Oculomotion mediates attentional guidance toward temporarily close objects

Unequal allocation of overt and covert attention in Multiple Object Tracking

In many real-life contexts, where objects are moving around, we are often required to allocate our attention unequally between targets or regions of different importance. However, typical multiple object tracking (MOT) tasks, primarily investigate equal attention allocation as the likelihood of each target being probed is the same. In two experiments, we investigated whether participants can allocate attention unequally across regions of the visual field, using a MOT task where two regions were probed with either a high and low or with equal priority. Experiment 1 showed that for high-priority regions, accuracy (for direction of heading judgments) improved, and participants had more frequent and longer fixations in that region compared with a low-priority region. Experiment 2 showed that eye movements were functional in that they slightly improved accuracy when participants could freely move their eyes compared with when they had to centrally fixate. Replicating Experiment 1, we found better tracking performance for high compared with low-priority regions, in both the free and fixed viewing conditions, but the benefit was greater for the free viewing condition. Although unequal attention allocation is possible without eye movements, eye movements seem to improve tracking ability, presumably by allowing participants to fixate more in the high-priority region and get a better, foveal view of the objects. These findings can help us better understand how observers in real-life settings (e.g., CCTV monitoring, driving) can use their limited attentional capacity to allocate their attention unequally in a demand-based manner across different tracking regions.

Distinct Neural Mechanisms Meet Challenges in Dynamic Visual Attention due to Either Load or Object Spacing

When engaged in dynamic visuospatial tasks, the brain copes with perceptual and cognitive processing challenges. During multiple-object tracking (MOT), the number of objects to be tracked (i.e., load) imposes attentional demands, but so does spatial interference from irrelevant objects (i.e., close encounters). Presently, it is not clear whether the effect of load on accuracy solely depends on the number of close encounters. If so, the same cognitive and physiological mechanisms deal with increasing load by preparing for and dealing with spatial interference. However, this has never been directly tested. Such knowledge is important to understand the neurophysiology of dynamic visual attention and resolve conflicting views within visual cognition concerning sources of capacity limitations. We varied the processing challenge in MOT task in two ways: the number of targets and the minimum spatial proximity between targets and distractors. In a first experiment, we measured task-induced pupil dilations and saccades during MOT. In a separate cohort, we measured fMRI activity. In both cohorts, increased load and close encounters (i.e., close spatial proximity) led to reduced accuracy in an additive manner. Load was associated with pupil dilations, whereas close encounters were not. Activity in dorsal attentional areas and frequency of saccades were proportionally larger both with higher levels of load and close encounters. Close encounters recruited additionally ventral attentional areas that may reflect orienting mechanisms. The activity in two brainstem nuclei, ventral tegmental area/substantia nigra and locus coeruleus, showed clearly dissociated patterns. Our results constitute convergent evidence indicating that different mechanisms underlie processing challenges due to load and object spacing.

Goal-directed unequal attention allocation during multiple object tracking

In standard multiple object tracking (MOT) tasks the relative importance of the targets being tracked is equal. This is atypical of everyday situations in which an individual may need to prioritize one target relative to another and so allocate attention unequally. We report three experiments that examined whether participants could unequally split attention using a modified MOT task in which target priority was manipulated. Specifically, we examined the effect of priority on participants’ magnitude of error and used a distribution mixture analysis to investigate how priority affected both participants’ probability of losing an item and tracking precision. Experiment 1 (trajectory tracking) revealed a higher magnitude of error and higher proportion of guessing for low- compared with high-priority targets. Experiments 2 (trajectory tracking) and 3 (position tracking) examined how fine-grained this ability is by manipulating target priority at finer increments. In line with Experiment 1, results from both these experiments indicated that participants could split attention unequally. There was some evidence that participants could allocate attention unequally at fine increments, but this was less conclusive. Taken together, these experiments demonstrate participants’ ability to distribute attention unequally across multiple moving objects but suggest some limitation with the flexibility of attention allocation.

The Cognitive Architecture of Perceived Animacy: Intention, Attention, and Memory

Human vision supports social perception by efficiently detecting agents and extracting rich information about their actions, goals, and intentions. Here, we explore the cognitive architecture of perceived animacy by constructing Bayesian models that integrate domain-specific hypotheses of social agency with domain-general cognitive constraints on sensory, memory, and attentional processing. Our model posits that perceived animacy combines a bottom-up, feature-based, parallel search for goal-directed movements with a top-down selection process for intent inference. The interaction of these architecturally distinct processes makes perceived animacy fast, flexible, and yet cognitively efficient. In the context of chasing, in which a predator (the "wolf") pursues a prey (the "sheep"), our model addresses the computational challenge of identifying target agents among varying numbers of distractor objects, despite a quadratic increase in the number of possible interactions as more objects appear in a scene. By comparing modeling results with human psychophysics in several studies, we show that the effectiveness and efficiency of human perceived animacy can be explained by a Bayesian ideal observer model with realistic cognitive constraints. These results provide an understanding of perceived animacy at the algorithmic level-how it is achieved by cognitive mechanisms such as attention and working memory, and how it can be integrated with higher-level reasoning about social agency.

Model of Multiple Identity Tracking (MOMIT) 2.0: Resolving the serial vs. parallel controversy in tracking

The present study investigated whether during tracking of multiple moving objects with distinct identities only one identity is tracked at each moment (serial tracking) or whether multiple identities can be tracked simultaneously (parallel tracking). By adopting the gaze-contingent display change technique, we manipulated in real time the presence/absence of object identities during tracking. The data on performance accuracy revealed a serial tracking pattern for facial images and a parallel pattern for color discs: when tracking faces, the presence/absence of only the currently foveated identity impacted the performance, whereas when tracking colors, the presence of multiple identities across the visual field led to improved tracking performance. This pattern is consistent with the identifiability of the different types of objects in the visual field. The eye movements during MIT showed a bias towards visiting and dwelling on individual targets when facial identities were present and towards visiting the blank areas between targets when color identities were present. Nevertheless, the eye visits were predominately on individual targets regardless of the type of objects and the presence of object identities. The eye visits to targets were beneficial for target tracking, particularly in face tracking. We propose the Model of Multiple Identity Tracking (MOMIT) 2.0 which accounts for the results and reconcile the serial vs. parallel controversy. The model suggests that observers cooperatively use attention, eye movements, perception, and working memory for dynamic tracking. Tracking appears more serial when high-resolution information needs to be sampled and maintained for discriminating the targets, whereas it appears more parallel when low-resolution information is sufficient.