CogSci ... Annual Conference of the Cognitive Science Society. Cognitive Science Society (U.S.). Conference最新文献

In the word-learning domain, both adults and young children are able to find the correct referent of a word from highly ambiguous contexts that involve many words and objects by computing distributional statistics across the co-occurrences of words and referents at multiple naming moments (Yu & Smith, 2007; Smith & Yu, 2008). However, there is still debate regarding how learners accumulate distributional information to learn object labels in natural learning environments, and what underlying learning mechanism learners are most likely to adopt. Using the Human Simulation Paradigm (Gillette, Gleitman, Gleitman & Lederer, 1999), we found that participants' learning performance gradually improved and that their ability to remember and carry over partial knowledge from past learning instances facilitated subsequent learning. These results support the statistical learning model that word learning is a continuous process.

The current study investigated eye-hand coordination in natural reaching. We asked whether the speed of reaching related to the quality of visual information obtained by young children and adults. Participants played with objects on a table while their eye and hand movements were recorded. We developed new techniques to find reaching events in natural activity and to determine how closely participants aligned gaze to objects while reaching. Reaching speed and eye alignment were related for adults but not for children. These results suggest that adults but not children adapt reaching movements according to the quality of visual information (or vice-versa) during natural activity. We discuss possibilities for why this coordination was not observed in children.

An understanding of human collaboration requires a level of analysis that concentrates on sensorimotor behaviors in which the behaviors of social partners continually adjust to and influence each other. A suite of individual differences in partners' ability to both read the social cues of others and to send effective behavioral cues to others create dyad differences in joint attention and joint action. The present paper shows that infant and dyad differences in hand-eye coordination predict dyad differences in joint attention. In the study reported here, 51 toddlers and their parents wore head-mounted eye-trackers as they played together with objects. This method allowed us to track the gaze direction of each participant to determine when they attended to the same object. We found that physically active toddlers align their looking behavior with their parent, and achieve a high proportion of time spent jointly attending to the same object in toy play. However, joint attention bouts in toy play don't depend on gaze following but rather on the coordination of gaze with hand actions on objects. Both infants and parents attend to their partner's object manipulations and in so doing fixate the object visually attended by their partner. Thus, the present results provide evidence for another pathway to joint attention - hand following instead of gaze following. Moreover, dyad differences in joint attention are associated with dyad differences in hand following, and specifically parents' and infants' manual activities on objects and the within- and between-partner coordination of hands and eyes during parent-infant interactions. In particular, infants' manual actions on objects play a critical role in organizing parent-infant joint attention to an object.

Mathematics requires thinking but also pattern recognition. Recent research indicates that perceptual learning (PL) interventions facilitate discovery of structure and recognition of patterns in mathematical domains, as assessed by tests of mathematical competence. Here we sought direct evidence that a brief perceptual learning module (PLM) produces changes in basic information extraction. Accuracy and speed of undergraduate participants' encoding of equations was assessed in a psychophysical task at pretest and delayed posttest. In between, the experimental group completed an Algebraic Transformations PLM, which involved identifying valid transformations of equations. Relative to controls, PLM participants showed reliable changes in encoding equations, detectable psychophysically 24 hours later. Encoding improvements were shown robustly by participants who were initially less proficient at algebra and were negligible for participants who were initially proficient. These results provide direct evidence for durable changes in information encoding produced by a PL intervention targeting a complex mathematical skill.

Semantic models play an important role in cognitive science. These models use statistical learning to model word meanings from co-occurrences in text corpora. A wide variety of semantic models have been proposed, and the literature has typically emphasized situations in which one model outperforms another. However, because these models often vary with respect to multiple sub-processes (e.g., their normalization or dimensionality-reduction methods), it can be difficult to delineate which of these processes are responsible for observed performance differences. Furthermore, the fact that any two models may vary along multiple dimensions makes it difficult to understand where these models fall within the space of possible psychological theories. In this paper, we propose a general framework for organizing the space of semantic models. We then illustrate how this framework can be used to understand model comparisons in terms of individual manipulations along sub-processes. Using several artificial datasets we show how both representational structure and dimensionality-reduction influence a model's ability to pick up on different types of word relationships.

What is the role of feedback information in different visual category learning (VCL) scenarios? To address this question we tested participants' performance in VCL tasks in which stimuli varied in three feature dimensions, one of which was relevant for the task and the other two were irrelevant. The relevant feature could be identified based on trial-by-trial feedback. In one condition the task relevant and irrelevant features were highly-salient. In the second condition all features had low-visual-saliency. Feedback information was also manipulated: In the high-information condition the task relevant feature could be identified by the information provided in each trial whereas in the mid-information condition the feedback was ambiguous and information from several learning trials was required in order to confidently identify the relevant feature. Surprisingly, our data shows that mid- and high-information feedback are similarly effective in high-saliency VCL tasks. In contrast, in low-saliency VCL tasks, mid-information feedback impairs learning. We suggest that VCL can be done effectively either when feedback is ambiguous or in low-saliency conditions, but not in scenarios when both challenges occur concurrently.

The work presented here uses a simple stochastic model as a cognitive psychometric tool for analyzing response time data in the Go/No-Go Discrimination task with motivationally distinct conditions. The parameters of the model inform us of underlying cognitive mechanisms because they have an established psychological meaning and allow us to quantify a subjects ability and response caution. Using these model parameters, we focus on the differences between subjects with varying degrees of substance abuse and antisocial behavioral disorders and show that there are reliable differences between the decision mechanisms of these subjects. Using data from executive working memory tasks, we postulate that these differences in cognitive processes might be due to differences in working memory capacity. Ultimately, we show that formal cognitive modeling has the potential to provide valuable insights into clinical phenomena that cannot be captured by traditional data analysis techniques.

In the McGurk Effect, a visual stimulus can affect the perception of an auditory signal, suggesting integration of the auditory and visual streams. However, it is unclear when in speech processing this auditory-visual integration occurs. The present study used a semantic priming paradigm to investigate whether integration occurs before, during, or after access of the lexical-semantic network. Semantic associates of the un-integrated auditory signal were activated when the auditory stream was a word, while semantic associates of the integrated McGurk percept (a real word) were activated when the auditory signal was a nonword. These results suggest that the temporal relationship between lexical access and integration depends on the lexicality of the auditory stream.

Theories of language production are monolingual but the world is multilingual. In the domain of word-form encoding, it is clear that languages rely differentially on different phonological units, challenging the generality of the monolingual theories. To address this, we propose the proximate units principle, which holds that the initial selection of sub-lexical phonological units (syllables, morae, phonemic segments, etc) is crucial both to understanding language specific processing, and to identifying what is language general in word production. We define proximate units and the role they play in speech planning and execution. The proximate units principle is consistent with much of what is already known about word form encoding across languages but also makes new predictions and can bring greater clarity to interpretations of experimental and speech error data.

How efficiently do we combine information across facial features when recognizing a face? Previous studies have suggested that the perception of a face is not simply the result of an independent analysis of individual facial features, but instead involves a coding of the relationships amongst features. This additional coding of the relationships amongst features is thought to enhance our ability to recognize a face. In our experiments, we tested whether an observer's ability to recognize a face is in fact better than what one would expect from their ability to recognize the individual facial features in isolation. We tested this by using a psychophysical summation-at-threshold technique that has been used extensively to measure how efficiently observers integrate information across spatial locations and spatial frequencies. Surprisingly, we found that observers integrated information across facial features less efficiently than would be predicted by their ability to recognize the individual parts.