Distinguishing Blocking From Attenuation in Visual Selective Attention

Yiǧit-Elliott, Serap; Palmer, John; Moore, Cathleen M.

doi:10.1177/0956797611407927

Cited by 15 publications

(14 citation statements)

References 40 publications

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“…We tested and confirmed this prediction. These results parallel other reports (Palmer and Moore, 2009; Yigit-Elliott et al, 2011) that show that high contrast distracters (foils) can be incorrectly selected, leading to errors in behavioral performance. Similarly, searching for a high contrast target among low contrast distracters is less impaired relative to searching for a low contrast target among high contrast distracters when attention is allocated elsewhere (Braun, 1994) or V4 is lesioned (Schiller and Lee, 1991).…”

Section: Discussionsupporting

confidence: 90%

Attentional Enhancement via Selection and Pooling of Early Sensory Responses in Human Visual Cortex

Pestilli

Carrasco

Heeger

et al. 2011

Neuron

185

283

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Summary To characterize the computational processes by which attention improves behavioral performance, we measured activity in visual cortex with functional magnetic resonance imaging as humans performed a contrast-discrimination task with focal and distributed attention. Focal attention yielded robust improvements in behavioral performance that were accompanied by increases in cortical responses. Using a quantitative analysis, we determined that if performance were limited only by the sensitivity of the measured sensory signals, the improvements in behavioral performance would have corresponded to an unrealistically large (approximately 400%) reduction in response variability. Instead, behavioral performance was well characterized by a pooling and selection process for which the largest sensory responses, those most strongly modulated by attention, dominated the perceptual decision. This characterization predicts that high contrast distracters that evoke large sensory responses should have a negative impact on behavioral performance. We tested and confirmed this prediction. We conclude that attention enhanced behavioral performance predominantly by enabling efficient selection of the behaviorally relevant sensory signals.

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Section: Discussionsupporting

confidence: 90%

Attentional Enhancement via Selection and Pooling of Early Sensory Responses in Human Visual Cortex

Pestilli

Carrasco

Heeger

et al. 2011

Neuron

185

283

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“…Quantitative metrics that are diagnostic of attention are (i) improvements in perceptual accuracy and (ii) shortening of reaction times. Using these metrics, the benefits of attention have been shown in primates to vary dramatically with the strength of a target stimulus (9, 10), its location relative to the locus of attention (11,12), and the presence and strength of distracting stimuli (13,14). In this study, we demonstrate these same benefits of attention in chickens.…”

supporting

confidence: 63%

Visuospatial selective attention in chickens

Sridharan

Ramamurthy

Schwarz

et al. 2014

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

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Voluntary control of attention promotes intelligent, adaptive behaviors by enabling the selective processing of information that is most relevant for making decisions. Despite extensive research on attention in primates, the capacity for selective attention in nonprimate species has never been quantified. Here we demonstrate selective attention in chickens by applying protocols that have been used to characterize visual spatial attention in primates. Chickens were trained to localize and report the vertical position of a target in the presence of task-relevant distracters. A spatial cue, the location of which varied across individual trials, indicated the horizontal, but not vertical, position of the upcoming target. Spatial cueing improved localization performance: accuracy (d′) increased and reaction times decreased in a space-specific manner. Distracters severely impaired perceptual performance, and this impairment was greatly reduced by spatial cueing. Signal detection analysis with an "indecision" model demonstrated that spatial cueing significantly increased choice certainty in localizing targets. By contrast, error-aversion certainty (certainty of not making an error) remained essentially constant across cueing protocols, target contrasts, and individuals. The results show that chickens shift spatial attention rapidly and dynamically, following principles of stimulus selection that closely parallel those documented in primates. The findings suggest that the mechanisms that control attention have been conserved through evolution, and establish chickens-a highly visual species that is easily trained and amenable to cutting-edge experimental technologiesas an attractive model for linking behavior to neural mechanisms of selective attention.T he capacity to select particular locations or stimuli for differential analysis and decision making is essential for any animal to behave intelligently in a complex environment. It follows that neural mechanisms that enable this capacity must have appeared early in evolution (1). In humans, and nonhuman primates, selective attention enables such adaptive behavior by selecting from all possible information the information that is most relevant for making decisions (2, 3). However, little is known about whether the capacity for selective attention exists in nonprimate vertebrate species.Studies that were intended to measure selective attention in nonprimate species have produced inconclusive results for several reasons. First, much of the previous work has inferred the capacity for selective attention based on selective learning or selective reporting of specific cue features, both in birds (4) and in rodents (5). For example, in highly cited work on feature-based attention (4), pigeons were reinforced for pecking on targets that contained combinations of two features (e.g., color and shape). In later trials, when the features were presented individually, they pecked almost exclusively on targets with only one of the two features (e.g., color, ignoring shape). The results ...

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“…The spatial extent of the attention field has been reported to be flexible in size and has been experimentally manipulated by introducing uncertainty about the location of the upcoming target (Castiello & Umilta, 1990; Datta & DeYoe, 2009; Eriksen & St James, 1986; Herrmann et al, 2010; Muller, Bartelt, Donner, Villringer, & Brandt, 2003; Yigit-Elliott et al, 2011). This flexibility, however, had previously not been demonstrated for featural attention.…”

Section: Discussionmentioning

confidence: 99%

“…Spatial attention has been shown to robustly modulate responses to stimulus contrast in behavioral (Carrasco, Penpeci-Talgar, & Eckstein, 2000; Herrmann et al, 2010; Ling & Carrasco, 2006; Lu & Dosher, 1998; Morrone, Denti, & Spinelli, 2002, 2004; Pestilli & Carrasco, 2005; Pestilli, Ling, & Carrasco, 2009; Pestilli, Viera, & Carrasco, 2007; Yigit-Elliott, Palmer, & Moore, 2011), single unit (Buracas & Boynton, 2007; Li, Lu, Tjan, Dosher, & Chu, 2008; Martinez-Trujillo & Treue, 2002; McAdams & Reid, 2005; Reynolds & Chelazzi, 2004; Reynolds et al, 2000; Williford & Maunsell, 2006) and neuroimaging studies (Buracas & Boynton, 2007; Liu, 2005; Lu, Li, Tjan, Dosher, & Chu, 2011; Murray & He, 2006; Pestilli, 2011). Yet, neither behavioral nor neurophysiology studies have systematically characterized the contrast dependence of FBA.…”

Section: Introductionmentioning

confidence: 99%

Feature-based attention enhances performance by increasing response gain

2012

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Covert spatial attention can increase contrast sensitivity either by changes in contrast gain or by changes in response gain, depending on the size of the attention field and the size of the stimulus (Herrmann, Montaser-Kouhsari, Carrasco, & Heeger, 2010), as predicted by the normalization model of attention (Reynolds & Heeger, 2009). For feature-based attention, unlike spatial attention, the model predicts only changes in response gain, regardless of whether the featural extent of the attention field is small or large. To test this prediction, we measured the contrast dependence of feature-based attention. Observers performed an orientation-discrimination task on a spatial array of grating patches. The spatial locations of the gratings were varied randomly so that observers could not attend to specific locations. Feature-based attention was manipulated with a 75% valid and 25% invalid pre-cue, and the featural extent of the attention field was manipulated by introducing uncertainty about the upcoming grating orientation. Performance accuracy was better for valid than for invalid pre-cues, consistent with a change in response gain, when the featural extent of the attention field was small (low uncertainty) or when it was large (high uncertainty) relative to the featural extent of the stimulus. These results for feature-based attention clearly differ from results of analogous experiments with spatial attention, yet both support key predictions of the normalization model of attention.

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Distinguishing Blocking From Attenuation in Visual Selective Attention

Cited by 15 publications

References 40 publications

Attentional Enhancement via Selection and Pooling of Early Sensory Responses in Human Visual Cortex

Attentional Enhancement via Selection and Pooling of Early Sensory Responses in Human Visual Cortex

Visuospatial selective attention in chickens

Feature-based attention enhances performance by increasing response gain

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