Attentional Performance, Age and Scholastic Achievement in Healthy Children

Attentional processes in children play a critical role in daily school demands and accomplishments. Studies on the association of attentional processes with school achievement and age in healthy school children are scarce. The aim of the present study was to identify correlations between dimensions of attentional performance, scholastic achievement and age.An extensive testing battery was used to assess a wide range of attentional dimensions. A principal component analysis revealed three factors that are related to attentional performance (distractibility, lapses of attention, cognitive speed). Age was negatively associated with distractibility, lapses of attention and cognitive speed, indicating that distractibility and lapses of attention decreased with age in healthy children and resulted in lower cognitive speed.Attentional processes in healthy children should be measured in relation to distractibility, lapses of attention and cognitive speed

A search asymmetry for interocular conflict

When two different images are presented to the two eyes, the percept will alternate between the images (a phenomenon called binocular rivalry). In the present study, we investigate the degree to which such interocular conflict is conspicuous. By using a visual search task, we show that search for interocular conflict is near efficient (15 ms/item) and can lead to a search asymmetry, depending on the contrast in the display. We reconcile our findings with those of Wolfe and Franzel (1988), who reported inefficient search for interocular conflict (26 ms/item) and found no evidence for a search asymmetry. In addition, we provide evidence for the suggestion that differences in search for interocular conflict are contingent on the degree of abnormal fusion of the dissimilar images

Modulating attentional load affects numerosity estimation: evidence against a pre-attentive subitizing mechanism

Traditionally, the visual enumeration of a small number of items (1 to about 4), referred to as subitizing, has been thought of as a parallel and pre-attentive process and functionally different from the serial attentive enumeration of larger numerosities. We tested this hypothesis by employing a dual task paradigm that systematically manipulated the attentional resources available to an enumeration task. Enumeration accuracy for small numerosities was severely decreased as more attentional resources were taken away from the numerical task, challenging the traditionally held notion of subitizing as a pre-attentive, capacity-independent process. Judgement of larger numerosities was also affected by dual task conditions and attentional load. These results challenge the proposal that small numerosities are enumerated by a mechanism separate from large numerosities and support the idea of a single, attention-demanding enumeration mechanism

Searching for faces differs from categorization: Evidence from scenes and eye movements

This study examined whether the detection of frontal, ¾ and profile face views differs from their categorization as faces. Experiment 1 compared three tasks that required observers to determine the presence or absence of a face but varied in the extent to which they had to search for faces in simple displays and small or large scenes to make this decision. Performance was equivalent for all face views in simple displays and small scenes, but was notably slower for profile views when this required the search for faces in extended scene displays. This search effect was confirmed in Experiment 2, which compared observers’ eye movements with their response times to faces in visual scenes. These results demonstrate that the categorization of faces at fixation is dissociable from the detection of faces in space. Consequently, we suggest that face detection should be studied with extended visual displays, such as natural scenes

Saliency Benchmarking Made Easy: Separating Models, Maps and Metrics

Dozens of new models on fixation prediction are published every year and compared on open benchmarks such as MIT300 and LSUN. However, progress in the field can be difficult to judge because models are compared using a variety of inconsistent metrics. Here we show that no single saliency map can perform well under all metrics. Instead, we propose a principled approach to solve the benchmarking problem by separating the notions of saliency models, maps and metrics. Inspired by Bayesian decision theory, we define a saliency model to be a probabilistic model of fixation density prediction and a saliency map to be a metric-specific prediction derived from the model density which maximizes the expected performance on that metric given the model density. We derive these optimal saliency maps for the most commonly used saliency metrics (AUC, sAUC, NSS, CC, SIM, KL-Div) and show that they can be computed analytically or approximated with high precision. We show that this leads to consistent rankings in all metrics and avoids the penalties of using one saliency map for all metrics. Our method allows researchers to have their model compete on many different metrics with state-of-the-art in those metrics: "good" models will perform well in all metrics.Comment: published at ECCV 201

The control of attentional target selection in a colour/colour conjunction task

To investigate the time course of attentional object selection processes in visual search tasks where targets are defined by a combination of features from the same dimension, we measured the N2pc component as an electrophysiological marker of attentional object selection during colour/colour conjunction search. In Experiment 1, participants searched for targets defined by a combination of two colours, while ignoring distractor objects that matched only one of these colours. Reliable N2pc components were triggered by targets and also by partially matching distractors, even when these distractors were accompanied by a target in the same display. The target N2pc was initially equal in size to the sum of the two N2pc components to the two different types of partially matching distractors, and became superadditive from about 250 ms after search display onset. Experiment 2 demonstrated that the superadditivity of the target N2pc was not due to a selective disengagement of attention from task-irrelevant partially matching distractors. These results indicate that attention was initially deployed separately and in parallel to all target-matching colours, before attentional allocation processes became sensitive to the presence of both matching colours within the same object. They suggest that attention can be controlled simultaneously and independently by multiple features from the same dimension, and that feature-guided attentional selection processes operate in parallel for different target-matching objects in the visual field

Haptic pop-out of movable stimuli

When, in visual and haptic search, a target is easily found among distractors, this is called a pop-out effect. The target feature is then believed to be salient, and the search is performed in a parallel way. We investigated this effect with movable stimuli in a haptic search task. The task was to find a movable ball among anchored distractors or the other way round. Results show that reaction times were independent of the number of distractors if the movable ball was the target but increased with the number of items if the anchored ball was the target. Analysis of hand movements revealed a parallel search strategy, shorter movement paths, a higher average movement speed, and a narrower direction distribution with the movable target, as compared with a more detailed search for an anchored target. Taken together, these results show that a movable object pops out between anchored objects and this indicates that movability is a salient object feature. Vibratory signals resulting from the movable ball were found to be a reasonable explanation regarding the sensation responsible for the pop-out of movability

Searching for the Majority: Algorithms of Voluntary Control

Voluntary control of information processing is crucial to allocate resources and prioritize the processes that are most important under a given situation; the algorithms underlying such control, however, are often not clear. We investigated possible algorithms of control for the performance of the majority function, in which participants searched for and identified one of two alternative categories (left or right pointing arrows) as composing the majority in each stimulus set. We manipulated the amount (set size of 1, 3, and 5) and content (ratio of left and right pointing arrows within a set) of the inputs to test competing hypotheses regarding mental operations for information processing. Using a novel measure based on computational load, we found that reaction time was best predicted by a grouping search algorithm as compared to alternative algorithms (i.e., exhaustive or self-terminating search). The grouping search algorithm involves sampling and resampling of the inputs before a decision is reached. These findings highlight the importance of investigating the implications of voluntary control via algorithms of mental operations