Order of Presentation Effects in Learning Color Categories

Acquisition of colour categories through learning: Differences between hue and lightness

Colour categories are acquired through learning, but the nature of this process is not fully understood. Some category distinctions are defined by hue (e.g. red/purple) but other by lightness (red/pink). The aim of this study was to investigate if the acquisition of key information for making accurate cross-boundary discriminations poses different challenges for hue-defined as opposed to lightness-defined boundaries. To answer this question, hue- and lightness-learners were trained on a novel category boundary within the GREEN region of colour space. After training, hue- and lightness-learners as well as untrained controls performed delayed same-different discrimination for lightness and hue pairs. In addition to discrimination data, errors during learning and category-labelling strategies were examined. Errors during learning distributed non-uniformly and in accordance with the Bezold-Brücke effect, which accounts for darker colours at the green-blue boundary appearing greener and lighter colours appearing bluer. Only hue-learners showed discrimination improvements due to category boundary acquisition. Thus, acquisition is more efficient for hue-category compared to lightness-category boundaries. Almost all learners reported using category-labelling strategies, with hue-learners almost exclusively using 'green'/'blue' and lightness learners using a wider range of labels, most often 'light'/'dark'. Thus, labels play an important role in colour category learning and such labelling does not conform to everyday naming: here, the label 'blue' is used for exemplars that would normally be named 'green'. In conclusion, labelling serves the purpose of highlighting key information that differentiates exemplars across the category boundary, and basic colour terms may be particularly effective in facilitating such attentional guidance.

Investigating interactions between types of order in categorization

This study simultaneously manipulates within-category (rule-based vs. similarity-based), between-category (blocked vs. interleaved), and across-blocks (constant vs. variable) orders to investigate how different types of presentation order interact with one another. With regard to within-category orders, stimuli were presented either in a "rule plus exceptions" fashion (in the rule-based order) or by maximizing the similarity between contiguous examples (in the similarity-based order). As for the between-category manipulation, categories were either blocked (in the blocked order) or alternated (in the interleaved order). Finally, the sequence of stimuli was either repeated (in the constant order) or varied (in the variable order) across blocks. This research offers a novel approach through both an individual and concurrent analysis of the studied factors, with the investigation of across-blocks manipulations being unprecedented. We found a significant interaction between within-category and across-blocks orders, as well as between between-category and across-blocks orders. In particular, the combination similarity-based + variable orders was the most detrimental, whereas the combination blocked + constant was the most beneficial. We also found a main effect of across-blocks manipulation, with faster learning in the constant order as compared to the variable one. With regard to the classification of novel stimuli, learners in the rule-based and interleaved orders showed generalization patterns that were more consistent with a specific rule-based strategy, as compared to learners in the similarity-based and blocked orders, respectively. This study shows that different types of order can interact in a subtle fashion and thus should not be considered in isolation.

A Computational Model of Context-Dependent Encodings During Category Learning

Although current exemplar models of category learning are flexible and can capture how different features are emphasized for different categories, they still lack the flexibility to adapt to local changes in category learning, such as the effect of different sequences of study. In this paper, we introduce a new model of category learning, the Sequential Attention Theory Model (SAT-M), in which the encoding of each presented item is influenced not only by its category assignment (global context) as in other exemplar models, but also by how its properties relate to the properties of temporally neighboring items (local context). By fitting SAT-M to data from experiments comparing category learning with different sequences of trials (interleaved vs. blocked), we demonstrate that SAT-M captures the effect of local context and predicts when interleaved or blocked training will result in better testing performance across three different studies. Comparatively, ALCOVE, SUSTAIN, and a version of SAT-M without locally adaptive encoding provided poor fits to the results. Moreover, we evaluated the direct prediction of the model that different sequences of training change what learners encode and determined that the best-fit encoding parameter values match learners' looking times during training.

One versus many: Multiple examples in word learning

A large body of research indicates that children can map words to categories and generalize the label to new instances of the category after hearing a single instance of the category labeled. Additional research demonstrates that word learning is enhanced when children are presented with multiple instances of a category through comparison or contrast. In this study, 3-year-old children participated in a novel noun generalization task in which a label was given for either (a) a single instance of a category, (b) multiple instances of a category, or (c) contrasting a category instance with non-category members. Children were asked to extend the label to a new category at test either immediately (Study 1) or after a 10-s delay (Study 2). The results indicate that when tested immediately, children who heard a single instance labeled outperformed children who were presented with multiple instances. However, when tested after a brief delay, there was no difference among the conditions.

A mechanism for the cortical computation of hierarchical linguistic structure

Biological systems often detect species-specific signals in the environment. In humans, speech and language are species-specific signals of fundamental biological importance. To detect the linguistic signal, human brains must form hierarchical representations from a sequence of perceptual inputs distributed in time. What mechanism underlies this ability? One hypothesis is that the brain repurposed an available neurobiological mechanism when hierarchical linguistic representation became an efficient solution to a computational problem posed to the organism. Under such an account, a single mechanism must have the capacity to perform multiple, functionally related computations, e.g., detect the linguistic signal and perform other cognitive functions, while, ideally, oscillating like the human brain. We show that a computational model of analogy, built for an entirely different purpose-learning relational reasoning-processes sentences, represents their meaning, and, crucially, exhibits oscillatory activation patterns resembling cortical signals elicited by the same stimuli. Such redundancy in the cortical and machine signals is indicative of formal and mechanistic alignment between representational structure building and "cortical" oscillations. By inductive inference, this synergy suggests that the cortical signal reflects structure generation, just as the machine signal does. A single mechanism-using time to encode information across a layered network-generates the kind of (de)compositional representational hierarchy that is crucial for human language and offers a mechanistic linking hypothesis between linguistic representation and cortical computation.

Putting category learning in order: Category structure and temporal arrangement affect the benefit of interleaved over blocked study

Recent research in inductive category learning has demonstrated that interleaved study of category exemplars results in better performance than does studying each category in separate blocks. However, the questions of how the category structure influences this advantage and how simultaneous presentation interacts with the advantage are open issues. In this article, we present three experiments. The first experiment indicates that the advantage of interleaved over blocked study is modulated by the structure of the categories being studied. More specifically, interleaved study results in better generalization for categories with high within- and between-category similarity, whereas blocked presentation results in better generalization for categories with low within- and between-category similarity. In Experiment 2, we present evidence that when presented simultaneously, between-category comparisons (interleaved presentation) result in a performance advantage for high-similarity categories, but no differences were found for low-similarity categories. In Experiment 3, we directly compared simultaneous and successive presentation of low-similarity categories. We again found an overall benefit for blocked study with these categories. Overall, these results are consistent with the proposal that interleaving emphasizes differences between categories, whereas blocking emphasizes the discovery of commonalities among objects within the same category.

Comparison and mapping facilitate relation discovery and predication

Relational concepts play a central role in human perception and cognition, but little is known about how they are acquired. For example, how do we come to understand that physical force is a higher-order multiplicative relation between mass and acceleration, or that two circles are the same-shape in the same way that two squares are? A recent model of relational learning, DORA (Discovery of Relations by Analogy; Doumas, Hummel & Sandhofer, 2008), predicts that comparison and analogical mapping play a central role in the discovery and predication of novel higher-order relations. We report two experiments testing and confirming this prediction.

Same, varied, or both? Contextual support aids young children in generalizing category labels

Children have a difficult time in generalizing among changes in background context. We examined the role of two processes that may aid in generalizing category labels in new contexts. In this study, 2-year-old children were taught novel object categories in one type of contextual condition and were tested for category generalization in a new context. In Experiment 1, children (N=48) learned in one of three conditions: (a) all category instances presented in the same context, (b) all category instances presented in varied contexts, or (c) some category instances presented in the same context and some presented in varied contexts. In Experiment 2, children (N=48) learned in one of three conditions, all of which included presentations in the same context and varied contexts but differed in order. Results from both experiments revealed that children were significantly more likely to choose the correct object when training was in both same and varied contexts regardless of order. The results suggest that contextual factors, by providing both support for aggregation and support for decontextualization, contribute to word learning and generalization for novice word learners.

Using a single feature to discriminate and form categories: the interaction between color, form and exemplar number

There is relatively little work that has focused on how infants use a single feature to discriminate objects or flexibly group objects together. Existing research suggests that the ease with which infants learn form and color discriminations is not equal. However, which of these dimensions is easier when discriminating between objects is still unclear. The studies in this paper tested how infants used these two dimensions under varying levels of diversity in a discrimination task. Combining traditional analyses with latent-states Markov-modeling, infant learning in these studies was characterized by a bend of overt behavior and attentional processes. Infants were able to learn both a color and form-based discrimination, but only generalized the form distinction to new stimuli. When presented with diversity on the irrelevant dimension, infants in the form condition learned quickly. However, infants in the color-condition did not show signs that they learned the distinction. The results show that infants could use both dimensions to distinguish between objects, but that form-based distinctions were easier and more likely to be generalized to new objects.

Learning words in space and time: probing the mechanisms behind the suspicious-coincidence effect

A major debate in the study of word learning centers on the extension of categories to new items. The rational approach assumes that learners make structured inferences about category membership, whereas the mechanistic approach emphasizes the attentional and memory processes that form the basis of generalization behaviors. Recent support for the rational view comes from observations of the suspicious-coincidence effect: People generalize category membership narrowly when presented with three subordinate-level exemplars that share the same label and generalize category membership broadly when presented with one exemplar. Across three experiments, we examined the mechanistic basis of this effect. Results showed that the presentation of multiple subordinate-level exemplars led to narrow generalization only when the exemplars were presented simultaneously, even when the number of exemplars was increased from three to six. These data demonstrate that the suspicious-coincidence effect is firmly grounded in the general cognitive processes of attention, memory, and visual comparison.

Developmental differences in children's context-dependent word learning

In this study, 2.5-, 3-, and 4-year-olds (N=108) participated in a novel noun generalization task in which background context was manipulated. During the learning phase of each trial, children were presented with exemplars in one or multiple background contexts. At the test, children were asked to generalize to a novel exemplar in either the same or a different context. The 2.5-year-olds' performance was supported by matching contexts; otherwise, children in this age group demonstrated context dependent generalization. The 3-year-olds' performance was also supported by matching contexts; however, children in this age group were aided by training in multiple contexts as well. Finally, the 4-year-olds demonstrated high performance in all conditions. The results are discussed in terms of the relationship between word learning and memory processes; both general memory development and memory developments specific to word learning (e.g., retention of linguistic labels) are likely to support word learning and generalization.

Doing with development: Moving toward a complete theory of concepts

Machery proposes that the construct of “concept” detracts from research progress. However, ignoring development also detracts from research progress. Developmental research has advanced our understanding of how concepts are acquired and thus is essential to a complete theory. We propose a framework that both accounts for development and holds great promise as a new direction for thinking about concepts.