Divided attention impairs detection of simple visual features

Covert spatial attention allows us to prioritize processing at relevant locations. There is substantial evidence that perception is poorer when attention is distributed across multiple locations than when attention is focused on a single location. However, recent work suggests that may not always be the case: divided attention does not appear to impair detection of simple visual features that are represented in primary visual cortex. Here, we re-examined this possibility. In two experiments, observers detected a simple target (a vertical Gabor), and we manipulated whether attention was focused at one location (focal-cue condition) or distributed across two locations (distributed-cue condition). In Experiment 1, targets could appear independently at each location. Thus, observers needed to judge target presence for each location separately in the distributed-cue condition. Under these conditions, we found a robust cost of dividing attention. In this experiment, the cost of dividing attention could reflect either a limit in perceptual processing or a limit in decision making. Therefore, in Experiment 2, we simplified the task to more directly test whether dividing attention impairs perceptual processing of the target. Specifically, only one target could appear on each trial, such that observers made the exact same decision in both conditions (“was a target present?”). Here, we found a marginal cost of dividing attention on performance, that was weaker than the cost in Experiment 1. Together, our results suggest that divided attention does impair detection of simple visual features, but that this cost is primarily due to limits in post-perceptual decision making.

Dissociating the neural correlates of subjective visibility from those of decision confidence

A key goal of consciousness science is identifying neural signatures of being aware vs. unaware of simple stimuli. This is often investigated in the context of near-threshold detection, with reports of stimulus awareness being linked to heightened activation in a frontoparietal network. However, due to the fact that reports of stimulus presence are also associated with higher confidence than reports of stimulus absence, these results could be explained by frontoparietal regions encoding stimulus visibility, decision confidence or both. Consistent with this view, previously we showed that prefrontal regions encode confidence in decisions about target presence (Mazor, Friston & Fleming, 2020). Here, we further ask if prefrontal cortex also encodes information about stimulus visibility over and above confidence. We first show that, whereas stimulus identity was best decoded from the visual cortex, stimulus visibility (presence vs. absence) was best decoded from prefrontal regions. To control for effects of confidence, we then selectively sampled trials prior to decoding to equalize the confidence distributions between absence and presence responses. This analysis revealed that posterior medial frontal cortex encoded stimulus visibility over and above decision confidence. We interpret our findings as providing support for a representation of stimulus visibility in specific higher-order cortical circuits, one that is dissociable from representations of both decision confidence and stimulus identity.

Ultrafast Object Detection in Naturalistic Vision Relies on Ultrafast Distractor Suppression

People are quicker to detect examples of real-world object categories in natural scenes than is predicted by classic attention theories. One explanation for this puzzle suggests that experience renders the visual system sensitive to midlevel features diagnosing target presence. These are detected without the need for spatial attention, much as occurs for targets defined by low-level features like color or orientation. The alternative is that naturalistic search relies on spatial attention but is highly efficient because global scene information can be used to quickly reject nontarget objects and locations. Here, we use ERPs to differentiate between these possibilities. Results show that hallmark evidence of ultrafast target detection in frontal brain activity is preceded by an index of spatially specific distractor suppression in visual cortex. Naturalistic search for heterogenous targets therefore appears to rely on spatial operations that act on neural object representations, as predicted by classic attention theory. People appear able to rapidly reject nontarget objects and locations, consistent with the idea that global scene information is used to constrain naturalistic search and increase search efficiency.

Minimum Time Search in Real-World Scenarios Using Multiple UAVs with Onboard Orientable Cameras

This paper proposes a new evolutionary planner to determine the trajectories of several Unmanned Aerial Vehicles (UAVs) and the scan direction of their cameras for minimizing the expected detection time of a nondeterministically moving target of uncertain initial location. To achieve this, the planner can reorient the UAVs cameras and modify the UAVs heading, speed, and height with the purpose of making the UAV reach and the camera observe faster the areas with high probability of target presence. Besides, the planner uses a digital elevation model of the search region to capture its influence on the camera likelihood (changing the footprint dimensions and the probability of detection) and to help the operator to construct the initial belief of target presence and target motion model. The planner also lets the operator include intelligence information in the initial target belief and motion model, in order to let him/her model real-world scenarios systematically. All these characteristics let the planner adapt the UAV trajectories and sensor poses to the requirements of minimum time search operations over real-world scenarios, as the results of the paper, obtained over 3 scenarios built with the modeling aid-tools of the planner, show.

When visual search target is rare: overweighting or under weighting the probability?

The prevalence of items in visual search may have substantial performance consequences. In laboratory visual search tasks in which the target is rare, viewers are likely to miss the target. A dual-threshold model proposed by Wolfe and Van Wert (2010) assumes that in the low prevalence condition, viewers shift their criteria resulting in more miss errors. However, from the prospective of prospect theory (Kahneman & Tversky, 1979), decision makers tend to overweight small probability. To explore how viewers subjectively weight the probability in the low prevalence visual search task, we compared viewers’ criteria with the optimal criteria by presenting different probability descriptions for a fixed prevalence rate. The data from this experiment indicated that target presence had an effect on viewers’ accuracy and response times but not probability descriptions. Viewers’ criteria under different probability descriptions were higher than optimal. These results are in accordance with the dual-threshold model assumption that viewers respond “target absent” more frequently than optimal, leading to more miss errors in the low prevalence condition.

Spatial attention follows category-based attention during naturalistic visual search: evidence from MEG decoding

In daily life, attention is often directed to high-level object attributes, such as when we look out for cars before crossing a road. Previous work used MEG decoding to investigate the influence of such category-based attention on the time course of object category representations. Attended object categories were more strongly represented than unattended categories from 180 ms after scene onset. In the present study, we used a similar approach to determine when, relative to this category-level modulation, attention is spatially focused on the target. Participants completed two tasks. In the first, they detected cars and people at varying locations in photographs of real-world scenes. In the second, they detected a cross that appeared at salient locations in an array of lines. Multivariate classifiers were trained on data of the artificial salience experiment and tested on data of the naturalistic visual search experiment. Results showed that the location of both target and distracter objects could be accurately decoded shortly after scene onset (50 ms). However, the emergence of spatial attentional selection - reflected in better decoding of target location than distracter location - emerged only later in time (240 ms). Target presence itself (irrespective of location and category) could be decoded from 180 ms after stimulus onset. Combined with earlier work, these results indicate that naturalistic category search operates through an initial spatially-global modulation of category processing that then guides attention to the location of the target.