Pushing the limits of imagination: mental practice for learning sequences

In 2 experiments, the efficacy of motor imagery for learning to type number sequences was examined. Adults practiced typing 4-digit numbers. Then, during subsequent training, they either typed in the same or a different location, imagined typing, merely looked at each number, or performed an irrelevant task. Repetition priming (faster responses for old relative to new numbers) was observed on an immediate test and after a 3-month delay for participants who imagined typing. Improvement across the delay in typing old and new numbers was found for the imagined and actual typing conditions but not for the other conditions. The findings suggest that imagery can be used to acquire and retain representations of sequences and to improve general typing skill.     

Syntactic transfer in artificial grammar learning

In an artificial grammar learning (AGL) experiment, participants were trained with instances of one grammatical structure before completing a test phase in which they were required to discriminate grammatical from randomly created strings. Importantly, the underlying structure used to generate test strings was different from that used to generate the training strings. Despite the fact that grammatical training strings were more similar to nongrammatical test strings than they were to grammatical test strings, this manipulation resulted in a positive transfer effect, as compared with controls trained with nongrammatical strings. It is suggested that training with grammatical strings leads to an appreciation of set variance that aids the detection of grammatical test strings in AGL tasks. The analysis presented demonstrates that it is useful to conceptualize test performance in AGL as a form of unsupervised category learning.     

Effector-independent and effector-dependent sequence representations underlie general and specific perceptuomotor sequence learning

Perceptuomotor sequence learning could be due to learning of effector-independent sequence information (e.g., response locations), effector-dependent information (e.g., motor movements of a particular effector), or both. Evidence also suggests that learning of statistical regularities in sequences (general-regularity learning) and specific sequences (specific-sequence learning) are dissociable. The authors examined the degree to which general and specific-sequence learning rely on effector-independent and effector-dependent representations. During training, participants typed sequences that followed a construction rule with a subset of sequences repeatedly processed. At test, effector-independent and effector-dependent learning was examined with respect to general-regularity and specific-sequence learning. Results suggest that general-regularity learning is subserved by effector-independent sequence representations, whereas specific-sequence learning is subserved by effector-dependent sequence representations, further dissociating these types of learning.     

New strings for old: The role of similarity processing in an incidental learning task

This paper reports three experiments that examine the role of similarity processing in McGeorge and Burton's (1990) incidental learning task. In the experiments subjects performed a distractor task involving four-digit number strings, all of which conformed to a simple hidden rule. They were then given a forced-choice memory test in which they were presented with pairs of strings and were led to believe that one string of each pair had appeared in the prior learning phase. Although this was not the case, one string of each pair did conform to the hidden rule. Experiment 1 showed that, as in the McGeorge and Burton study, subjects were significantly more likely to select test strings that conformed to the hidden rule. However, additional analyses suggested that rather than having implicitly abstracted the rule, subjects may have been selecting strings that were in some way similar to those seen during the learning phase. Experiments 2 and 3 were designed to try to separate out effects due to similarity from those due to implicit rule abstraction. It was found that the results were more consistent with a similarity-based model than implicit rule abstraction per se.     

The subliminal mere exposure effect does not generalize to structurally related stimuli.

R.F. Bornstein (1994) questioned whether subliminal mere exposure effects might generalize to structurally related stimuli, thereby providing evidence for the existence of implicit learning. Two experiments examined this claim using letter string stimuli constructed according to the rules of an artificial grammar. Experiment 1 demonstrated that brief, masked exposure to grammatical strings impaired recognition but failed to produce a mere exposure effect on novel structurally related strings seen at test. Experiment 2 replicated this result but also demonstrated that a reliable mere exposure effect could be obtained, provided the same grammatical strings were presented at test. The results suggest that the structural relationship between training and test items prevents the mere exposure effect when participants are unaware of the exposure status of stimuli, and therefore provide no evidence for the existence of implicit learning.     

先前知识经验对远距离水平映射规则内隐学习的限制

先前研究发现远距离规则能够被内隐地习得和迁移,表明内隐学习获得的知识是底层的抽象规则,那么这一抽象规则的习得和迁移是否会受到先前知识经验的限制?研究采用汉语声调的远距离水平映射规则为材料,通过创设不符合平仄知识经验的任意声调水平映射规则,在控制组块和重复结构等表面特征的条件下,探讨先前知识经验是否限制了远距离水平映射规则的内隐学习和迁移。结果发现相对于符合平仄知识经验的汉语声调水平映射规则,被试不能够内隐地习得和迁移任意声调的水平映射规则,表明先前知识经验在远距离水平映射规则内隐学习过程中发挥着重要作用。     

Prior familiarity with components enhances unconscious learning of relations

The influence of prior familiarity with components on the implicit learning of relations was examined using artificial grammar learning. Prior to training on grammar strings, participants were familiarised with either the novel symbols used to construct the strings or with irrelevant geometric shapes. Participants familiarised with the relevant symbols showed greater accuracy when judging the correctness of new grammar strings. Familiarity with elemental components did not increase conscious awareness of the basis for discriminations (structural knowledge) but increased accuracy even in its absence. The subjective familiarity of test strings predicted grammaticality judgments. However, prior exposure to relevant symbols did not increase overall test string familiarity or reliance on familiarity when making grammaticality judgments. Familiarity with the symbols increased the learning of relations between them (bigrams and trigrams) thus resulting in greater familiarity for grammatical versus ungrammatical strings. The results have important implications for models of implicit learning.     

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.     

Information theory and artificial grammar learning: inferring grammaticality from redundancy

In artificial grammar learning experiments, participants study strings of letters constructed using a grammar and then sort novel grammatical test exemplars from novel ungrammatical ones. The ability to distinguish grammatical from ungrammatical strings is often taken as evidence that the participants have induced the rules of the grammar. We show that judgements of grammaticality are predicted by the local redundancy of the test strings, not by grammaticality itself. The prediction holds in a transfer test in which test strings involve different letters than the training strings. Local redundancy is usually confounded with grammaticality in stimuli widely used in the literature. The confounding explains why the ability to distinguish grammatical from ungrammatical strings has popularized the idea that participants have induced the rules of the grammar, when they have not. We discuss the judgement of grammaticality task in terms of attribute substitution and pattern goodness. When asked to judge grammaticality (an inaccessible attribute), participants answer an easier question about pattern goodness (an accessible attribute).     

Memory for noun pairs in the same or different underlying strings

A number of studies have shown that children learn noun pairs faster when they have been presented in a noun-verb-noun context than when they are presented in a noun-conjunction-noun context. Suzuki and Rohwer (1969) hypothesized that the underlying strings of sentences correspond to memory units, making it easier to recall two nouns from the same underlying string than from two different underlying strings. They reported that data from fifth graders supported this hypothesis but that data from college students did not. The experiments reported here were done to determine whether the hypothesis would be supported (a) if the test rate were faster than that used by Suzuki and Rohwer or (b) if sentences longer and more complex than those used by them were employed. The recall data accorded with some predictions derived from the hypothesis. However, data from Ss’ posttraining reports on how they learned the pairs suggest that Ss, particularly adults, often made up their own strings rather than using those provided, and raise the question of the adequacy of Suzuki and Rohwer’s procedure for testing this hypothesis, particularly in adults.     

Typing letter strings varying in orthographic structure

Subjects typed six-letter strings varying in orthographic structure. Lexical status, word frequency, position-sensitive log bigram frequency, and regularity of letter sequencing were systematically varied. Cumulative reaction times (RTs) of the keystrokes were adequately described by a linear function of letter position in the test string. Overall, words were typed faster than nonwords, and regular strings faster than irregular strings. Although the effect of log bigram frequency was not significant, this variable interacted with regularity and word frequency. Post hoc analyses of performance on each of the 200 letter strings revealed significant effects of the number of irregularities, log bigram frequency, and log word frequency. Transition times between successive keystrokes were significantly longer for illegal than for legal letter transitions. These results are similar to previous findings on the role of orthographic structure in the perceptual recognition of letter strings and provide a more complete analysis of context effects in typing.     

Expanding the Intertrial Interval During Extinction: Response Cessation and Recovery

We examined trial spacing during extinction following a human contingency learning task. Specifically, we assessed if an expanding retrieval practice schedule ( [Bjork and Bjork, 1992] and [Bjork and Bjork, 2006]), in which the spacing between extinction trials was progressively increased, would result in faster immediate extinction and less recovery from extinction than uniformly spaced extinction trials. We used an ABB vs. ABA renewal design and observed that, whereas the expanding group extinguished faster during extinction treatment, the expanding and constant groups showed the same level of extinction with an immediate test in the extinction context (ABB) and the two groups showed equivalent ABA renewal at test in the training context. We conclude that the faster extinction observed in the expanding groups could be misleading in clinical treatment, if the therapist used the absence of fear during extinction as the basis for terminating treatment.     

Effector-dependent learning by observation of a finger movement sequence

Can observational learning be effector dependent? In 3 experiments, observers watched a model respond to a 6-item unique sequence in a serial reaction time task. Their sequence knowledge was then compared with that of controls who had performed an unrelated task or observed a model responding to random targets. Observational learning was indicated when the introduction of a new sequence was associated with more reaction time elevation in observers than in controls. The authors found evidence of observational learning only when observers used the finger movement sequence that they observed during training, not when they responded at the same sequence of locations using different digits. Free generation and recognition tests also detected observational learning. These results imply that observational learning can be both explicit and effector dependent.     

Intentional control based on familiarity in artificial grammar learning

It is commonly held that implicit learning is based largely on familiarity. It is also commonly held that familiarity is not affected by intentions. It follows that people should not be able to use familiarity to distinguish strings from two different implicitly learned grammars. In two experiments, subjects were trained on two grammars and then asked to endorse strings from only one of the grammars. Subjects also rated how familiar each string felt and reported whether or not they used familiarity to make their grammaticality judgment. We found subjects could endorse the strings of just one grammar and ignore the strings from the other. Importantly, when subjects said they were using familiarity, the rated familiarity for test strings consistent with their chosen grammar was greater than that for strings from the other grammar. Familiarity, subjectively defined, is sensitive to intentions and can play a key role in strategic control.     

Implicit Learning and Concept Learning

In Experiments 1 and 2, subjects were exposed to letter strings that followed a pattern—the second letter was always the same. This exposure was disguised as a test of immediate memory. Following this training, subjects could discriminate new letter strings following the pattern from letter strings not following the pattern more often than would be expected by chance, which is the traditional evidence for concept learning. Discrimination was also better than would be predicted from subjects' explicit report of the pattern, demonstrating the co-occurrence of concept learning and implicit learning. In Experiment 3, rules were learned explicitly. Discrimination was worse than would be predicted from subjects' explicit report, validating the implicit learning paradigm. In Experiment 4, deviations from a prototypical pattern were presented during training. In the test of discrimination, prototypes were as familiar as old deviations and more familiar than new deviations, even when considering only implicit knowledge. Experiment 5 found implicit knowledge of a familiar concept. These results are consistent with the hypothesis that the distinguishing features of a concept can be learned implicitly, and that one type of implicit learning is concept learning.     

Abstraction Processes in Artificial Grammar Learning

Four experiments explored the extent to which abstract knowledge may underlie subjects' performance when asked to judge the grammaticality of letter strings generated from an artificial grammar. In Experiments 1 and 2 subjects studied grammatical strings instantiated with one set of letters and were then tested on grammatical and ungrammatical strings formed either from the same or a changedletter-set.Evenwith a change ofletter-set, subjects were found to be sensitive to a variety of violations of the grammar. In Experiments 3 and 4, the critical manipulation involved the way in which the training strings were studied: an incidental learning procedure was used for some subjects, and others engaged in an explicit code-breaking task to try to learn the rules of the grammar. When strings were generated from a biconditional (Experiment 4) but not from a standard finite-state grammar (Experiment 3), grammaticality judgements for test strings were independent of their surface similarity to specific studied strings. Overall, the results suggest that transfer in this simple memory task is mediated at least to some extent by abstract knowledge.     

Beyond dissociation logic: evidence for controlled and automatic influences in artificial grammar learning

Evidence for unconscious learning has typically been based on dissociations between direct and indirect tests of learning. Because of some inherent problems with dissociation logic, we applied the logic of opposition to 2 artificial grammar learning experiments. In Experiment 1, participants were exposed to 2 different sets of letter strings, generated from 2 different grammars, and later rated test strings for grammaticality with either in-concert (rate grammatical strings consistent with either structure) or opposition (rate grammatical only strings from 1 of the structures) instructions. Manipulating response deadline affected controlled, but not automatic influences. In Experiment 2, after similar training, a source-monitoring test was administered from which the in-concert and opposition conditions were derived. The test indicated that varying the retention interval affected controlled, but not automatic, influences. The results are discussed in terms of awareness, knowledge representation, and metacognitive processing.     

Sequential learning and rule abstraction in Bengalese finches

The Bengalese finch (Lonchura striata var. domestica) is a species of songbird. Males sing courtship songs with complex note-to-note transition rules, while females discriminate these songs when choosing their mate. The present study uses serial reaction time (RT) to examine the characteristics of the Bengalese finches’ sequential behaviours beyond song production. The birds were trained to produce the sequence with an “A–B–A” structure. After the RT to each key position was determined to be stable, we tested the acquisition of the trained sequential response by presenting novel and random three-term sequences (random test). We also examined whether they could abstract the embedded rule in the trained sequence and apply it to the novel test sequence (abstract test). Additionally, we examined rule abstraction through example training by increasing the number of examples in baseline training from 1 to 5. When considered as (gender) groups, training with 5 examples resulted in no statistically significant differences in the abstract tests, while statistically significant differences were observed in the random tests, suggesting that the male birds learned the trained sequences and transferred the abstract structure they had learned during the training trials. Individual data indicated that males, as opposed to females, were likely to learn the motor pattern of the sequence. The results are consistent with observations that males learn to produce songs with complex sequential rules, whereas females do not.     

Implicit learning of conjunctive rule sets: An alternative to artificial grammars

A single experiment is reported that investigated implicit learning using a conjunctive rule set applied to natural words. Participants memorized a training list consisting of words that were either rare-concrete and common-abstract or common-concrete and rare-abstract. At test, they were told of the rule set, but not told what it was. Instead, they were shown all four word types and asked to classify words as rule-consistent words or not. Participants classified the items above chance, but were unable to verbalize the rules, even when shown a list that included the categories that made up the conjunctive rule and asked to select them. Most participants identified familiarity as the reason for classifying the items as they did. An analysis of the materials demonstrated that conscious micro-rules (i.e., chunk knowledge) could not have driven performance. We propose that such materials offer an alternative to artificial grammar for studies of implicit learning.     

Connectionist and Memory-Array Models of Artificial Grammar Learning

Subjects exposed to strings of letters generated by a finite state grammar can later classify grammatical and nongrammatical test strings, even though they cannot adequately say what the rules of the grammar are (e.g., Reber, 1989). The MINERVA 2 (Hintzman, 1986) and Medin and Schaffer (1978) memory-array models and a number of connectionist outoassociator models are tested against experimental data by deriving mainly parameter-free predictions from the models of the rank order of classification difficulty of test strings. The importance of different assumptions regarding the coding of features (How should the absence of a feature be coded? Should single letters or digrams be coded?), the learning rule used (Hebb rule vs. delta rule), and the connectivity (Should features be predicted only by previous features in the string, or by all features simultaneously?) is investigated by determining the performance of the models with and without each assumption. Only one class of connectionist model (the simultaneous delta rule) passes all the tests. It is shown that this class of model can be regarded by abstracting a set of representative but incomplete rules of the grammar.