The Influence of Attention, Learning, and Motivation on Visual Search

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.

Brings together a complete understanding of search that can be obtained by considering the research from a number of different paradigms and domains. Explores relationship between perceptual organization and other cognitive processes. Describes the neural mechanisms underlying perceptual organization using two different approaches--neurophysiological and neuropsychological.

Auteur

Michael Dodd received his Ph.D. in Cognitive Psychology from the University of Toronto in 2005 and was a Killam postdoctoral fellow at the University of British Columbia before joining the University of Nebraska faculty in 2007. His research encompasses many different aspects of human cognition, with a particular focus on visual attention (e.g., visual search; inhibition of return; object-based attention; apparent motion; sensory processing; scene perception; oculomotor programming; task-induced changes in eye movements), memory (false memory, retrieval-induced forgetting, directed forgetting), individual differences (influences of political temperament on cognition) and goal-directed activity, as well as the interactions between these cognitive.

Dr. John H. Flowers jointed the UNL faculty in 1972. He received his Ph.D. from Yale University in 1972 in experimental psychology. His primary research interests are in the general area of human information processing, particularly attention, implicit learning, and the perception of structure. His interest in the perception of structure has recently led to a research program on the use of sound as a means for representing data.

Texte du rabat
Visual search is one of our most ubiquitous activities, as anyone who has had a Where's my car? moment can attest. Attending to relevant stimuli while screening out distractions requires a complex set of interactions between visual, neurological, and behavioral processes. While recent years have seen digital technologies both enhance our visual search experiences and present more intricate visual challenges in our everyday lives, advances in research are quickly catching up with the real world.

The Influence of Attention, Learning, and Motivation on Visual Search brings together a number of exciting lines of inquiry into this topic. In keeping with the near-limitless set of variables that influence search, contributors represent scholarship in laboratory and applied settings, cognitive processes intimately involved in search, and related concepts from a variety of disciplines. Chapters delve into current studies on a wide range of component factors relating to search, including:

• Searching in space and time.

• Automatic control of visual selection.

• Guidance of visual search by memory and knowledge.

• Reward and attentional control in visual search.

• Statistical learning and its consequences.

• Overcoming hurdles in translating visual data between the lab and the field.

• The search termination problem in visual search.

For cognitive and social psychologists, The Influence of Attention, Learning, and Motivation on Visual Search is a stimulating volume that holds multiple possibilities for future developments across a number of behavioral and cognitive domains, from decision-making to problem-solving, from autism and other cognitive deficits to the effects of aging.

Contenu
Introduction.- Searching in Space and in Time.- Automatic Control of Visual Selection.- Guidance of Visual Search by Memory and Knowledge.- Reward and Attentional Control in Visual Search.- Statistical Learning and its Consequences.- Overcoming Hurdles in Translating Visual Search Research Between the Lab and the Field.-When Do I Quit? The Search Termination Problem in Visual Search.