Literature DB >> 12916667

Dynamics of attention in depth: evidence from multi-element tracking.

Lavanya Viswanathan1, Ennio Mingolla.   

Abstract

We examined the allocation of attention in depth using a multi-element tracking paradigm. Observers were required to track a predefined subset of from two to eight elements in displays containing up to sixteen identical moving elements. We first show that depth cues, such as binocular disparity and occlusion through T-junctions, improve performance in a multi-element tracking task in the case where element boundaries are allowed to intersect in the depiction of motion in a single frontoparallel plane. We also show that the allocation of attention across two perceptually distinguishable planar surfaces, either frontoparallel or receding at a slanting angle and defined by coplanar elements, is easier than allocation of attention within a single surface. The same result was not found when attention was required to be deployed across items of two-color populations rather than across items of a single color. Our results suggest that, when surface information does not suffice to distinguish between targets and distractors that are embedded in these surfaces, division of attention across two surfaces aids in tracking moving targets. A final experiment with populations of elements moving within distinct volumes produced similar results, suggesting that spatial separation in three dimensions, rather than confinement to surfaces as such, may explain the improved performance for the two-surface case.

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Year:  2002        PMID: 12916667     DOI: 10.1068/p3432

Source DB:  PubMed          Journal:  Perception        ISSN: 0301-0066            Impact factor:   1.490


  14 in total

1.  Swapping or dropping? Electrophysiological measures of difficulty during multiple object tracking.

Authors:  Trafton Drew; Todd S Horowitz; Edward K Vogel
Journal:  Cognition       Date:  2012-11-07

2.  Direction information in multiple object tracking is limited by a graded resource.

Authors:  Todd S Horowitz; Michael A Cohen
Journal:  Atten Percept Psychophys       Date:  2010-10       Impact factor: 2.199

3.  The early attentional pancake: Minimal selection in depth for rapid attentional cueing.

Authors:  Ryan E O'Donnell; Kyrie H Murawski; Ella Herrmann; Jesse Wisch; Garrett D Sullivan; Brad Wyble
Journal:  Atten Percept Psychophys       Date:  2022-07-07       Impact factor: 2.157

4.  Automatic feature-based grouping during multiple object tracking.

Authors:  Gennady Erlikhman; Brian P Keane; Everett Mettler; Todd S Horowitz; Philip J Kellman
Journal:  J Exp Psychol Hum Percept Perform       Date:  2013-03-04       Impact factor: 3.332

5.  Evidence for the effect of depth on visual working memory.

Authors:  Jiehui Qian; Jiaofeng Li; Kaiyue Wang; Shengxi Liu; Quan Lei
Journal:  Sci Rep       Date:  2017-07-25       Impact factor: 4.379

6.  Binocular vision supports the development of scene segmentation capabilities: Evidence from a deep learning model.

Authors:  Ross Goutcher; Christian Barrington; Paul B Hibbard; Bruce Graham
Journal:  J Vis       Date:  2021-07-06       Impact factor: 2.240

7.  Healthy older observers show equivalent perceptual-cognitive training benefits to young adults for multiple object tracking.

Authors:  Isabelle Legault; Rémy Allard; Jocelyn Faubert
Journal:  Front Psychol       Date:  2013-06-06

8.  Visual search in depth: The neural correlates of segmenting a display into relevant and irrelevant three-dimensional regions.

Authors:  Katherine L Roberts; Harriet A Allen; Kevin Dent; Glyn W Humphreys
Journal:  Neuroimage       Date:  2015-07-26       Impact factor: 6.556

9.  Effect of age and stereopsis on a multiple-object tracking task.

Authors:  Marjolaine Plourde; Marie-Eve Corbeil; Jocelyn Faubert
Journal:  PLoS One       Date:  2017-12-15       Impact factor: 3.240

10.  Effect of depth information on multiple-object tracking in three dimensions: A probabilistic perspective.

Authors:  James R H Cooke; Arjan C Ter Horst; Robert J van Beers; W Pieter Medendorp
Journal:  PLoS Comput Biol       Date:  2017-07-20       Impact factor: 4.475

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