We used visual search to explore whether attention could be guided by Kanizsa-type subjective contour and subjective contours induced by line-ends. Unlike previous experiments, we compared search performance with subjective contours against performance with real, luminance contours and we had observers search for orientations or shapes produced by subjective contours rather than searching for the presence of the contours, themselves. Visual search for one orientation or shape among distractors of another orientation or shape was efficient when items were defined by luminance contours. Search was much less efficient among items defined by Kanizsa-type subjective contours. Search remained efficient when items were defined by subjective contours induced by line-ends. The difference between Kanizsa-type subjective contour and subjective contours induced by line-ends is consistent with physiological evidence suggesting that the brain mechanisms underlying the perception of these two kinds of subjective contours might be different.
Auckland, M.E., Cave, K.R., & Donnelly, N. (2007). Non-target objects can influence perceptual processes during object recognition. Psychonomic Bulletin and Review.
Previous experiments have shown that objects are recognized more readily in a semantically consistent visual context. However, the benefit from context could be explained by response bias, and may not reflect the influence of context on the perceptual processes of recognition or during representation. We conducted a six-alternative forced choice experiment to measure semantic and perceptual errors. A target object appeared briefly, surrounded by four context objects. The target was more accurately identified when the context consisted of objects semantically related to the target. The large number of semantic errors, which increased when the context presentation preceded the target, showed that response bias did account for a proportion of the context effect. Nonetheless, significant facilitation was still present after a bias correction. Recognition of an object can be affected by context not only when it is embedded in a coherent naturalistic scene, but also when it is simply near other related objects.
Chen, Z., & Cave, K.R. (2006) Reinstating object-based attention under positional certainty: The importance of subjective parsing. Perception & Psychophysics, 68, 992-1003.
Previous studies show that interference from flanking distractors can be modulated by the object organization of the scene. The experiments reported here test for object-based attention under conditions of positional certainty, which allows a narrow focus of attention to the target. Prior research has suggested that object-based attention does not arise in these circumstances, but the experiments presented here show that object-based attention can still appear if previous experience with the stimuli leads participants to interpret the stimulus as two separate objects. Two control experiments demonstrate that the appearance of object-based attention is not simply due to a widening of the focus of spatial attention. The presence of object-based attention in such a focusedattention task argues against an explanation of object-based attention based on priority in the order of visual search proposed by Shomstein and Yantis (2002).
Chen, Z., & Cave, K.R. (2006) When does visual attention select all features of a distractor? Journal of Experimental Psychology: Human Perception and Performance, 32, 1452-1464.
What happens after visual attention is allocated to an object? Although many theories of attention assume that all of its features are selected and processed, there has been little direct evidence that an irrelevant feature dimension of an attended non-target is processed. In 5 experiments presented here, we employed a singleton paradigm to investigate the effect of attention on non-target objects. Participants made a speeded feature discrimination of a target for which the response was either compatible or incompatible with an irrelevant feature dimension of a distractor. The results show that the irrelevant distractor features were processed to the point that they interfered with the response to the target. The response compatibility effect was observed even when the location of the target or of the distractor was invariant, although it was much weaker when both locations were invariant. These results demonstrate that in many circumstances an attended distractor is completely selected and fully processed, and the complete processing of distractors depends on a number of factors, many of which are related to the strength of attention to the distractor.
Cave, K.R., & Batty, M.J. (2006). From searching for features to searching for threat: Drawing the boundary between preattentive and attentive vision. Visual Cognition, 14, 629-646.
The distinction between preattentive and attentional processing has been a key element in many theories of attention, but there are conflicting claims as to which functions are performed preattentively, and which require attention. Recent studies suggest that stimuli associated with strong emotions or threat are effective at capturing and/or holding attention. Especially relevant for the question of preattentive vision are search experiments showing that emotional stimuli are sometimes found more quickly than neutral stimuli. An examination of these experiments indicates that there is no evidence that the threatening nature of stimuli is detected preattentively. There is evidence, however, that participants can learn to associate particular features, combinations of features, or configurations of lines with threat, and use them to guide search to threat-related targets. This debate highlights the importance of determining not only what information is encoded preattentively, but how target features that are used to guide search are specified.
Batty, M.J., Cave, K.R., & Pauli, P. (2005). Abstract stimuli associated with threat through conditioning cannot be detected preattentively. Emotion, 5, 418-430.
Studies of anxiety suggest that threat stimuli can be identified preattentively, but this conclusion is questionable because of possible low-level perceptual confounds. Two experiments used visual search tasks in which abstract shapes were conditioned to carry neutral or negative valence. Experiment 1 found generally faster responses to threat-associated abstract stimuli but no evidence that they were detected preattentively, irrespective of trait anxiety level. A similar pattern was found in Experiment 2, in which individuals high in snake or spider fear showed no evidence of preattentive detection of abstract stimuli associated with their feared object. In contrast, implicit behavioral measures showed significant effects of conditioning, demonstrating that targets associated with threat were negatively evaluated in these experiments.
Sobel, K.V., & Cave, K.R. (2002) The roles of salience and strategy in conjunction search. Journal of Experimental Psychology: Human Perception and Performance, 28, 1055-1070.
In some cases the search for a conjunction target proceeds through the smaller group of elements in the display (e.g., E. Zohary & S. Hochstein, 1989), while in others search is limited to those elements that share a particular feature with the target (e.g., N. A. Kaptein, J. Theeuwes, & A. H. C. van der Heijden, 1995). In 6 experiments, participants searched for a conjunction target from among displays consisting of various proportions of 2 distractor types. Smaller-group search was more prevalent than target-feature search with denser displays and with features that were highly discriminable. Explicit instructions to limit search to a specific feature affected performance only when the discriminability of the guiding feature was much greater than the other target feature. Together, these experiments show that bottom-up factors have more influence in guiding conjunction searches than previously thought.
Cave, K.R. (2001). Selection can be performed effectively without temporal binding, but could be even more effective with it. Visual Cognition, 8, 467-487.
Experiments using spatial cues and spatial probes provide strong evidence for an attention mechanism that chooses a location and selects all information at that location. This selection process can work very quickly; so quickly that selection probably begins before segmentation and grouping. It can be implemented in a neural network simply and efficiently without temporal binding.
In conjunction with this spatial attention, however, temporal binding can potentially enhance visual selection in complex scenes. First, it would allow a target object to be selected without also selecting a superimposed distractor. Second, it could maintain representations of objects after attention has moved to another object. Third, it could allow multiple parts of an object or scene to be selected, segmented, and analyzed simultaneously. Thus, temporal synchrony should be more likely to appear during tasks with overlapping targets and distractors, and tasks that require that multiple objects or multipart objects be analysed and remembered simultaneously.
Kim, M.-S., & Cave, K.R. (2001). Perceptual grouping via spatial selection in a focused-attention task. Vision Research, 41, 611-624.
Theories of attention can be separated into those that select by location, and those that select by location-invariant representation. Experiments demonstrating stronger interference or facilitation from distractors grouped by nonspatial features with the target than ungrouped distractors have been considered as evidence for the selection of location-invariant representations. However, few studies have measured spatial attention directly at the locations of the grouped or ungrouped objects. In these experiments subjects responded to spatial probes (dots) while also identifying a cued target letter among distractors. Probe responses were faster for distractor locations with the target color than for those with the non-target color, implying that target-color locations receive more attention. This pattern of spatial attention may explain why target-color distractors interfere more with target identification than nontarget-color distractors. These results suggest that although attention can be directed by nonspatial properties such as grouping by color or organization of the scene into objects, selection may ultimately be based on location.
Davidson, H., Cave, K.R., & Sellner, D. (2000). Differences in visual attention and task interference between males and females reflect differences in brain laterality. Neuropsychologia, 38, 508-519.
Two cognitive tasks (a letter memory task and a spatial memory task) designed to selectively activate the left or right hemisphere were combined with attentional probe tasks to measure how hemispheric activation affects attention to left and right hemifields. The probe task in Experiment 1 required the identification of digits in the left and right hemifield. During the letter task, male subjects identifed more probes from the left hemifield than from the right. Their accuracy varied little across the two hemifields during the dots task.
Experiment 2 tested whether this pattern is due to either spatial attention or interference in character processing. Instead of identifying digits, the probe task required subjects to respond to a black square that appeared in the periphery of the screen. For male subjects, the pattern was the opposite of that from Experiment 1. During the letter task they responded faster to the probe in the right hemifield than in the left hemifield. Their response times were equivalent across the two hemifields during the dots task.
These results indicate two separate effects of laterality in male subjects. The activation of one hemisphere produced more attention to the contralateral hemifield in Experiment 2, and the letter memory task interfered with the processing of other characters in the right visual field more than those in the left visual field in Experiment 1. Neither of these effects appeared in female subjects, corroborating earlier claims that female brains are less lateralized than male brains.
Wolfe, J.M., & Cave, K.R. (1999). The psychophysical evidence for a binding problem in human vision. Neuron, 24, 11-17.
This paper reviews the psychophysical evidence on the binding problem. Objects have features like color, size, orientation, and so forth. Under some circumstances, measures of performance and/or reports of stimulus appearance suggest that those features are not tightly bound to their objects. Under most natural circumstances, however, we do not encounter problems with unbound features. The nature of the binding problem has important implications for our understanding of visual and attentional mechanisms.
The normal operation of these mechanisms might hide the binding problem in everyday vision.
Kim, M.-S., & Cave, K.R. (1999). Grouping effects on spatial attention in visual search. Journal of General Psychology, 126, 326-352.
In visual search tasks, spatial attention selects the locations containing a target or a distractor with one of the target's features, implying spatial attention driven by target features (Kim & Cave, 1995). The current study measures the effects of location-based grouping processes in visual search. In searches for a color/shape combination (conjunction search), spatial probes show that a cluster of same-color or same-shape elements surrounding the target are grouped and selected together. However, in searches for a shape target (feature search), evidence for grouping by an irrelevant feature dimension is weaker or nonexistent. Grouping processes can aid search for a visual target by selecting groups of locations that share a common feature, although there is little or no grouping by an irrelevant feature when the target is defined by a unique salient feature.
Cave, K.R. (1999). The FeatureGate Model of Visual Selection. Psychological Research, 62, 182-194.
The model presented here is an attempt to explain the results from a number of different studies in visual attention, including parallel feature searches and serial conjunction searches, variations in search slope with variations in feature contrast and individual subject differences, attentional gradients triggered by cuing, feature-driven spatial selection, split attention, inhibition of distractor locations, and flanking inhibition. The model is implemented in a neural network consisting of a hierarchy of spatial maps. Attentional gates control the flow of information from each level of the hierarchy to the next. The gates are jointly controlled by a Bottom-Up System favoring locations with unique features, and a Top-Down System favoring locations with features designated as target features. Because the gating of each location depends on the features present there, the model is called FeatureGate.
Cave, K.R., & Bichot, N.P. (1999). Visuo-spatial attention: Beyond a spotlight model. Psychonomic Bulletin and Review, 6, 204-223.
Much of the research in visual attention has been driven by the spotlight metaphor. This metaphor has been useful over many years for generating experimental questions in attention research. However, theories and models of visual selection have reached such a level of complexity that debate now centers around more specific questions about the nature of attention. In this review, the general question "Is visual attention like a spotlight?" is broken down into seven specific questions concerning the nature of visual attention, and the evidence relevant to each is examined. The answers to these specific questions provide important clues about why visual selection is necessary and what purpose attention plays in visual cognition.
Kim, M.-S., & Cave, K.R. (1999). Top-down and Bottom-up Attentional Control: On the Nature of Interference from a Salient Distractor. Perception and Psychophysics, 61, 1009-1023.
Two experiments using spatial probes measured the temporal and spatial interaction between top-down control of attention and bottom-up interference from a salient distractor in visual search. Subjects searched for a square among circles, ignoring color. Probe response times showed that a color singleton distractor could draw attention to its location in the early stage of visual processing (before 100 msec SOA), but only when the color singleton distractor was located far from the target. Apparently the bottom-up activation of the singleton distractor's location is affected early on by local interactions with nearby stimulus locations. Moreover, probe results showed a singleton distractor did not receive attention after extended practice. These results suggest top-down control of attention is possible at an early stage of visual processing. In the long SOA condition (150 msec SOA), spatial attention selects the target location over distractor locations, and this tendency occurred with or without extended practice.
Bichot, N.P., Cave, K.R., & Pashler, H. (1999). Visual Selection Mediated by Location: Feature-based Selection of Noncontiguous Locations. Perception and Psychophysics, 61, 403-423.
Experiments using two different methods and three types of stimuli tested whether stimuli at nonadjacent locations could be selected simultaneously. In one set of experiments, subjects attended to red digits presented in multiple frames with green digits. Accuracy was no better when red digits appeared successively than when pairs of red digits occurred simultaneously, implying allocation of attention to the two locations simultaneously. Different tasks involving oriented grating stimuli produced the same result. The final experiment demonstrated split attention with an array of spatial probes. When the probe at one of two target locations was correctly reported, the probe at the other target location was more often reported correctly than any of the probes at distractor locations, including those between the targets. Together these experiments provide strong converging evidence that when two targets were easily discriminated from distractors by a basic property, spatial attention can be split across both locations.
Cepeda, N.J., Cave, K.R., Bichot, N.P. & Kim, M.-S. (1998). Spatial selection via feature-driven inhibition of distractor locations. Perception and Psychophysics, 60, 727-746.
The allocation of spatial attention was measured with detection probes at different locations. Response times were faster for probes at the location of the target digit, which subjects reported, than at the locations of distractor digits, which they ignored. Probes at blank locations between stimuli produced fast responses, indicating that selection was accomplished by inhibiting distractor locations but not other areas. Unlike earlier studies using location cuing with simpler stimuli, these experiments showed no attentional differences across horizontal or vertical midlines. Attention varied little with distance from the target, although blank locations far from the target were somewhat less attended than those near the target, and attention was only slightly affected by expectations for stimulus location. This task demonstrates a form of feature-driven spatial attention, in which locations with objects lacking target features are inhibited.
Cave, K.R. & Zimmerman, J.M. (1997). Flexibility in spatial attention before and after practice. Psychological Science, 8, 399-403.
These experiments used spatial probes to measure how spatial attention is allocated across the visual field during search for a target letter in an 8-letter array. There were three main findings. (1) Attentional strength is flexibly adjusted according to the confusability between target and distractors. (2) Distractor locations near the target receive more inhibition than those farther from the target, indicating that the nearby distractors interfere more with target identification. (3) Despite the fact that consistent practice improves search rate, it does not diminish the strength of spatial attention in this task.
Kim, M.-S., & Cave, K.R. (1995). Spatial attention in visual search for features and feature conjunctions. Psychological Science, 6, 376-380.
Spatial attention was measured in visual search tasks using a spatial probe. Both speed and accuracy measures showed that in a conjunction task, spatial attention was allocated to locations according to the presence of target features. Also, contrary to some predictions, spatial attention was used when a clearly distinguishable feature defined the target. The results raise questions about any account that assumes separate mechanisms for feature and conjunction search. The probe method demonstrated here allows a very direct measurement of attentional allocation, and may uncover aspects of selection not revealed by visual search.