In the late-1980s, visual cognition was a small subfield of cognitive psychology, and the standard texts mainly discussed just iconic memory in their sections on visual cognition. In the subsequent two decades, and especially very recently, many remarkable new aspects of the processing of brief visual stimuli have been discovered -- change blindness, repetition blindness, the attentional blink, newly-discovered properties of visual short-term memory and of the face recognition system, the influence of reentrant processing on visual perception, and the surprisingly intimate relationships between eyeblinks and visual cognition. This volume provides up-to-date tutorial reviews of these many new developments in the study of visual cognition written by the leaders in the discipline, providing an incisive and comprehensive survey of research in this dynamic field.

These essays tackle some of the central issues in visual cognition, presenting experimental techniques from cognitive psychology, new ways of modeling cognitive processes on computers from artificial intelligence, and new ways of studying brain organization from neuropsychology, to address such questions as: How do we recognize objects in front of us? How do we reason about objects when they are absent and only in memory? How do we conceptualize the three dimensions of space? Do different people do these things in different ways? And where are these abilities located in the brain? While this research, which appeared as a special issue of the journal Cognition, is at the cutting edge of cognitive science, it does not assume a highly technical background on the part of readers. The book begins with a tutorial introduction by the editor, making it suitable for specialists and nonspecialists alike.

The Influence of Attention, Learning, and Motivation on Visual Search will bring together distinguished authors who are conducting cutting edge research on the many factors that influence search behavior. These factors will include low-level feature detection; statistical learning; scene perception; neural mechanisms of attention; and applied research in real world settings.

Cognitive Load Measurement and Application provides up-to-date research and theory on the functional role of cognitive load measurement and its application in multimedia and visual learning. Grounded in a sound theoretical framework, this edited volume introduces methodologies and strategies that effect high-quality cognitive load measurement in learning. Case studies are provided to aid readers in comprehension and application within various learning situations, and the book concludes with a review of the possible future directions of the discipline.

Technology-enhanced, collaborative and blended learning settings can promote more effective approaches to teaching, learning and assessment when context, agency and individual characteristics are taken into account. This book presents critical insight into the theoretical and practical progress made towards establishing effective, valid and reliable strategies for using and evaluating such approaches, and the challenges and implications of doing so. Topics explored include technology-enhanced learning and student evaluations; student engagement and the perception of teaching quality; instructional design and assessment strategies; blended network and mobile technologies for enriching learning and for monitoring and assessment; and the motivations of students to engage with evaluation. Contributors examine issues such as the underlying variabilities in student evaluation of teaching; the implications of inherited cultural and pedagogic practices for educators using collaborative and blended learning; and the international empirical progress in research to understand and measure interactions between cognition, successful learning, and individual difference in technology-augmented settings.

This volume presents the latest thinking on attention from the philosophers and psychologists who are working at the interface between these two disciplines.

The perception-action cycle is the circular flow of information that takes place between the organism and its environment in the course of a sensory-guided sequence of behaviour towards a goal. Each action causes changes in the environment that are analyzed bottom-up through the perceptual hierarchy and lead to the processing of further action, top-down through the executive hierarchy, toward motor effectors. These actions cause new changes that are analyzed and lead to new action, and so the cycle continues. The Perception-action cycle: Models, architectures and hardware book provides focused and easily accessible reviews of various aspects of the perception-action cycle. It is an unparalleled resource of information that will be an invaluable companion to anyone in constructing and developing models, algorithms and hardware implementations of autonomous machines empowered with cognitive capabilities. The book is divided into three main parts. In the first part, leading computational neuroscientists present brain-inspired models of perception, attention, cognitive control, decision making, conflict resolution and monitoring, knowledge representation and reasoning, learning and memory, planning and action, and consciousness grounded on experimental data. In the second part, architectures, algorithms, and systems with cognitive capabilities and minimal guidance from the brain, are discussed. These architectures, algorithms, and systems are inspired from the areas of cognitive science, computer vision, robotics, information theory, machine learning, computer agents and artificial intelligence. In the third part, the analysis, design and implementation of hardware systems with robust cognitive abilities from the areas of mechatronics, sensing technology, sensor fusion, smart sensor networks, control rules, controllability, stability, model/knowledge representation, and reasoning are discussed.