Dimensional weighting in cross-dimensional singleton conjunction search.

In order to efficiently deploy our limited visual processing resources, we must decide what information is relevant and to be prioritized and what information should rather be ignored. To detect visual information that we know is relevant but that is not very salient, we need to set our system to prioritize and combine information from different visual dimensions (e.g., size, color, motion). Four experiments examined the allocation of processing resources across different visual dimensions when observers searched for a singleton target defined by a conjunction of size (primary dimension: the target was always large) with either color or motion (secondary dimension: variable across trials) within heterogeneously sized, colored, and moving distractors. The results revealed search reaction times to be substantially increased in a given trial in which the secondary target dimension was changed from the preceding trial--indicative of a suboptimal distribution of dimensional weights carried over from the previous trial and of attentional weight being bound by the (need to filter within the) primary dimension, thereby reducing the weight available for processing the secondary dimensions. Semantic precueing of the secondary dimension and visual marking of the search-irrelevant items in the primary dimension reduced these costs significantly. However, observers were limited in their ability to implement both top-down sets simultaneously. These findings argue in favor of a parallel distribution of dimensional processing resources across multiple visual dimensions and, furthermore, that visual marking releases attentional weight bound to the primary dimension, thus permitting more efficient (parallel) processing in the secondary dimensions.

[1]  H. J. Muller,et al.  Visual search for singleton feature targets across dimensions: Stimulus- and expectancy-driven effects in dimensional weighting. , 2003, Journal of experimental psychology. Human perception and performance.

[2]  H. Egeth,et al.  Searching for conjunctively defined targets. , 1984, Journal of experimental psychology. Human perception and performance.

[3]  A. Treisman,et al.  A feature-integration theory of attention , 1980, Cognitive Psychology.

[4]  J. Wolfe,et al.  Changing your mind: on the contributions of top-down and bottom-up guidance in visual search for feature singletons. , 2003, Journal of experimental psychology. Human perception and performance.

[5]  A. Treisman.  Features and Objects: The Fourteenth Bartlett Memorial Lecture , 1988, The Quarterly journal of experimental psychology. A, Human experimental psychology.

[6]  C. Olivers,et al.  Current versus past ambiguity in intertrial priming , 2012 .

[7]  Z Li,et al.  Contextual influences in V1 as a basis for pop out and asymmetry in visual search. , 1999, Proceedings of the National Academy of Sciences of the United States of America.

[8]  Hermann J. Müller,et al.  Sources of Top–Down Control in Visual Search , 2009, Journal of Cognitive Neuroscience.

[9]  Jan Theeuwes,et al.  SEARCH FOR A CONJUNCTIVELY DEFINED TARGET CAN BE SELECTIVELY LIMITED TO A COLOR-DEFINED SUBSET OF ELEMENTS , 1995 .

[10]  Derrick G. Watson,et al.  Fractionating the preview benefit in search: dual-task decomposition of visual marking by timing and modality. , 2002, Journal of experimental psychology. Human perception and performance.

[11]  H. Müller,et al.  Searching for unknown feature targets on more than one dimension: Investigating a “dimension-weighting” account , 1996, Perception & psychophysics.

[12]  Ralph Weidner,et al.  Dimensional weighting of primary and secondary target-defining dimensions in visual search for singleton conjunction targets , 2009, Psychological research.

[13]  Jeff Miller,et al.  Divided attention: Evidence for coactivation with redundant signals , 1982, Cognitive Psychology.

[14]  H J Müller,et al.  Top-down controlled visual dimension weighting: an event-related fMRI study. , 2002, Cerebral cortex.

[15]  G. Humphreys,et al.  Visual marking: prioritizing selection for new objects by top-down attentional inhibition of old objects. , 1997, Psychological review.

[16]  B. C. Motter,et al.  The guidance of eye movements during active visual search , 1998, Vision Research.

[17]  Harold Pashler,et al.  A Boolean map theory of visual attention. , 2007, Psychological review.

[18]  Zhaoping Li,et al.  Psychophysical Tests of the Hypothesis of a Bottom-Up Saliency Map in Primary Visual Cortex , 2007, PLoS Comput. Biol..

[19]  Joseph Krummenacher,et al.  Visual search for dimensionally redundant pop-out targets: parallel-coactive processing of dimensions is location specific. , 2002, Journal of experimental psychology. Human perception and performance.

[20]  H. Müller,et al.  Visual search for dimensionally redundant pop-out targets: Evidence for parallel-coactive processing of dimensions , 2001, Perception & psychophysics.

[21]  G. Humphreys,et al.  When visual marking meets the attentional blink: More evidence for top-down, limited capacity inhibition , 2002 .

[22]  H J Müller,et al.  Visual search for singleton feature targets within and across feature dimensions , 1995, Perception & psychophysics.

[23]  J. Wolfe,et al.  Guided Search 2.0 A revised model of visual search , 1994, Psychonomic bulletin & review.

[24]  Joseph Krummenacher,et al.  Inter-trial and redundant-signals effects in visual search and discrimination tasks: Separable pre-attentive and post-selective effects , 2010, Vision Research.