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

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.

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.

In the current study we investigate the proposal that one aspect of social perception, action anticipation, involves the recruitment of representations for self-produced action. An eye tracking paradigm was implemented to measure prospective gaze to a goal while performing either a motor or working memory task. Results indicate an effect of the motor task, suggesting the interference of a shared motor and action perception representation.