Attention, Perception, & Psychophysics

Journal Information
ISSN / EISSN : 19433921 / 1943393X
Current Publisher: Springer Science and Business Media LLC (10.3758)
Total articles ≅ 2,126
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Latest articles in this journal

Cary Stothart, James R. Brockmole
Attention, Perception, & Psychophysics pp 1-7; doi:10.3758/s13414-019-01790-9

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Megan H. Papesh, Juan D. Guevara Pinto
Attention, Perception, & Psychophysics pp 1-13; doi:10.3758/s13414-019-01777-6

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Benjamin Wolfe, Ben D. Sawyer, Anna Kosovicheva, Bryan Reimer, Ruth Rosenholtz
Attention, Perception, & Psychophysics pp 1-16; doi:10.3758/s13414-019-01795-4

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Stephen Grossberg
Attention, Perception, & Psychophysics pp 1-28; doi:10.3758/s13414-019-01789-2

Abstract:This article describes mechanistic links that exist in advanced brains between processes that regulate conscious attention, seeing, and knowing, and those that regulate looking and reaching. These mechanistic links arise from basic properties of brain design principles such as complementary computing, hierarchical resolution of uncertainty, and adaptive resonance. These principles require conscious states to mark perceptual and cognitive representations that are complete, context sensitive, and stable enough to control effective actions. Surface–shroud resonances support conscious seeing and action, whereas feature–category resonances support learning, recognition, and prediction of invariant object categories. Feedback interactions between cortical areas such as peristriate visual cortical areas V2, V3A, and V4, and the lateral intraparietal area (LIP) and inferior parietal sulcus (IPS) of the posterior parietal cortex (PPC) control sequences of saccadic eye movements that foveate salient features of attended objects and thereby drive invariant object category learning. Learned categories can, in turn, prime the objects and features that are attended and searched. These interactions coordinate processes of spatial and object attention, figure–ground separation, predictive remapping, invariant object category learning, and visual search. They create a foundation for learning to control motor-equivalent arm movement sequences, and for storing these sequences in cognitive working memories that can trigger the learning of cognitive plans with which to read out skilled movement sequences. Cognitive–emotional interactions that are regulated by reinforcement learning can then help to select the plans that control actions most likely to acquire valued goal objects in different situations. Many interdisciplinary psychological and neurobiological data about conscious and unconscious behaviors in normal individuals and clinical patients have been explained in terms of these concepts and mechanisms.
Ann J. Carrigan, Susan G. Wardle, Anina N. Rich
Attention, Perception, & Psychophysics pp 1-15; doi:10.3758/s13414-019-01782-9

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Deirdre E. McLaughlin, Yaminah D. Carter, Cecilia C. Cheng, Tyler K. Perrachione
Attention, Perception, & Psychophysics pp 1-20; doi:10.3758/s13414-019-01778-5

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Hector Arciniega, AlexandreA Kilgore-Gomez, Alison Harris, Dwight J. Peterson, Jaclyn McBride, Emily Fox, Marian E. Berryhill
Attention, Perception, & Psychophysics pp 1-7; doi:10.3758/s13414-019-01774-9

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Jennifer E. Swansburg, Heather F. Neyedli
Attention, Perception, & Psychophysics pp 1-9; doi:10.3758/s13414-019-01794-5

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Cathleen M. Moore, Teresa Stephens, Elisabeth Hein
Attention, Perception, & Psychophysics pp 1-12; doi:10.3758/s13414-019-01763-y

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Daniel A. Gajewski, Junjun Zhang, Sarah Shomstein, Joseph C. Nah, John W. Philbeck
Attention, Perception, & Psychophysics pp 1-10; doi:10.3758/s13414-019-01793-6

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