Some primitive mechanisms of spatial attention☆
References (35)
- et al.
Connectionist models and their properties
Cognitive Science
(1982) - et al.
How direct is visual perception? Some reflections on Gibson's “ecological approach”
Cognition
(1981) - et al.
Connectionism and cognitive architecture: A critical analysis
Cognition
(1988) Psychological explanations and knowledge-dependent processes
Cognition
(1981)The role of location indexes in spatial perception: A sketch of the FINST spatial-index model
Cognition
(1989)- et al.
A feature integration theory of attention
Cognitive Psychology
(1980) Visual Routines
Cognition
(1984)Multielement visual tracking: Attention and perceptual organization
Cognitive Psychology
(1992)- et al.
A neural network model of spatial indexing
Investigative Ophthalmology and Visual Science
(1993) - et al.
Indexing multiple loci in the visual field: Evidence for simultaneous facilitation in visual search
Visual attention within and around the field of focal attention: A zoom lens model
Perception and Psychophysics
Multiple abrupt onset cues produce illusory line motion
Investigative Ophthalmology and Visual Science
Focal visual attention produces motion sensation in lines
Investigative Ophthalmology and Visual Science
An object-specific spatial attentional facilitation that does not travel to adjacent spatial locations
Investigative Ophthalmology and Visual Science
Curve tracing operation and the perception of spatial relations
Shifts in selective visual attention: Towards the underlying neural circuitry
Human Neurobiology
On the demystification of mental imagery
Behavioral and Brain Science
Cited by (118)
Fast automated counting procedures in addition problem solving: When are they used and why are they mistaken for retrieval?
2016, CognitionCitation Excerpt :Instead, the representations we hypothesize are closer to an object file in which each object is individuated (Feigenson et al., 2002; Simon, 1997). It is known that the use of object-file representations yields a set-size signature with success at representing sets up to four objects and failure with larger numbers (Kahneman, Treisman, & Gibbs, 1992; Pylyshyn, 1989; Pylyshyn, 1994). The involvement of this type of representation in very small problems would explain why their solving was affected by a strong size-effect, whereas RTs for small problems involving operands larger than four (the medium small problems) remained immune to size effect.
Neural and Behavioral Signatures of Core Numerical Abilities and Early Symbolic Number Development
2015, Development of Mathematical Cognition: Neural Substrates and Genetic Influences: Volume 2Two core systems of numerical representation in infants
2014, Developmental ReviewCitation Excerpt :Recently, the OTS has been proposed to account for adults’ fast and accurate processing of small visual sets. The current OTS model (sometimes referred to as “parallel individuation”; Carey, 2004) is considered part of infants’ core knowledge of objects (Cheries, Mitroff, Wynn, & Scholl, 2009; Leslie, Xu, Tremoulet, & Scholl, 1998; Scholl & Leslie, 1999; Spelke & Kinzler, 2007) and is a reformulation of two previous models, the FINST mechanism (Pylyshyn, 1989, 1994, 2001; Pylyshyn & Storm, 1988; Trick & Pylyshyn, 1994) and the object file mechanism (Kahneman & Treisman, 1984; Kahneman, Treisman, & Gibbs, 1992), both of which are mechanisms of visual attention designed to explain humans’ ability to individuate and track visual objects and solve the problem of object correspondence. The OTS consists of a set of indexes that “point” to individual objects, allowing objects to be tracked through time and space (Kahneman et al., 1992; Pylyshyn, 1989).
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The work reported herein was carried out under the author's direction at the Center for Cognitive Science, University of Western Ontario. Much of it has been reported in theses in the Department of Psychology and the Department of Electrical Engineering at the University of Western Ontario, by graduate students Brian Acton, Jacquie Burkell, Roy Eagleson, Paul McKeever, William Schmidt, Chris Sears and Lana Trick. These students, along with our Research Scientist Brian Fisher, contributed most of the empirical and theoretical work discussed in this paper. This research was supported by the Canadian Natural Science and Engineering Research Council (Grant A2600) and by a “Project B-4” grant from the Institute for Robotics and Intelligent Systems.
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