Contextual interference in implicit and explicit motor learning

The purposes of this study were to examine the contextual interference effect in implicit learning and to compare implicit and explicit learning. Thirty-two participants performed a pursuit-tracking task for 60 acquisition and ten retention trials. The middle segment of target pathways had only two patterns whereas other segments had random patterns. A combination of awareness and practice order for the middle segment created four acquisition conditions: implicit-blocked, implicit-serial, explicit-blocked and explicit-serial. A questionnaire and a recognition test revealed that implicit groups were unaware of the repetition. Results showed no contextual interference effect in either implicit or explicit learning. Acquisition and retention performances were better for the middle segment than the other segments regardless of awareness. No difference between the implicit and explicit groups was found, suggesting that the implicit learning condition led to learning equivalent to the explicit learning condition.     

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.     

Effects of aging on implicit sequence learning: Accounting for sequence structure and explicit knowledge

The present research was intended to examine the sequence learning ability of elderly people — with a focus on comparing sequences with different structural characteristics and on properly assessing explicit knowledge. Experiment 1 showed that learning-related improvements in serial reaction time task performance were greater for young than elderly subjects, and elderly subjects were especially poor at learning a sequence with complex structural characteristics. Measures of recognition memory showed that neither young nor elderly subjects showed above-chance explicit knowledge of the sequences. Experiment 2 was designed to test the validity and sensitivity of the explicit recognition measures by comparing young subjects in groups given all random trials, given sequence trials with implicit instructions, or given sequence trials with explicit instructions. Experiment 2 confirmed the sensitivity of the recognition measures to explicit knowledge, so it is concluded that group effects in Exp. 1 reflect age-related differences in implicit learning.     

The role of working memory capacity in implicit and explicit sequence learning of children: Differentiating movement speed and accuracy

This study investigated the role of working memory capacity on implicit and explicit motor sequence learning in young children. To this end, a task was utilized that required a gross motor response (flexing the elbow) and that could differentiate between movement speed (i.e., reaction time and movement time) and movement accuracy. Children aged 7–9 years practiced a serial reaction time task that involved the production of a fixed sequence of elbow flexions of prescribed magnitude across two consecutive days. Children in the explicit group were informed about the presence of the sequence and were shown this sequence, while children in the implicit group were not made aware of the sequence. Additionally, children's verbal and visuospatial working memory capacity was assessed. Results of day 1 regarding movement speed revealed no evidence of sequence learning for either group, but movement accuracy results suggested that sequence learning occurred for the implicit group. For both groups, only improvements in movement accuracy were consolidated on day 2, indicating both general and sequence specific learning. Working memory capacity did not correlate with learning in either of the groups. Children in the explicit group accumulated more sequence knowledge compared to children in the implicit group, but this knowledge did not translate to more or better sequence learning. The minimal differences found between the implicit and explicit condition and the absence of a role for working memory capacity add to the increasing evidence that the observed differences between implicit and explicit sequence learning in adults may be less distinct in children.     

Distinguishing implicit and explicit learning

I agree with Dienes and Berry’s (1997) and Neal and Hesketh’s (1997) call for investigations of the qualitative differences between implicit and explicit learning and note that such investigations must be guided by a workable definition of what is implicit and by theories that predict what the qualitative differences might be. Following Schacter, Bowers, and Booker’s (1989) retrieval intentionality criterion, I propose using anencoding intentionality criterion to distinguish implicit from explicit learning; we can reasonably infer that implicit learning has occurred when a variable known to influence explicit learning has no effect in a comparable implicit learning condition. I then suggest that implicit learning depends on noncognitive, nonhierarchical associations, whereas explicit learning depends on cognitive, hierarchical associations, and briefly describe an experiment that confirms a qualitative difference between implicit and explicit learning predicted by this hypothesis.     

Auditory priming: implicit and explicit memory for words and voices.

Five experiments explore priming effects on auditory identification and completion tasks as a function of semantic and nonsemantic encoding tasks and whether speaker's voice is same or different at study and test. Auditory priming was either unaffected by the study task manipulation (Experiments 2, 4, and 5) or was less affected than was explicit memory (Experiments 1 and 3). Study-to-test changes of speaker's voice had nonsignificant effects on priming when white noise masked target items on the identification test (Experiments 1 and 2) or the stem-completion test (Experiment 5). However, significant voice change effects were observed on priming of completion performance when stems were spoken clearly (Experiments 3 and 4). Results are consistent with the idea that a presemantic auditory perceptual representation system plays an important role in the observed priming. Alternative explanations of the presence or absence of voice change effects under different task conditions are considered.     

The impact of response mode on implicit and explicit sequence learning

Evidence regarding the influence of response mode on sequence learning in serial reaction time (SRT) tasks has been mixed so far. In the present study, sequence learning was investigated under two different response conditions: manual (button presses) versus verbal (pronunciation of digits). Additionally, participants were divided post hoc into subgroups differing in their degree of explicit knowledge about the sequence. Results showed an interaction between response mode and type of learning (implicit vs. explicit), with explicit learning functioning more effectively under verbal than under manual conditions, whereas implicit learning was unaffected by the variation of the response mode. Implications concerning different underlying learning mechanisms (R-R learning vs. R-S learning) are discussed. Specifically, we suggest that the high response-effect distinctiveness of the verbal responses facilitated R-R learning.     

Obtaining separate measures for implicit and explicit memory

In this paper a new model, the Implicit/Explicit Separation (IES) model, is developed and applied. The model is designed to obtain separate probability measures for explicit memory storage, implicit memory storage, fractional storage, and non-storage. The model is needed because memory research has shown the importance of the distinction between a conscious memory of a target event and a memory residue that is unable to support conscious recall or confident recognition, but it is still able to support guessing at rates above chance. Maximum likelihood and population-parameter mapping estimates for the parameters of the IES model are provided. The accuracy of parameter estimates is studied as a function of sample size. Three experiments are reported to demonstrate how the IES model is used to achieve a more fine grained assessment of the quality of information storage. These experiments also provide strong validation support for the IES model itself. Across the three experiments, each of the four components for representing target information (explicit, implicit, fractional, and non-storage) demonstrates a different pattern. The IES model is discussed in terms of alternative models such as the dual-process model and the process-dissociation model.     

Providing explicit information disrupts implicit motor learning after basal ganglia stroke

Despite their purported neuroanatomic and functional isolation, empirical evidence suggests that sometimes conscious explicit processes can influence implicit motor skill learning. Our goal was to determine if the provision of explicit information affected implicit motor-sequence learning after damage to the basal ganglia. Individuals with stroke affecting the basal ganglia (BG) and healthy controls (HC) practiced a continuous implicit motor-sequencing task; half were provided with explicit information (EI) and half were not (No-EI). The focus of brain damage for both BG groups was in the putamen. All of the EI participants were at least explicitly aware of the repeating sequence. Across three days of practice, explicit information had a differential effect on the groups. Explicit information disrupted acquisition performance in participants with basal ganglia stroke but not healthy controls. By retention (day 4), a dissociation was apparent--explicit information hindered implicit learning in participants with basal ganglia lesions but aided healthy controls. It appears that after basal ganglia stroke explicit information is less helpful in the development of the motor plan than is discovering a motor solution using the implicit system alone. This may be due to the increased demand placed on working memory by explicit information. Thus, basal ganglia integrity may be a crucial factor in determining the efficacy of explicit information for implicit motor-sequence learning.     

Eliciting false memories on implicit and explicit memory tests after incidental learning

Abstract: In a false memory experiment, lists of semantic associates (e.g., newspaper, letter, book, etc.) were presented to three groups of participants to induce false memories for critical nonpresented (CN) words (e.g., read) in an incidental learning task. The control group simply estimated the frequency rate in everyday Japanese discourse of each word on a list. The imagery instruction group received an additional instruction to imagine a thematically related converging word from the target words on a list. Participants in the imagery plus writing group received the same instructions as those in the imagery instruction group, but were also required to write down the word they imagined for each list. The results from the implicit and explicit memory tests given after the incidental learning episode showed that the level of priming for CN words was equivalent to that for actually presented target words for all three groups on the implicit test, whereas explicit memory results showed that participants explicitly recognized more target words than CN words. The implications for implicit associative response and fuzzy‐trace theories of false memory, as well as implicit priming, are discussed.     

Explicit and implicit motor sequence learning in children and adults; the role of age and visual working memory

This study investigated explicit and implicit motor learning, and the influence of visual working memory (VWM) and age. Sixty children and 28 adults learned a nine-button sequence task explicitly and implicitly. Performance in explicit and implicit learning improved with age. Learning curves were similar across ages for implicit learning. In explicit learning, learning curves differed across ages: younger children started slower, but their learning rate was higher compared to older children. Learning curves were similar across VWM scores, but performance in explicit learning was positively influenced by VWM scores. Further research and implications for education and rehabilitation are discussed.     

An egocentric frame of reference in implicit motor sequence learning

We investigated which frame of reference is evoked during implicit motor sequence learning. Participants completed a typical serial reaction time task. In the first experiment, we isolated egocentric and allocentric frames of reference and found that learning was solely in an egocentric reference frame. In a second experiment, we isolated hand-centered space from other egocentric frames of reference. We found that for a one-handed sequencing task, the sequence was coded in an egocentric reference frame but not a hand-centered reference frame. Our results are restricted to implicit learning of novel sequences in the early stages of learning. These findings are consistent with claims that the neural mechanisms involved in motor skill learning operate in egocentric coordinates.     

Input- and output-monitoring in implicit and explicit memory

Previous experiments have shown that the procedure of questioning subjects retrospectively about the input and output status of information (input and output monitoring) is a useful method for assessing the awareness states of subjects during implicit and explicit memory tasks. The main purpose of the present study was to investigate whether the previous findings could be extended to other implicit and explicit memory tasks. We were especially interested in whether differences in input- and output-monitoring performance can be observed when both the implicit and explicit memory tasks are conceptual ones. In a final test phase, the target items from the study phase and new distractor items were presented. In a recognition-like situation, subjects had to decide whether an item had been presented in the study phase (input status), as well as whether they had produced the item in the memory-test phase (output status). In all three experiments judgments about the input status - but only for those items that had been produced in the implicit or in the explicit memory test - were more precise after explicit than after implicit memory testings. This finding was not influenced by the distinction between perceptual and conceptual-memory tasks (Exp. 1), and was obtained under conditions in which the implicit and the explicit memory tasks were both conceptual and differed only in test instructions (Exps. 2 and 3). These results suggest that not only subjects performing a perceptual test of implicit memory, but also subjects in a conceptual implicit test were less aware of using information from a previous study episode than subjects who received memory instructions. It is concluded that requiring judgments about the input status of information is a good method for assessing subjects test awareness and is preferable to the use of a questionnaire (Exp. 3). In contrast, in all three experiments no differences were found with the output-monitoring measure between implicit and explicit test conditions.     

Context-dependence of implicit and explicit memory characteristics

The present experiments explore whether repetition priming in a word-stem completion task is context-dependent. In the first experiment, the environmental context was changed or remained constant at the testing stage. Implicit memory performance did not reveal any effects of environmental context. When tested by free recall, however, the same subjects showed an environmental congruency effect. On the other hand, effects of a change in presentation modality were restricted to implicit memory measures. In the second experiment, self-awareness was manipulated to create congruent or incongruent internal contexts at the testing stage. Performance on the word-stem completion task was seen to be influenced by internal contextual information. This pattern of results corroborates a processing account of implicit memory phenomena. Implicit and explicit expressions of memory utilize episodic information, but in a different way.     

Elaboration effects in implicit and explicit memory tests

Dissociation effects in explicit and implicit tests of memory were examined in two experiments. In Experiment 1 serial-position effects were studied. Results showed that the standard primacy effect found in free recall is absent in an implicit word-stem completion test. In Experiment 2 a dissociation was found for the effect of high- and low-frequency words in free recall and word-stem completion tests. Both findings are explained in terms of a modified and extended version of the activation-elaboration learning account, which was inspired by attempts to simulate dissociation effects in connectionist models. The relationship between this account and two other leading accounts of dissociation effects in implicit and explicit memory is discussed, and a model to integrate aspects of all three accounts is suggested.     

Gender differences in implicit and explicit memory for affective passages

Thirty-two participants were administered 4 verbal tasks, an Implicit Affective Task, an Implicit Neutral Task, an Explicit Affective Task, and an Explicit Neutral Task. For the Implicit Tasks, participants were timed while reading passages aloud as quickly as possible, but not so quickly that they did not understand. A target verbal passage was repeated three times, and alternated with other previously unread passages. The Implicit Affective and Neutral passages had strong affective or neutral content, respectively. The Explicit Tasks were administered at the end of testing, and consisted of multiple choice questions regarding the passages. Priming effects in terms of more rapid reading speed for the target compared to non-target passages were seen for both the Implicit Affective Task and the Implicit Neutral Task. Overall reading speed was faster for the passages with neutral compared to affective content, consistent with studies of the emotional Stroop effect. For the Explicit memory tasks, overall performance was better on the items from the repeated passage, and on the Affective compared to Neutral Task. The male subjects showed greater priming for affective material than female subjects, and a greater gain than female subjects in explicit memory for affective compared to neutral material.     

Psychometric intelligence dissociates implicit and explicit learning

The hypothesis that performance on implicit learning tasks is unrelated to psychometric intelligence was examined in a sample of 605 German pupils. Performance in artificial grammar learning, process control, and serial learning did not correlate with various measures of intelligence when participants were given standard implicit instructions. Under an explicit rule discovery instruction, however, a significant relationship between performance on the learning tasks and intelligence appeared. This finding provides support for Reber's hypothesis that implicit learning, in contrast to explicit learning, is independent of intelligence, and confirms thereby the distinction between the 2 modes of learning. However, because there were virtually no correlations among the 3 learning tasks, the assumption of a unitary ability of implicit learning was not supported.     

Effects of learning contexts on implicit and explicit learning

Two parallel tasks involving rule learning were identified in Experiment 1A and were used to assess implicit and explicit learning. In both tasks, subjects had to input numbers in order to reach the target values of outputs. The relationship between inputs and outputs was either simple (in the simple task) or complex (in the complex task), and the way in which target values were presented could be in the form of either numbers (in the simple task) or lines (in the complex task). Experiment 1B examined the validity of the explicit measure in the complex task. Experiments 2–4 investigated the interaction between learning contexts and the simple/complex learning tasks. Verbalization and instructions to search for the rules facilitated the simple-task learning and hurt or have no effect on the complex-task learning. In the observational-learning condition, no learning occurred for the simple task, and the complex task learning was impaired. These results suggest that the complex task and simple task involve two distinct learning systems. Other implications are also discussed.