Noise Exclusion in Spatial Attention

Dosher, Barbara Anne; Lü, Zhong-Lin

doi:10.1111/1467-9280.00229

Cited by 245 publications

(337 citation statements)

References 39 publications

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“…Mark's (1972) proposal that such modulation operates by influencing the variance of magnitude representations provides a key theoretical element in the model we will describe below. The hypothesis that attention operates in part by modulating variability in an internal representation is also consistent with findings concerning visual detection and discrimination tasks (Dosher & Lu, 2000;Rahnev et al, 2011).…”

Section: Reference-point Modelssupporting

confidence: 86%

“…Marks, 1972). In the present model, variances increase exponentially with distance from the reference point; however, a variety of neural mechanisms for gain control could potentially implement the impact of attention on gain control (Dosher & Lu, 2000;Rahnev et al, 2011; for a review see Reynolds & Chelazzi, 2004).…”

Section: Reference Points In Symbolic Comparisonsmentioning

confidence: 92%

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The discovery and comparison of symbolic magnitudes

Chen

Holyoak

2014

Cognitive Psychology

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a b s t r a c tHumans and other primates are able to make relative magnitude comparisons, both with perceptual stimuli and with symbolic inputs that convey magnitude information. Although numerous models of magnitude comparison have been proposed, the basic question of how symbolic magnitudes (e.g., size or intelligence of animals) are derived and represented in memory has received little attention. We argue that symbolic magnitudes often will not correspond directly to elementary features of individual concepts. Rather, magnitudes may be formed in working memory based on computations over more basic features stored in long-term memory. We present a model of how magnitudes can be acquired and compared based on BARTlet, a representationally simpler version of Bayesian Analogy with Relational Transformations (BART; Lu, Chen, & Holyoak, 2012). BARTlet operates on distributions of magnitude variables created by applying dimension-specific weights (learned with the aid of empirical priors derived from pre-categorical comparisons) to more primitive features of objects. The resulting magnitude distributions, formed and maintained in working memory, are sensitive to contextual influences such as the range of stimuli and polarity of the question. By incorporating psychological reference points that control the precision of magnitudes in working memory and applying the tools of signal detection theory, BARTlet is able to account for a wide range of empirical phenomena involving magnitude comparisons, including the symbolic distance effect and the semantic congruity effect. We discuss the role of reference points in cognitive and social decision-making, and implications for the evolution of relational representations.

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Section: Reference-point Modelssupporting

confidence: 86%

Section: Reference Points In Symbolic Comparisonsmentioning

confidence: 92%

The discovery and comparison of symbolic magnitudes

Chen

Holyoak

2014

Cognitive Psychology

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“…Stimulus enhancement and internal additive noise reduction might, in theory, be distinguished biologically but cannot be distinguished on the basis of performance measures. External noise exclusion (Dosher & Lu, 2000a, 2000b …”

Section: Signature Patterns For Three Attention Mechanismsmentioning

confidence: 99%

Spatial attention: Different mechanisms for central and peripheral temporal precues?

Lü¹,

Dosher²

2000

Journal of Experimental Psychology: Human Perception and Perfor

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119

204

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The external noise paradigm (Z.-L. Lu & B. A. Dosher, 1998) was applied to investigate mechanisms of spatial attention in location precuing. Observers were precued or simultaneously cued to identify 1 of 4 pseudocharacters embedded in various amounts of external noise. The cues were either central or peripheral. Both central and peripheral precuing significantly reduced threshold in the presence of high external noise (16% and 17.5%). Only peripheral precuing significantly reduced threshold in the presence of low, or no, external noise (11%). A perceptual template model identified different mechanisms of attention for central and peripheral precuing, external noise exclusion for central precuing, and a combination of external noise exclusion and stimulus enhancement (or equivalently, internal additive noise reduction) for peripheral cuing.In a high workload environment, a human operator might need to monitor a large number of information sources simultaneously. Whereas this might be accomplished by saccades, the eye movement system is limited by the relatively long time (about 200 ms) each saccade takes (Hallett, 1986). On the other hand, the existence of a faster spatial attention system was proposed about a century ago (Helmholtz, 186671911;Wundt, 1902), selecting regions of the visual field for further processing without eye movements. This view has been established by the more recent literature

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“…These metaphoric models of attention make strong suggestions about how attention operates, and in certain cases even admit quantitative applications. An alternative approach is to develop a formal perceptual decision structure and test models of attention effects by studying modulations of perceptual discriminability (signal and noise levels) in the cognitive processes (Dosher and Lu, 2000b;Lu and Dosher, 1998).…”

Section: Introductionmentioning

confidence: 99%

External Noise Distinguishes Mechanisms of Attention

Lü¹,

Dosher²

2005

Neurobiology of Attention

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102

148

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Attention to objects or features of objects affects performance on perceptual tasks such as detection, recognition, or identification. The speed or accuracy of task performance can be significantly influenced by changes in the state of attention, especially in complex task environments. The state of attention may be manipulated by specific environmental cues, or by decisions about allocation of attention induced by task demands. The challenge is to understand and predict these attention-mediated changes in task performance, and to identify the mechanisms by which attention is operating. A theoretical and empirical framework has been developed to directly assess the mechanisms of attention by systematically manipulating the amount and/or characteristics of the external noise added to the signal stimuli and measuring modulations of perceptual discriminability (signal and noise levels) in the cognitive processes. Three classes of attention mechanisms-stimulus enhancement, external noise exclusion, and internal noise reduction, each with its signature performance pattern, can be distinguished. Empirically, the two mechanisms of stimulus enhancement and external noise exclusion are shown to occur in different circumstances. A task-taxonomy of attention mechanisms is obtained by partitioning experiments in the literature according to several factors. The framework has also been extended to the assessment of spatial and temporal characteristics of the attention window, the coordination of multimodal auditory-visual cues in the performance of visual tasks, and the action of multitask load in performance.

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Noise Exclusion in Spatial Attention

Abstract: Abstract-Precue

Cited by 245 publications

References 39 publications

The discovery and comparison of symbolic magnitudes

The discovery and comparison of symbolic magnitudes

Spatial attention: Different mechanisms for central and peripheral temporal precues?

External Noise Distinguishes Mechanisms of Attention

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