance for the instructional conditions     

Implicit learning of tonality: a self-organizing approach

Tonal music is a highly structured system that is ubiquitous in our cultural environment. We demonstrate the acquisition of implicit knowledge of tonal structure through neural self-organization resulting from mere exposure to simultaneous and sequential combinations of tones. In the process of learning, a network with fundamental neural constraints comes to internalize the essential correlational structure of tonal music. After learning, the network was run through a range of experiments from the literature. The model provides a parsimonious account of a variety of empirical findings dealing with the processing of tone, chord, and key relationships, including relatedness judgments, memory judgments, and expectancies. It also illustrates the plausibility of activation being a unifying mechanism underlying a range of cognitive tasks.     

Implicit sequence learning in a search task

This study investigated the effects of selection demands on implicit sequence learning. Participants in a search condition looked for a target among seven distractors and responded on the target identity. The responses followed a deterministic sequence, and sequence learning was compared to that found in two control conditions in which the targets were presented alone, either at a central location or over a series of unpredictable locations. Sequence learning was obtained in all conditions, and it was equivalent for the two variable location conditions, regardless of the perceptual demands. Larger effects of learning were observed in the central location, both on the indirect measures and on the measures taken from a cued-generation task. The expression of learning decreased selectively in this condition when the sequence validity was reduced over a test block. These results are consistent with the claims that implicit and explicit learning are mixed in this central condition and that implicit learning is not affected by selection difficulty.     

Implicit sequence learning in a search task

This study investigated the effects of selection demands on implicit sequence learning. Participants in a search condition looked for a target among seven distractors and responded on the target identity. The responses followed a deterministic sequence, and sequence learning was compared to that found in two control conditions in which the targets were presented alone, either at a central location or over a series of unpredictable locations. Sequence learning was obtained in all conditions, and it was equivalent for the two variable location conditions, regardless of the perceptual demands. Larger effects of learning were observed in the central location, both on the indirect measures and on the measures taken from a cued-generation task. The expression of learning decreased selectively in this condition when the sequence validity was reduced over a test block. These results are consistent with the claims that implicit and explicit learning are mixed in this central condition and that implicit learning is not affected by selection difficulty.     

Implicit learning of a speed-contingent target feature

Previous human implicit learning studies have mostly investigated implicit associations between two consecutive stimuli or between a stimulus and the subsequent response (e.g., Cleeremans, Destrebecqz, & Boyer, Trends in Cognitive Sciences, 2(10), 406–416, 1998). In the present study, participants’ response speed was used as a cue to predict an upcoming target feature. We called this new type of cueing, “cueing-by-response” (CBR). We investigated whether CBR could be learned implicitly. Participants performed two tasks: participants quickly responded to a target in the simple detection task and determined the orientation of a new target in the consecutive visual search task. We applied a contingency that the target location in the visual search task was determined by the participant’s response speed in the preceding simple detection task. The results demonstrated that participants learned the contingency without conscious awareness; they searched for the target more efficiently in the visual search task as the experiment progressed. But when the target appeared in a random location, this efficiency disappeared. Moreover, the experimental group exhibited faster response speeds to the target in the visual search task compared with the control groups, which had no contingency. These results suggest that individuals may use the relative speed of their own response as a predictive cue to guide spatial attention toward upcoming target locations, and CBR can be implicitly learned.     

Implicit learning: Below the subjective threshold

In this review, we consider three possible criteria by which knowledge might be regarded as implicit or inaccessible: It might be implicit only in the sense that it is difficult to articulate freely, or it might be implicit according to either an objective threshold or a subjective threshold. We evaluate evidence for these criteria in relation to artificial grammar learning, the control of complex systems, and sequence learning, respectively. We argue that the convincing evidence is not yet in, but construing the implicit nature of implicit learning in terms of a subjective threshold is most likely to prove fruitful for future research. Furthermore, the subjective threshold criterion may demarcate qualitatively different types of knowledge. We argue that (1) implicit, rather than explicit, knowledge is often relatively inflexible in transfer to different domains, (2) implicit, rather than explicit, learning occurs when attention is focused on specific items and not underlying rules, and (3) implicit learning and the resulting knowledge are often relatively robust.     

Implicit learning: Indirect, not unconscious

Dienes and Berry (1997) argue that there really are two kinds of knowledge, implicit and explicit, that can be characterized through a subjective threshold. We argue that the subjective threshold does not separate two forms of knowledge, but instead two uses of knowledge, for two different purposes. With Neal and Hesketh (1997), we suggest that an understanding of learning will be better served by investigating the processing that occurs under various circumstances than by attempting to isolate learning that occurs with awareness from that which occurs without it.     

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.     

Implicit and explicit processes in a second-language learning task

Abstract

Two experiments examined the learning of a set of Greek pronunciation rules through explicit and implicit modes of rule presentation. Experiment 1 compared the effectiveness of implicit and explicit modes of presentation in two modalities, visual and auditory. Subjects in the explicit or rule group were presented with the rule set, and those in the implicit or natural group were shown a set of Greek words, composed of letters from the rule set, linked to their pronunciations. Subjects learned the Greek words to criterion and were then given a series of tests which aimed to tap different types of knowledge. The results showed an advantage of explicit study of the rules. In addition, an interaction was found between mode of presentation and modality. Explicit instruction was more effective in the visual than in the auditory modality, whereas there was no modality effect for implicit instruction. Experiment 2 examined a possible reason for the advantage of the rule groups by comparing different combinations of explicit and implicit presentation in the study and learning phases. The results suggested that explicit presentation of the rules is only beneficial when it is followed by practice at applying them.     

Progression-regression effects in tracking repeated patterns

Subjects used a position control system to perform compensatory tracking of a repeated input pattern. Tracking error was roughly proportional to the velocity of the input signal. Error magnitude decreased with practice and increased with the addition of a concurrent memory task. These effects can be modeled as progressive and regressive changes in how well subjects used control movement velocity and displayed error velocity to anticipate the input pattern and thereby reduce their effective time delay. The weighting of velocity cues in this model progressed with practice and regressed with the secondary task, even though the secondary task required no concurrent visual scanning or simultaneous motor response. This regression effect appears to indicate cognitive interference with the anticipation process. Stationary linear models provide a good approximation to the movement patterns; however, these models do not account for episodes of rapid pulse-like movements that were revealed in the ensemble-averaged trajectories.     

Implicit learning of a recursive rule in an artificial grammar

Participants performed an artificial grammar learning task, in which the standard finite state grammar (J. Verb. Learn. Verb. Behavior 6 (1967) 855) was extended with a recursive rule generating self-embedded sequences. We studied the learnability of such a rule in two experiments. The results verify the general hypothesis that recursivity can be learned in an artificial grammar learning task. However this learning seems to be rather based on recognising chunks than on abstract rule induction. First, performance was better for strings with more than one level of self-embedding in the sequence, uncovering more clearly the self-embedding pattern. Second, the infinite repeatability of the recursive rule application was not spontaneously induced from the training, but it was when an additional cue about this possibility was given. Finally, participants were able to verbalise their knowledge of the fragments making up the sequences-especially in the crucial front and back positions-, whereas knowledge of the underlying structure, to the extent it was acquired, was not articulatable. The results are discussed in relation to previous studies on the implicit learnability of complex and abstract rules.     

Implicit learning of social predictions

Humans exchange a range of nonverbal social signals in every interaction. It is an open question whether people use these signals, consciously or unconsciously, to guide social behavior. This experiment directly tested whether participants could learn to predict another person’s behavior using nonverbal cues in a single interaction, and whether explicit knowledge of the cue-outcome relationship was necessary for successful prediction. Participants played a computerized game of rock-paper-scissors against an avatar they believed was another participant. Sometimes the avatar generated a predictive facial cue before the play. On these trials, participants’ win-frequency increased over time, even if they did not acquire explicit knowledge of the predictive cue. The degree to which participants could predict the avatar (wins on cued trials) related to their self-reported liking of the avatar. These findings demonstrate the importance of implicit associative learning mechanisms in guiding social behavior on a moment-to-moment basis during interaction.     

Implicit visual learning and the expression of learning

Although the existence of implicit motor learning is now widely accepted, the findings concerning perceptual implicit learning are ambiguous. Some researchers have observed perceptual learning whereas other authors have not. The review of the literature provides different reasons to explain this ambiguous picture, such as differences in the underlying learning processes, selective attention, or differences in the difficulty to express this knowledge. In three experiments, we investigated implicit visual learning within the original serial reaction time task. We used different response devices (keyboard vs. mouse) in order to manipulate selective attention towards response dimensions. Results showed that visual and motor sequence learning differed in terms of RT-benefits, but not in terms of the amount of knowledge assessed after training. Furthermore, visual sequence learning was modulated by selective attention. However, the findings of all three experiments suggest that selective attention did not alter implicit but rather explicit learning processes.     

Implicit learning: Robustness in the face of psychiatric disorders

The performance of a group of psychiatric inpatients on two different cognitive tasks was compared with that of a control group of college undergraduates. The task in the first experiment was implicit learning of a complex, synthetic grammar; the task in the second experiment was explicit learning of relatively simple letter-to-number matching rules. In the first experiment, differences between the normals and the psychiatrically impaired were found on the preliminary memorization task but not on the implicit grammar learning task; in the second experiment, differences were observed on all phases of the experiment, with the inpatients performing no better than chance. These findings provide support for the hypothesis that, under appropriate conditions, individuals suffering from serious disorders may show no deficits when working with complex and abstract stimulus domains while showing serious performance problems when working with relatively simple, concrete stimuli. The key factor is that the former were presented as tasks that tap nonreflective, implicit processes, whereas the latter were put forward as ones that recruit conscious, explicit processes.The experiments are based in part on studies reported in Abrams (1987). Preparation of this article was supported in part by a grant from the City University of New York PSC-CUNY Research Award Program, Brooklyn College of CUNY.     

Implicit learning and statistical learning: one phenomenon, two approaches

The domain-general learning mechanisms elicited in incidental learning situations are of potential interest in many research fields, including language acquisition, object knowledge formation and motor learning. They have been the focus of studies on implicit learning for nearly 40 years. Stemming from a different research tradition, studies on statistical learning carried out in the past 10 years after the seminal studies by Saffran and collaborators, appear to be closely related, and the similarity between the two approaches is strengthened further by their recent evolution. However, implicit learning and statistical learning research favor different interpretations, focusing on the formation of chunks and statistical computations, respectively. We examine these differing approaches and suggest that this divergence opens up a major theoretical challenge for future studies.