Collaboration facilitates abstract category learning

We examined the effects of collaboration (dyads vs. individuals) and category structure (coherent vs. incoherent) on learning and transfer. Working in dyads or individually, participants classified examples from either an abstract coherent category, the features of which are not fixed but relate in a meaningful way, or an incoherent category, the features of which do not relate meaningfully. All participants were then tested individually. We hypothesized that dyads would benefit more from classifying the coherent category structure because past work has shown that collaboration is more beneficial for tasks that build on shared prior knowledge and provide opportunities for explanation and abstraction. Results showed that dyads improved more than individuals during the classification task regardless of category coherence, but learning in a dyad improved inference-test performance only for participants who learned coherent categories. Although participants in the coherent categories performed better on a transfer test, there was no effect of collaboration.     

Implicit learning of musical timbre sequences: statistical regularities confronted with acoustical (dis)similarities

The present study investigated the influence of acoustical characteristics on the implicit learning of statistical regularities (transition probabilities) in sequences of musical timbres. The sequences were constructed in such a way that the acoustical dissimilarities between timbres potentially created segmentations that either supported (S1) or contradicted (S2) the statistical regularities or were neutral (S3). In the learning group, participants first listened to the continuous timbre sequence and then had to distinguish statistical units from new units. In comparison to a control group without the exposition phase, no interaction between sequence type and amount of learning was observed: Performance increased by the same amount for the three sequences. In addition, performance reflected an overall preference for acoustically similar timbre units. The present outcome extends previous data from the domain of implicit learning to complex nonverbal auditory material. It further suggests that listeners become sensitive to statistical regularities despite acoustical characteristics in the material that potentially affect grouping.     

Perceptual learning in visual category acquisition

The attribute structure of a set of dot patterns was studied by having subjects segment (parse) the dots of each pattern into parts or subunits by drawing circles around groups of dots from each pattern. These parsing data were obtained for subjects who had no prior experience with the patterns and for subjects who had previously learned to identify the patterns as members of one of four categories. Analyses of the parsing data indicated that category learning increased the salience of large subunits that were similar in orientation for patterns that were members of the same category. This evidence for perceptual learning was obtained even when the category training procedure required learning to identify the patterns individually, suggesting that attribute abstraction and item learning are not incompatible. It was also obtained without an increase in overall intersubject agreement. The latter result led us to question the usefulness of intersubject agreement as an index of category knowledge.     

Implicit learning out of the lab: the case of orthographic regularities

Children's (Grades 1 to 5) implicit learning of French orthographic regularities was investigated through nonword judgment (Experiments 1 and 2) and completion (Experiments 3a and 3b) tasks. Children were increasingly sensitive to (a) the frequency of double consonants (Experiments 1, 2, and 3a), (b) the fact that vowels can never be doubled (Experiment 2), and (c) the legal position of double consonants (Experiments 2 and 3b). The latter effect transferred to never doubled consonants but with a decrement in performance. Moreover, this decrement persisted without any trend toward fading, even after the massive amounts of experience provided by years of practice. This result runs against the idea that transfer to novel material is indicative of abstract rule-based knowledge and suggests instead the action of mechanisms sensitive to the statistical properties of the material. A connectionist model is proposed as an instantiation of such mechanisms.     

Implicit learning of sequences of tasks

Task sets can be configured in advance of performing a new task. However, the degree to which advance information is actually used for advance configuration depends on the nature of the available information. The role of implicit learning was explored in 2 experiments by means of a modified serial reaction time task with repeated sequences of 4 dimensionally organized tasks. Although there was clear evidence for implicit learning of the sequence (of length 8), the learning was not associated with a reduction of shift costs, either with a short (200 ms) or with a long (1,200 ms) response-stimulus interval. In contrast, a reduction of shift costs was observed when external precues were introduced in a 3rd experiment. According to these results, the sequences of stimulus features that serve as cues for the tasks to perform on the stimuli are learned, but the representation of the features is void of their task-associated meanings.     

The acquisition of category structure in unsupervised learning

Four experiments examined the extent to which prior knowledge influences the acquisition of category structure in unsupervised learning conditions. Prior knowledge is general knowledge about a broad domain that explains why an object has the features it does. Category structure refers to the statistical regularities of features within and across categories. Subjects viewed items and then divided them up into the categories that seemed most natural. Each item had one feature that was related to prior knowledge and five features that were not. The results showed that even this small amount of prior knowledge helped subjects to discover the category structure. In addition, prior knowledge enhanced the learning of many of the category's features, and not just the features that were directly relevant to the knowledge. The results suggest that prior knowledge may help to integrate the features of a category, thereby improving the acquisition of category structure.     

Implicit learning of fifth- and sixth-order sequential probabilities

Serial reaction time (SRT) task studies have established that people can implicitly learn sequential contingencies as complex as fourth-order probabilities. The present study examined people’s ability to learn fifth-order (Experiment 1) and sixth-order (Experiment 2) probabilities. Remarkably, people learned fifth- and sixth-order probabilities. This suggests that the implicit sequence learning mechanism can operate over a range of at least seven sequence elements.     

Types of semantic category and stimulus modality in procedural learning: implications for models of semantic memory

The present work attempts to determine whether procedural learning of a semantic categorisation task is influenced by the type of semantic category of the stimuli (biological and non-biological elements). It is also an attempt to determine the effect of the stimulus presentation modality on the categorisation task. A semantic categorisation task (4 series of 40 stimuli) was administered to 256 participants (128 classifying pictures, and 128 classifying words). Biological categories were responded to faster than non-biological ones although there were no significant differences between the interaction of the category type and the stimulus presentation modality. Reaction times progressively decreased with practice. However, the initial differences disappeared when subjects were trained. The way that current models account for these investigation findings is discussed. In addition, it is suggested that there is an attentional bias in favor of biological elements, which disappears when presumably less relevant elements become more relevant as a function of the task characteristics.     

Perceptual-motor sequence learning of general regularities and specific sequences.

Participants viewed digit strings and typed them on a computer keyboard. When they used the same key configuration across training and test, they typed test strings that adhered to the same sequence rule as training strings faster than test strings that adhered to the opposite rule (general-regularity [GR] learning), and they typed test strings that were processed repeatedly during training faster than test strings that were not (specific-sequence [SS] learning). However, when they used different key configurations at training and at test, GR learning, but not SS learning, was observed. Conversely, when they did not type but spoke the strings aloud during training, SS learning, but not GR learning, was observed. Results suggest that in addition to declarative memory for specific sequences, relatively independent subsystems underlie procedural learning of perceptual-motor sequence components (producing GR effects) and sequence wholes (producing SS effects).     

Implicit word learning benefits from semantic richness: electrophysiological and behavioral evidence

Words differ considerably in the amount of associated semantic information. Despite the crucial role of meaning in language, it is still unclear whether and how this variability modulates language learning. Here, we provide initial evidence demonstrating that implicit learning in repetition priming is influenced by the amount of semantic features associated with a given word. Electroencephalographic recordings were obtained while participants performed a visual lexical decision task; the complete stimulus set was repeated once. Repetition priming effects on performance accuracy and the N400 component of the event-related brain potential were enhanced for words with many semantic features. These findings suggest a novel and important impact of the richness of semantic representations on learning and plasticity within the lexical-conceptual system; they are discussed in their relevance for assumptions concerning basic mechanisms underlying word learning.     

Implicit learning of semantic preferences of English words by Chinese learners

The aim of the present study was to explore whether Chinese learners could implicitly learn the semantic preferences of novel English words. In training, participants learned four novel verbs and were exposed to a set of verb-noun phrases that included these new words. What the participants were not told was that the use of the verbs depended on the concreteness of the nouns (i.e., the semantic preference rule). In testing, participants were required to choose between two possible verbs (one of which violated the semantic preference rule) for nouns that never occurred in training. The results showed that participants acquired unconscious knowledge of semantic preferences under incidental learning conditions, as measured by verbal reports and structural knowledge attributions. Our results provide further evidence for implicit learning of semantic preferences, suggesting that implicit learning is an important mechanism in the acquisition of L2 collocations.     

Implicit learning of higher order sequences in middle age

Previous studies have demonstrated age-related deficits in implicit learning of higher order sequences in comparisons of college-age and elderly adults (e.g., J. H. Howard & D. V. Howard, 1997). This study examined whether these age deficits begin in middle age. Results showed a reliable age-related deficit in pattern sensitivity in "older" compared with "younger" middle-aged people, and age reliably predicted sensitivity to the sequence by using both speed and accuracy measures. The results are consistent with an age-related decline in a generic cognitive resource as reflected in T. A. Salthouse's (1996) simultaneity mechanism of cognitive aging.     

Implicit and explicit category learning by capuchin monkeys (Cebus apella)

Current theories of human categorization differentiate an explicit, rule-based system of category learning from an implicit system that slowly associates regions of perceptual space with response outputs. The researchers extended this theoretical differentiation to the category learning of New World primates. Four capuchins (Cebus apella) learned categories of circular sine-wave gratings that varied in bar spatial frequency and orientation. The rule-based and information-integration tasks, respectively, had one-dimensional and two-dimensional solutions. Capuchins, like humans, strongly dimensionalized the stimuli and learned the rule-based task more easily. The results strengthen the suggestion that nonhuman primates have some structural components of humans' capacity for explicit categorization, which in humans is linked to declarative cognition and consciousness. The results also strengthen the primate contrast to other vertebrate species that may lack the explicit system. Therefore, the results raise important questions about the origins of the explicit categorization system during cognitive evolution and about its overall phylogenetic distribution.     

Implicit statistical learning is directly associated with the acquisition of syntax

This article reports on an individual differences study that investigated the role of implicit statistical learning in the acquisition of syntax in children. One hundred children ages 4 years 5 months through 6 years 11 months completed a test of implicit statistical learning, a test of explicit declarative learning, and standardized tests of verbal and nonverbal ability. They also completed a syntactic priming task, which provided a dynamic index of children's facility to detect and respond to changes in the input frequency of linguistic structure. The results showed that implicit statistical learning ability was directly associated with the long-term maintenance of the primed structure. The results constitute the first empirical demonstration of a direct association between implicit statistical learning and syntactic acquisition in children.     

The genesis and use of exemplar vs. prototype knowledge in abstract category learning

Accurate classification of new exemplars in an abstraction paradigm may be due to their similarity to old exemplars rather than to abstract category (or prototype) knowledge. In the present study, subjects received initial training on a two-category problem before being transferred to a task in which half of the exemplar-response pairs had their responses reversed while the remaining half of the pairs were unchanged. When transfer occurred with no delay and involved old exemplars, more errors occurred for changed than for unchanged pairs. This result implies the use of exemplar-specific rather than abstract category knowledge. However, when transfer was delayed by 24 or 72 h, errors occurred equally often for changed and unchanged pairs. This result suggests that exemplar-specific knowledge is no longer used. Since subjects were still able to accurately classify exemplars prior to the transfer task at these delays, some form of abstract category knowledge is implicated.     

Applying an exemplar model to an implicit rule-learning task: Implicit learning of semantic structure

Studies of implicit learning often examine peoples’ sensitivity to sequential structure. Computational accounts have evolved to reflect this bias. An experiment conducted by Neil and Higham [Neil, G. J., & Higham, P. A.(2012). Implicit learning of conjunctive rule sets: An alternative to artificial grammars. Consciousness and Cognition, 21, 1393–1400] points to limitations in the sequential approach. In the experiment, participants studied words selected according to a conjunctive rule. At test, participants discriminated rule-consistent from rule-violating words but could not verbalize the rule. Although the data elude explanation by sequential models, an exemplar model of implicit learning can explain them. To make the case, we simulate the full pattern of results by incorporating vector representations for the words used in the experiment, derived from the large-scale semantic space models LSA and BEAGLE, into an exemplar model of memory, MINERVA 2. We show that basic memory processes in a classic model of memory capture implicit learning of non-sequential rules, provided that stimuli are appropriately represented.     

The distributed learning effect for children's acquisition of an abstract syntactic construction

In many cognitive domains, learning is more effective when exemplars are distributed over a number of sessions than when they are all presented within one session. The present study investigated this distributed learning effect with respect to English-speaking children's acquisition of a complex grammatical construction. Forty-eight children aged 3;6–5;10 (Experiment 1) and 72 children aged 4;0–5;0 (Experiment 2) were given 10 exposures to the construction all in one session (massed), or on a schedule of two trials per day for 5 days (distributed-pairs), or one trial per day for 10 days (distributed). Children in both the distributed-pairs and distributed conditions learnt the construction better than children in the massed condition, as evidenced by productive use of this construction with a verb that had not been presented during training. Methodological and theoretical implications of this finding are discussed, with particular reference to single-process accounts of language acquisition.     

Implicit learning of complex structures: active adaptation and selective processing in acquisition and application

Subjects exposed to members of a structured domain become sensitive to the general structure of that domain, even when they are unaware that the domain has such structure (e.g., Reber, 1993). Numerous investigators have attempted to characterize this learning as unselective in acquisition and automatic in application. However, we contend that this characterization miscasts the fundamental nature of learning. In a series of experiments, we demonstrate that what subjects learn implicitly about the structure of a domain critically depends on decisions they make about how to organize the structural components. Similarly, the application of knowledge gained implicitly is not stable, but may be selected or even created under the demands of the test task. We conclude that implicit learning, just like explicit learning, proceeds through active organization of the stimulus complex, rather than by passively absorbing any level of structure. We propose a synthesis, in which learning, with and without awareness, is understood through a common set of principles.     

Incidental learning of real-world regularities

The large literature on incidental learning relies almost exclusively on laboratory experiments. Whenever researchers have attempted to demonstrate incidental learning of real-world regularities, they have typically failed to show learning. For example, it is well established that people do not learn regularities in everyday objects, such as the left-right orientation of faces on coins, despite a very large exposure to them. In this report, we examine this apparent contradiction. We argue that most studies exploring real-life incidental learning use tests that are not as sensitive to low-confidence information as those traditionally used in laboratory tasks. Using more sensitive measures, we show that it is possible to learn regularities from British and Japanese cultural life as a direct result of exposure to these regularities. Further, confidence measures suggest that although the information may be acquired incidentally, it can be expressed with and without concomitant awareness of that knowledge.