David H. Rakison

Language is not Just for Talking Redundant Labels Facilitate Learning of Novel Categories

In addition to having communicative functions, verbal labels may play a role in shaping concepts. Two experiments assessed whether the presence of labels affected category formation. Subjects learned to categorize “aliens” as those to be approached or those to be avoided. After accuracy feedback on each response was provided, a nonsense label was either presented or not. Providing nonsense category labels facilitated category learning even though the labels were redundant and all subjects had equivalent experience with supervised categorization of the stimuli. A follow-up study investigated differences between learning verbal and nonverbal associations and showed that learning a nonverbal association did not facilitate categorization. The findings show that labels make category distinctions more concrete and bear directly on the language-and-thought debate.

Threat Perception Across the Life Span: Evidence for Multiple Converging Pathways

Snakes and spiders are the objects of two of the most common fears and phobias throughout the world. In the lab, researchers have documented two interesting phenomena in adult humans and nonhuman primates: A propensity for the rapid association of snakes and spiders with fear, and a propensity for the rapid detection of these threatening stimuli. Here, we describe these perceptual biases for threat and highlight new work supporting their existence in infants and young children.

Infants’ Use of Functional Parts in Basic‐like Categorization

An experiment with the sequential touching technique investigated the role of object parts on 1- to 2-year-old infants’ ability to form basic-level categories (cows and cars) from two different superordinate domains. Using the novel task design developed by Rakison and Butterworth, infants were tested with normal category exemplars as well as modified versions that were made by removing or attaching object parts (legs and wheels). Results revealed a developmental trend whereby infants’ use of object parts in categorization decreased with age. Analyses of infants’ functional responses (e.g. jumping or rolling) suggested that they might initially associate different kinds of object movement with different kinds of parts.

Exploring the neural correlates of goal-directed action and intention understanding

Because we are a cooperative species, understanding the goals and intentions of others is critical for human survival. In this fMRI study, participants viewed reaching behaviors in which one of four animated characters moved a hand towards one of two objects and either (a) picked up the object, (b) missed the object, or (c) changed his path halfway to lift the other object. The characters included a human, a humanoid robot, stacked boxes with an arm, and a mechanical claw. The first three moved in an identical, human-like biological pattern. Right posterior superior temporal sulcus (pSTS) activity increased when the human or humanoid robot shifted goals or missed the target relative to obtaining the original goal. This suggests that the pSTS was engaged differentially for figures that appeared more human-like rather than for all human-like motion. Medial frontal areas that are part of a protagonist-monitoring network with the right pSTS (e.g., Mason and Just, 2006) were most engaged for the human character, followed by the robot character. The current data suggest that goal-directed action and intention understanding require this network and it is used similarly for the two processes. Moreover, it is modulated by character identity rather than only the presence of biological motion. We discuss the implications for behavioral theories of goal-directed action and intention understanding.

U-Shaped Curves in Development: A PDP Approach.

As the articles in this issue attest, U-shaped curves in development have stimulated a wide spectrum of research across disparate task domains and age groups and have provoked a variety of ideas about their origins and theoretical significance. In our view, the ubiquity of the general pattern suggests that U-shaped curves can arise from multiple factors, and that the various viewpoints represented herein may be useful for explaining some aspects of developmental change. In this spirit, we offer an additional way of thinking about such phenomena. Specifically, we suggest that U-shaped curves can arise within a domain-general learning mechanism as it slowly masters a domain characterized by statistical regularities and exceptions. This idea differs from those considered thus far, and may encompass many of the phenomena addressed by other views, three of which we outline briefly here. JOURNAL OF COGNITION AND DEVELOPMENT, 1(5), 137–145 Copyright

Is an infant a people person

Kuhlmeier, Bloom, and Wynn (2004) presented interesting data that purport to show that 5-month olds apply the constraint of continuous motion to objects but not to people. They propose, based on these data, that humans are interpreted in terms of social actions whereas inanimate objects are construed in terms of object physics. We believe that care must be taken, however, before strong conclusions can be drawn from their empirical findings. We also find their proposal fails to address an important developmental issue, namely, what mechanism might underlie infants’ ability to learn about people, animates more generally, and inanimates. We address these issues in turn. Limitations of the empirical findings. The main finding of the experiments is that infants looked for different durations at the one box versus two box test events but equally long at the one person versus two person test events. There are a number of reasons why we have reservations about this finding. First, Kuhlmeier et al. caution that infants’ looking behavior in Experiment 2 must be interpreted with discretion, but they nonetheless rely on it as the basis for their conclusions about the nature of infants’ representations for people and inanimates. We are wary, however, of interpreting these null results as meaningful, particularly in light of such a small sample of infants in each condition ðN 1⁄4 10Þ: Additionally, our reading of the data is that one condition alone—the continuous habituation condition with the box in Experiment 1—may be driving force behind the statistical significance of results. That is, it is not clear that infants in both conditions in Experiment 1 responded by looking longer at the anomalous event than the event

Expectations About Single Event Probabilities in the First Year of Life: The Influence of Perceptual and Statistical Information

Recent evidence suggests that infants can generate expectations about future events from a sample of probabilistic data. However, little is known about the conditions that support the development of this ability. Three experiments tested the prediction that 8- and 12-month-olds respond to base rates as well as perceptual cues when they generate expectations from a sample of probabilistic data. Results revealed that 12-month-olds were sensitive to the statistical and perceptual properties of the evidence depending on the distribution of high-to-low base rate items in the sample. Specifically, 12-month-olds focused on perceptual features of the evidence when a sample was large and more skewed (e.g., 6:1), whereas they attended to statistical properties when the sample was smaller and less skewed (e.g., 4:1). In contrast, eight-month-olds always focused on the perceptual features of the evidence. Neither group generated expectations from a small, less skewed sample (e.g., 2:1). These results suggest that the ability to generate expectations about future events is mediated by specific features of the available evidence and undergoes significant change during the 1st year of life.

The development of modeling or the modeling of development

We agree with many theoretical points presented by Rogers & McClelland (R&M), especially the role of domain-general learning of coherent covariation. Nonetheless, we argue that in failing to be informed by key aspects of development, including the role of labels on categorization and the emergence of constraints on learning, their model fails to capture important features of the ontogeny of knowledge. The book Semantic Cognition by Rogers and McClelland (2004) is an elegant demonstration that a simple parallel distributed processing (PDP) model can exhibit behavior that matches the behavior found in a range of empirical studies on infants’ conceptual development. As such, Rogers & McClelland (R&M) make a compelling case that domain-general, rather that domain-specific, mechanisms that are sensitive to lowerand higher-order covariation underpin early concept formation. Although we concur with many of the authors’ claims and their general theoretical perspective, in this commentary we propose that R&M have overlooked a number of key points about development which are crucial to consider in modeling early concept formation. An important aspect of early concept learning overlooked by R&M is the role of verbal labels. Labels affect categorization and concept development in infants as young as 9 months (e.g., Balaban & Waxman 1997; Xu 2002), and their effect continues to grow in the subsequent months (e.g., Fulkerson & Haaf 2003; Nazzi & Gopnik 2001; Waxman & Markow 1995). Thus, labeling may be an important additional mechanism by which infants construe semantically related items as similar to one another in the absence of observable similarities. Unfortunately, the role of labels cannot be investigated in R&M’s network because they are implemented as simple stimulus features (the ISA relation). Inour opinion, it is erroneous to implement basiclevel category labels as features akin to having wings or barking. The principle of coherent covariation gains traction because the feature can move, for example, is informative in that not all entities can move and that being able to move predicts other properties. Labels are different: Many things from different semantic categories can move, but only canaries are canaries. From this perspective, the category label is the piece of information that varies most coherently and is most predictive of the item’s category. To explore the consequences of labels on concept formation, a model needs to map multiple exemplars (e.g., many different canaries), to a single label. In the process of learning to associate a single label with multiple category exemplars, the label becomes strongly associated with features most predictive of the category (Lupyan 2005) providing the “glue” that may be necessary for cohering together items from categories with high intra-category variability (Lupyan, in press). Thus, rather than adding a simple feature, labels can be thought to schematize a given stimulus by placing it into a relationship with the other members of the category. An additional concern relates to the fact that humans, and especially human infants, demonstrate clear limits on learning, whereas connectionist networks are capable of learning essentially any pattern of inputs (Massaro 1988). This point is overlooked in two ways by R&M’s model. First, in a number of simulations the model is able to show patterns of behavior that match those of infants only after it receives a level of experience that is unavailable in the real-world or the laboratory setting. The model, for example, has only begun to differentiate conceptually the input stimuli after 50 epochs, but by this time the network has been exposed to over 50,000 trials (Siegler 2005). Second, and more important, R&M expose the model to all of the covarying input at the same time, yet infants are limited in the amount and kind of correlated information they can process. Before approximately 7 months of age, for example, infants are unable to encode relations among static features (Younger & Cohen 1986), and it is not until around 14 months of age that they can encode object features or whole objects with dynamic motion-related cues such as can fly or can walk (Rakison 2005). That infants are unable to process certain kinds of information constrains concept learning, but, at the same time, it also facilitates concept learning; that is, it allows infants to learn about more fundamental aspects of things in the world while at the same time ignoring other aspects. R&M’s model, in contrast, is exposed simultaneously to a wide range of information which in an infant would probably lead to what William James (1890) called a “blooming, buzzing confusion.” R&M argue that they used input features that they consider to be important or salient to infants, but in our view this approach disregards a large database of empirical data that shows to which features infants actually attend in developing concepts (see Madole & Oakes 1999). Finally, the architecture of R&M’s model is sufficiently flexible and powerful to demonstrate learning for any input pattern. Fitting a PDP model to existing data is not the strongest test of the theory advocated by the model (Roberts & Pashler 2000); more powerful support for the theory behind the model is to generate novel predictions that are borne out by empirical studies. Moreover, from our perspective any model that tries to emulate a set of empirical findings with infants or children must take developmental issues into account. We have recently developed such a PDP model for early concept formation that is theoretically compatible with that of that of R&M, but that incorporates development in a number of plausible ways (e.g., increasing over time the number of hidden units and reducing over time the weight-decay parameter of fast but not slow learning links) (Rakison & Lupyan, in press). This developmentally oriented model exhibits behavior that is unintuitive but nonetheless matches that found in infants. For example, 14-month-olds learn relations in simple causal events that are consistent and inconsistent with the real world (e.g., agents possessing moving or static parts), but 16-month-olds demonstrate constraints on learning by failing to learn the inconsistent events (Rakison 2005). From our perspective it is necessary for models to be informed and compatible with key developmental findings and issues if traction is to be made in determining the origins, nature, and development of concepts. Semantic redintegration: Ecological

Developing without concepts

We evaluate the heterogeneity hypothesis by considering the developmental time course and the mechanism of acquisition of exemplars, prototypes, and theories. We argue that behavioral and modeling data point to a sequential emergence of these three types of concepts within a single system. This suggests that similar or identical underlying cognitive processes - rather than separate ones - underpin representation acquisition.

Do 5-Month-Old Infants Possess an Evolved Detection Mechanism for Snakes, Sharks, and Rodents?

ABSTRACT The 4 experiments reported here used the preferential looking and habituation paradigms to examine whether 5-month-olds possess a perceptual template for snakes, sharks, and rodents. It was predicted that if infants possess such a template, then they would attend preferentially to schematic images of these nonhuman animal stimuli relative to scrambled versions of the same stimuli. The results revealed that infants looked longer at a schematic snake than at 2 scrambled versions of the image and generalized from real snakes to the schematic image. The experiments also demonstrated that 5-month-olds showed no preferential looking for schematic sharks or schematic rodents relative to scrambled versions of those images. These data add to the growing support for the view that humans, like many nonhuman animals, possess an evolved fear mechanism for detecting threats that were recurrent across evolutionary time.