Target Detection In Visual Search Research Articles

Target Detection in Visual Search: Unravelling the Pupillary Response

Target Detection in Visual Search: Unravelling the Pupillary Response

The effect of visual entrainment on target detection in visual search.

The effect of visual entrainment on target detection in visual search.

Improving target detection in visual search through the augmenting multi-sensory cues

The present experiment tested 60 individuals on a multiple screen, visual target detection task. Using a within-participant design, individuals received no-cue augmentation, an augmenting tactile cue alone, an augmenting auditory cue alone or both of the latter augmentations in combination. Results showed significant and substantive improvements in performance such that successful search speed was facilitated by more than 43%, errors of omission were reduced by 86% and errors of commission were reduced by more than 77% in the combinatorial cueing condition compared with the non-cued control. These outcomes were not a trade of performance efficiency for associated mental effort because recorded levels of cognitive workload were also reduced by more than 30% in the multi-cued circumstance compared with the control condition. When the tactile modality was incorporated it led to the highest gain in performance speed, when the auditory modality was incorporated, it led to the best levels of performance accuracy. The combined condition rendered the best of each from of performance increment. Reasons for this outcome pattern are discussed alongside their manifest practical benefits. Practitioner Summary: This experiment tested 60 individuals on a multiple screen, visual target detection task. Individuals received no-cue augmentation, tactile cue alone, an augmenting auditory cue alone or both of the latter augmentations in combination. Results showed significant and substantive improvements in the combinatorial cueing condition compared with the non-cued control.

Faster target selection in preview visual search depends on luminance onsets: behavioral and electrophysiological evidence

To investigate how target detection in visual search is modulated when a subset of distractors is presented in advance (preview search), we measured search performance and the N2pc component as an electrophysiological marker of attentional target selection. Targets defined by a color/shape conjunction were detected faster and the N2pc emerged earlier in preview search relative to a condition in which all items were presented simultaneously. Behavioral and electrophysiological preview benefits disappeared when stimuli were equiluminant with their background, in spite of the fact that targets were feature singletons among the new items in preview search. The results demonstrate that previewing distractors expedites the spatial selection of targets at early sensory-perceptual stages, and that these preview benefits depend on rapid attentional capture by luminance onsets.

Characteristic sounds make you look at target objects more quickly

When you are looking for an object, does hearing its characteristic sound make you find it more quickly? Our recent results supported this possibility by demonstrating that when a cat target, for example, was presented among other objects, a simultaneously presented "meow" sound (containing no spatial information) reduced the manual response time for visual localization of the target. To extend these results, we determined how rapidly an object-specific auditory signal can facilitate target detection in visual search. On each trial, participants fixated a specified target object as quickly as possible. The target's characteristic sound speeded the saccadic search time within 215-220 msec and also guided the initial saccade toward the target, compared with presentation of a distractor's sound or with no sound. These results suggest that object-based auditory-visual interactions rapidly increase the target object's salience in visual search.

What, when and how of target detection in visual search

When and how do we decide whether the target is present in the scene or not? There are surprisingly few quantitative models that address this question. We propose a generative model of visual search. First, the observer obtains stimulus information (corrupted by additive white noise of variance σ) at each location and time instant. Second, information across scene locations is combined using optimal Bayesian inference to compute the instantaneous evidence for target presence in the scene (log likelihood ratio of target presence vs. absence at time t). Third, the observer accumulates evidence over time and decides ‘yes’ if the accumulated evidence exceeds criterion ζ+Δ, ‘no’ if the evidence falls below criterion −ζ+Δ, and otherwise continues to observe the scene. Δ is a criterion-shift which depends on the target frequency, and the reward for different responses. This model has only 2 free parameters (noise σ, criterion ζ), compared to many parameters in drift diffusion models. The model can explain several search phenomena including how accuracy and RT are affected by set-size, target-distractor discriminability, distractor heterogeneity, target frequency and reward. It can capture the shape of the RT distribution in target present and absent trials for different tasks like feature, conjunction and spatial configuration search. It explains that rare targets are missed (Wolfe et. al, 2005) because decreasing target frequency (e.g., from 50% to 2%) shifts the starting point of the decision process closer to ‘no’ than ‘yes’ criterion, leading to high miss error rates, and fast abandoning of search. Our model predicts that increasing penalties on miss errors will decrease these errors and increase RTs. We validated these predictions through psychophysics experiments with 4 human subjects. To summarize, we have proposed a generative model of visual search that with only 2 free parameters, can explain a wide range of search phenomena.

What, when and how of target detection in visual search.

What, when and how of target detection in visual search.

Attention to features precedes attention to locations in visual search: evidence from electromagnetic brain responses in humans.

Single-unit recordings in macaque extrastriate cortex have shown that attentional selection of nonspatial features can operate in a location-independent manner. Here, we investigated analogous neural correlates at the neural population level in human observers by using simultaneous event-related potential (ERP) and event-related magnetic field (ERMF) recordings. The goals were to determine (1) whether task-relevant features are selected before attention is allocated to the location of the target, and (2) whether this selection reflects the locations of the relevant features. A visual search task was used in which the spatial distribution of nontarget items with attended feature values was varied independently of the location of the target. The presence of task-relevant features in a given location led to a change in ERP/ERMF activity beginning approximately 140 msec after stimulus onset, with a neural origin in the ventral occipito-temporal cortex. This effect was independent of the location of the actual target. This effect was followed by lateralized activity reflecting the allocation of attention to the location of the target (the well known N2pc component), which began at approximately 170 msec poststimulus. Current source localization indicated that the allocation of attention to the location of the target originated in more anterior regions of occipito-temporal cortex anterior than the feature-related effects. These findings suggest that target detection in visual search begins with the detection of task-relevant features, which then allows spatial attention to be allocated to the location of a likely target, which in turn allows the target to be positively identified.

A dynamic model of how feature cues guide spatial attention

We will describe a computational model of attention which explains the guidance of spatial attention by feedback within a distributed network. We hypothesize that feedback within the ventral pathway transfers the target template from prefrontal areas into intermediate areas like V4. The oculomotor circuit consisting of FEF, LIP and superior colliculus picks up this distributed activity and provides a continuous spatial reentry signal from premotor cells. In order to test this hypothesis, we simulate two experiments that require a response given a color cue. The first experiment indicates a parallel feature-based enhancement prior to any spatial selection. If two targets are behaviorally relevant, as in the second experiment, experimental findings indicate that subjects split their attention between two locations containing the searched feature. Our simulation results suggest that the split in attention between two foci is a transient effect occurring during competition. We predict that the time after cue presentation determines the state of this competition and ultimately the distribution of attention at different locations. In addition we provide simulation results to explain how reentrant processing through the oculomotor circuit might lead to variations of the time for target detection in visual search.