© 2017 Elsevier Inc. All rights reserved. Systems Factorial Technology: A Theory Driven Methodology for the Identification of Perceptual and Cognitive Mechanisms explores the theoretical and methodolo...
With the explosion of “big data,” digital repositories of texts and images are growing rapidly. These datasets present new opportunities for psychological research, but they require new methodologies ...
While previous studies have shown that human behavior adjusts in response to uncertainty, it is still not well understood how uncertainty is estimated and represented. As probability distributions are...
When people search a display for a target defined by a unique feature, fast saccades are predominantly stimulus-driven whereas slower saccades are primarily goal-driven. Here we use this dissociative ...
When learning rule-based categories, sufficient cognitive resources are needed to test hypotheses, maintain the currently active rule in working memory, update rules after feedback, and to select a ne...
When interacting with categories, representations focused on within-category relationships are often learned, but the conditions promoting within-category representations and their generalizability ar...
We provide a tutorial on the basic attributes of computational cognitive models—models that are formulated as a set of mathematical equations or as a computer simulation. We first show how models can ...
We introduce the δ-machine, a statistical learning tool for classification based on (dis)similarities between profiles of the observations to profiles of a representation set consisting of prototypes....
Visualization is an important tool for capturing the network activities. Effective visualization allows people to gain insights into the data information and discovery of communication patterns of net...
Under the guidance of a formal exemplar model of categorization, we conduct comparisons of natural-science classification learning across four conditions in which the nature of the training examples i...
This thesis aims to understand visual style in the context of computer science, using traditionally intangible artistic properties to enhance existing content manipulation algorithms and develop new c...
This special section brings together behavioral, computational, mathematical, and neuroimaging approaches to understand the processes underlying category learning. Over the past decade, there has been...
This paper provides a critical examination of the current state and future possibility of formal cognitive theory for insight problem solving and its associated “aha!” experience. Insight problems are...
This article reports data sets aimed at the development of a detailed feature-space representation for a complex natural category domain, namely 30 common subtypes of the categories of igneous, metamo...
The recent introduction of 3D shape analysis frameworks able to quantify the deformation of a shape into another in terms of the variation of real functions yields a new interpretation of the 3D shape...
The present study proposes and examines the multidimensional vector (MDV) model framework as a modeling schema for choice response times. MDV extends the Thurstonian model, as well as signal detection...
The large use of CAD systems in many industrial fields, such as automotive, naval, and aerospace, has generated a number of 3D databases making available a lot of 3D digital models. Within enterprises...
The field of psychological science has seen major advances in the development of formal models of perceptual classification learning; however, little work has tested such models in real-world natural-...
The experimental study of sonic interactions can elucidate one of the most important aspects of the design process: "How should the sonic interaction be structured to produce a target perceptual resul...
The auditory perception of materials is a popular topic in the study of non-vocal sound-source perception. In this chapter, we review the empirical evidence on the mechanical and acoustical correlates...