Comparing the time course and efficacy of spatial and feature-based attention

Liu, Taosheng; Stevens, Sean T.; Carrasco, Marisa

doi:10.1016/j.visres.2006.09.017

Cited by 156 publications

(165 citation statements)

References 31 publications

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“…The transition from guidance to selection is therefore marked by the transition from feature-selective activation patterns that are triggered in a spatially global fashion across the visual field to spatially specific modulations of neural responses to potentially task-relevant objects. In contrast to the common assumption that spatial attention is generally faster than attention for features [37,38], feature-based attention should precede spatial attention during visual search when the location of target objects is not known in advance [39].…”

Section: Selectionmentioning

confidence: 84%

The neural basis of attentional control in visual search

Eimer

2014

Trends in Cognitive Sciences

239

205

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How do we localize and identify target objects among distractors in visual scenes? The role of selective attention in visual search has been studied for decades, and the outlines of a general processing model are now beginning to emerge. Attentional processes unfold in real time, and this review describes four temporally and functionally dissociable stages of attention in visual search (preparation, guidance, selection, and identification). Insights from neuroscientific studies of visual attention suggest that our ability to find target objects in visual search is based on processes that operate at each of these four stages in close association with working memory and recurrent feedback mechanisms.

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Section: Selectionmentioning

confidence: 84%

The neural basis of attentional control in visual search

Eimer

2014

Trends in Cognitive Sciences

239

205

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“…The time constant of the attentional modulation chosen here (∼150 ms) is consistent with the temporal dynamics of stimulus-driven attention measured in psychophysical experiments. Stimulus-driven attention peaks around 100-120 ms after a trigger stimulus, whereas goal-driven attention requires more time (∼300 ms) to be deployed (50)(51)(52). The speed of stimulus-driven attention in rivalry could be slower than that typically measured in studies of exogenous attention, because the changes in neural activity during rivalry are less abrupt than those evoked by a high-contrast brief cue typically used to summon attention.…”

Section: Discussionmentioning

confidence: 99%

Attention model of binocular rivalry

Rankin

Rinzel

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

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When the corresponding retinal locations in the two eyes are presented with incompatible images, a stable percept gives way to perceptual alternations in which the two images compete for perceptual dominance. As perceptual experience evolves dynamically under constant external inputs, binocular rivalry has been used for studying intrinsic cortical computations and for understanding how the brain regulates competing inputs. Converging behavioral and EEG results have shown that binocular rivalry and attention are intertwined: binocular rivalry ceases when attention is diverted away from the rivalry stimuli. In addition, the competing image in one eye suppresses the target in the other eye through a pattern of gain changes similar to those induced by attention. These results require a revision of the current computational theories of binocular rivalry, in which the role of attention is ignored. Here, we provide a computational model of binocular rivalry. In the model, competition between two images in rivalry is driven by both attentional modulation and mutual inhibition, which have distinct selectivity (feature vs. eye of origin) and dynamics (relatively slow vs. relatively fast). The proposed model explains a wide range of phenomena reported in rivalry, including the three hallmarks: (i) binocular rivalry requires attention; (ii) various perceptual states emerge when the two images are swapped between the eyes multiple times per second; (iii) the dominance duration as a function of input strength follows Levelt's propositions. With a bifurcation analysis, we identified the parameter space in which the model's behavior was consistent with experimental results.B inocular rivalry is a visual phenomenon in which perception alternates between incompatible monocular images presented to the two eyes. During binocular rivalry, perceptual experience evolves dynamically while the external inputs are held constant. Binocular rivalry thereby provides an opportunity to gain insights about the intrinsic cortical computations underlying visual perception (1, 2).In conventional models of binocular rivalry, the competition between two percepts has been characterized as mutual inhibition between two populations of neurons selective for each of the two stimuli (3-11). Notwithstanding the differences in their details, these models consider the neural processing underlying binocular rivalry to be an automatic process. These models predict, therefore, that the dynamics of binocular rivalry are influenced mainly by bottom-up sensory inputs.Converging experimental evidence has shown, however, that binocular rivalry also depends on attention (for a review, see ref.12). First, EEG has been used to measure a neural correlate of the perceptual alternations during binocular rivalry when observers pay attention to the rival stimuli (13). However, this rivalry-induced modulation of the EEG signal is largely or entirely eliminated when attention is diverted away from the stimuli (14). Second, behavioral experiments comparing the perceptual cons...

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“…For exogenous cues, interstimulus intervals (ISIs) of 50 ms were sufficient to produce a cueing effect, whereas for endogenous cues, an ISI of 200 ms or more is needed in order to observe a cueing effect (Liu, Stevens, & Carrasco, 2007;Yeshurun, Montagna, & Carrasco, 2008). The differential time course might be due to endogenous attention shifts being slower or needing additional time to decode the information carried by the symbolic cue (Eimer, 2000).…”

Section: Peripheral and Central Spatial Cueingmentioning

confidence: 99%

Textures shape the attentional focus: Evidence from exogenous and endogenous cueing

Feldmann-Wüstefeld

Schubö

2013

Atten Percept Psychophys

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The spatial cueing paradigm (Posner Quarterly Journal of Experimental Psychology 32:3-25, 1980) has often been used to investigate the time course of the deployment of visual attention in space. In a series of eight experiments we investigated whether spatial cues would not only enhance processing of stimuli presented at cued locations, but also enhance processing of the entire texture in which the stimuli were presented. Results showed highest accuracy for responses to stimuli presented at cued locations, a replication of the traditional cueing effect (Posner 1980). Additionally, stimuli presented at uncued locations were responded to with higher accuracy when they were presented inside the same texture as the cued location, as compared with stimuli presented outside the texture with the cued location. To investigate this texture advantage for both automatic and voluntary attention deployment, exogenous and endogenous cues were used. The texture advantage was observed for short interstimulus intervals (ISIs) of 50 and 100 ms for exogenous cues and for a longer ISI of 200 ms for endogenous cues. These findings indicate that the arrangement of task-irrelevant visual stimuli also can have a large impact on the cueing effect. This suggests that visual spatial attention spreads texture-wise across the visual field. Control experiments revealed that the homogeneity within texture elements contributes most to the effect but that the texture advantage is a function of both orientation contrast at the texture border and homogeneity within texture elements.

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Comparing the time course and efficacy of spatial and feature-based attention

Cited by 156 publications

References 31 publications

The neural basis of attentional control in visual search

The neural basis of attentional control in visual search

Attention model of binocular rivalry

Textures shape the attentional focus: Evidence from exogenous and endogenous cueing

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