The Handbook of Attention
The Handbook of Attention

Laboratory research on human attention has often been conducted under conditions that bear little resemblance to the complexity of our everyday lives. Although this research has yielded interesting discoveries, few scholars have truly connected these findings to natural experiences. This book bridges the gap between "laboratory and life" by bringing together cutting-edge research using traditional methodologies with research that focuses on attention in everyday contexts. It offers definitive reviews by both established and rising research stars on foundational topics such as visual attention and cognitive control, underrepresented domains such as auditory and temporal attention, and emerging areas of investigation such as mind wandering and embodied attention. The contributors discuss a range

of approaches and methodologies, including psychophysics, mental chronometry, stationary and mobile eye-tracking, and electrophysiological and functional brain imaging. Chapters on everyday attention consider such diverse activities as driving, shopping, reading, multitasking, and playing videogames. All chapters present their topics in the same overall format: historical context, current research, the possible integration of laboratory and real-world approaches, future directions, and key and outstanding issues. ContributorsRichard A. Abrams, Lewis Baker, Daphne Bavelier, Virginia Best, Adam B. Blake, Paul W. Burgess, Alan D. Castel, Karen Collins, Mike J. Dixon, Sidney K. D'Mello, Julia Focker, Charles L. Folk, Tom Foulsham, Jonathan A. Fugelsang, Bradley S. Gibson, Matthias S. Gobel, Davood G. Gozli, Arthur C. Graesser, Peter A. Hancock, Kevin A. Harrigan, Simone G. Heideman, Cristy Ho, Roxane J. Itier, Gustav Kuhn, Michael F. Land, Mallorie Leinenger, Daniel Levin, Steven J. Luck, Gerald Matthews, Daniel Memmert, Stephen Monsell, Meeneley Nazarian, Anna C. Nobre, Andrew M. Olney, Kerri Pickel, Jay Pratt, Keith Rayner, Daniel C. Richardson, Evan F. Risko, Barbara Shinn-Cun

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