Mirror-image symmetry and search asymmetry: a comparison of their effects on visual search and a possible unifying explanation

Emergent human-like covert attention in feedforward convolutional neural networks

Covert attention allows the selection of locations or features of the visual scene without moving the eyes. Cues and contexts predictive of a target's location orient covert attention and improve perceptual performance. The performance benefits are widely attributed to theories of covert attention as a limited resource, zoom, spotlight, or weighting of visual information. However, such concepts are difficult to map to neuronal populations. We show that a feedforward convolutional neural network (CNN) trained on images to optimize target detection accuracy and with no explicit incorporation of an attention mechanism, a limited resource, or feedback connections learns to utilize cues and contexts in the three most prominent covert attention tasks (Posner cueing, set size effects in search, and contextual cueing) and predicts the cue/context influences on human accuracy. The CNN's cueing/context effects generalize across network training schemes, to peripheral and central pre-cues, discrimination tasks, and reaction time measures, and critically do not vary with reductions in network resources (size). The CNN shows comparable cueing/context effects to a model that optimally uses image information to make decisions (Bayesian ideal observer) but generalizes these effects to cue instances unseen during training. Together, the findings suggest that human-like behavioral signatures of covert attention in the three landmark paradigms might be an emergent property of task accuracy optimization in neuronal populations without positing limited attentional resources. The findings might explain recent behavioral results showing cueing and context effects across a variety of simple organisms with no neocortex, from archerfish to fruit flies.

Mirror blindness: Our failure to recognize the target in search for mirror-reversed shapes

It is well known that visual search for a mirror target (i.e., a horizontally flipped item) is more difficult than search for other-oriented items (e.g., vertically flipped items). Previous studies have typically attributed costs of mirror search to early, attention-guiding processes but could not rule out contributions from later processes. In the present study we used eye tracking to distinguish between early, attention-guiding processes and later target identification processes. The results of four experiments revealed a marked human weakness in identifying mirror targets: Observers appear to frequently fail to classify a mirror target as a target on first fixation and to continue with search even after having directly looked at the target. Awareness measures corroborated that the location of a mirror target could not be reported above chance level after it had been fixated once. This mirror blindness effect explained a large proportion (45-87%) of the overall costs of mirror search, suggesting that part of the difficulties with mirror search are rooted in later, object identification processes (not attentional guidance). Mirror blindness was significantly reduced but not completely eliminated when both the target and non-targets were held constant, which shows that perfect top-down knowledge can reduce mirror blindness, without completely eliminating it. The finding that non-target certainty reduced mirror blindness suggests that object identification is not solely achieved by comparing a selected item to a target template. These results demonstrate that templates that guide search toward targets are not identical to the templates used to conclusively identify those targets.

Measurement properties of streamlined wolf motor function test in patients at subacute to chronic stages after stroke

BACKGROUND. Previous research using the streamlined Wolf Motor Function Test (SWMFT) has focused either on the 3- to 9-month period or on the >12-month period after stroke and lacked the information for those at 9 to 12 months. Whether SWMFT scores reflect motor deficit and recovery from early to late stages after stroke remains unclear.

OBJECTIVE

A retrospective study using the Functional Ability Scale (FAS) was conducted to evaluate whether all SWMFTs items measure the poststroke recovery of upper extremity (UE) motor function and if they could be used for patients within 9 to 12 months after a stroke.

METHODS

Rasch analysis was conducted, and data were drawn from patients 3 months to years after a stroke.

RESULTS

The continuum of UE motor function in SWMFT-FAS was supported. Subacute patients had the best motor function, followed by the 9- to 12-month group, and then chronic patients. Variation in UE motor function was large (2.35-2.72 logits), and motor abilities of these 3 groups overlapped. The 8 SWMFT items could target a broad range of UE motor function, from -8.28 to 7.80 logits. The average difficulty of these 8 items also matched the UE motor ability of the subgroup at 9 to 12 months after stroke, and individual versions of the SWMFT performed well to assess the motor ability of this group.

CONCLUSIONS

The SWMFTs had sound hierarchical properties. The SWMFT-Chronic or the SWMFT-Subacute could be used to evaluate UE function of this subgroup at 9 to 12 months after stroke.

Signal detection evidence for limited capacity in visual search

The nature of capacity limits (if any) in visual search has been a topic of controversy for decades. In 30 years of work, researchers have attempted to distinguish between two broad classes of visual search models. Attention-limited models have proposed two stages of perceptual processing: an unlimited-capacity preattentive stage, and a limited-capacity selective attention stage. Conversely, noise-limited models have proposed a single, unlimited-capacity perceptual processing stage, with decision processes influenced only by stochastic noise. Here, we use signal detection methods to test a strong prediction of attention-limited models. In standard attention-limited models, performance of some searches (feature searches) should only be limited by a preattentive stage. Other search tasks (e.g., spatial configuration search for a "2" among "5"s) should be additionally limited by an attentional bottleneck. We equated average accuracies for a feature and a spatial configuration search over set sizes of 1-8 for briefly presented stimuli. The strong prediction of attention-limited models is that, given overall equivalence in performance, accuracy should be better on the spatial configuration search than on the feature search for set size 1, and worse for set size 8. We confirm this crossover interaction and show that it is problematic for at least one class of one-stage decision models.