The role of eye fixations in concentration and amplification effects during multiple object tracking

Visual Attention and Cognitive Archaeology: An Eye-Tracking Study of Palaeolithic Stone Tools

The study of lithic technology can provide information on human cultural evolution. This article aims to analyse visual behaviour associated with the exploration of ancient stone artefacts and how this relates to perceptual mechanisms in humans. In Experiment 1, we used eye tracking to record patterns of eye fixations while participants viewed images of stone tools, including examples of worked pebbles and handaxes. The results showed that the focus of gaze was directed more towards the upper regions of worked pebbles and on the basal areas for handaxes. Knapped surfaces also attracted more fixation than natural cortex for both tool types. Fixation distribution was different to that predicted by models that calculate visual salience. Experiment 2 was an online study using a mouse-click attention tracking technique and included images of unworked pebbles and 'mixed' images combining the handaxe's outline with the pebble's unworked texture. The pattern of clicks corresponded to that revealed using eye tracking and there were differences between tools and other images. Overall, the findings suggest that visual exploration is directed towards functional aspects of tools. Studies of visual attention and exploration can supply useful information to inform understanding of human cognitive evolution and tool use.

A hidden Markov model for analyzing eye-tracking of moving objects : Case study in a sustained attention paradigm

Eye-tracking provides an opportunity to generate and analyze high-density data relevant to understanding cognition. However, while events in the real world are often dynamic, eye-tracking paradigms are typically limited to assessing gaze toward static objects. In this study, we propose a generative framework, based on a hidden Markov model (HMM), for using eye-tracking data to analyze behavior in the context of multiple moving objects of interest. We apply this framework to analyze data from a recent visual object tracking task paradigm, TrackIt, for studying selective sustained attention in children. Within this paradigm, we present two validation experiments to show that the HMM provides a viable approach to studying eye-tracking data with moving stimuli, and to illustrate the benefits of the HMM approach over some more naive possible approaches. The first experiment utilizes a novel 'supervised' variant of TrackIt, while the second compares directly with judgments made by human coders using data from the original TrackIt task. Our results suggest that the HMM-based method provides a robust analysis of eye-tracking data with moving stimuli, both for adults and for children as young as 3.5-6 years old.

Examining the roles of working memory and visual attention in multiple object tracking expertise

When tracking multiple moving targets among visually similar distractors, human observers are capable of distributing attention over several spatial locations. It is unclear, however, whether capacity limitations or perceptual-cognitive abilities are responsible for the development of expertise in multiple object tracking. Across two experiments, we examined the role of working memory and visual attention in tracking expertise. In Experiment 1, individuals who regularly engaged in object tracking sports (soccer and rugby) displayed improved tracking performance, relative to non-tracking sports (swimming, rowing, running) (p = 0.02, ηp2 = 0.163), but no differences in gaze strategy (ps > 0.31). In Experiment 2, participants trained on an adaptive object tracking task showed improved tracking performance (p = 0.005, d = 0.817), but no changes in gaze strategy (ps > 0.07). They did, however, show significant improvement in a working memory transfer task (p < 0.001, d = 0.970). These findings indicate that the development of tracking expertise is more closely linked to processing capacity limits than perceptual-cognitive strategies.

Eye Behavior During Multiple Object Tracking and Multiple Identity Tracking

We review all published eye-tracking studies to date that have used eye movements to examine multiple object (MOT) or multiple identity tracking (MIT). In both tasks, observers dynamically track multiple moving objects. In MOT the objects are identical, whereas in MIT they have distinct identities. In MOT, observers prefer to fixate on blank space, which is often the center of gravity formed by the moving targets (centroid). In contrast, in MIT observers have a strong preference for the target-switching strategy, presumably to refresh and maintain identity-location bindings for the targets. To account for the qualitative differences between MOT and MIT, two mechanisms have been posited, a position tracking (MOT) and an identity tracking (MOT & MIT) mechanism. Eye-tracking studies of MOT have also demonstrated that observers execute rescue saccades toward targets in danger of becoming occluded or are about to change direction after a collision. Crowding attracts the eyes close to it in order to increase visual acuity for the crowded objects to prevent target loss. It is suggested that future studies should concentrate more on MIT, as MIT more closely resembles tracking in the real world.

The role of eye movements in the size-speed illusion of approaching trains

Recent research on the perceived speed of large moving objects, compared to smaller moving objects, has revealed the presence of a size-speed illusion. This illusion, where a large object seems to be moving more slowly than a small object travelling at the same speed may account for collisions between motor cars and trains at level crossings, which is a serious safety issue in New Zealand and worldwide. One possible reason for the perceived size-speed difference may be related to the movement of our eyes when we track moving vehicles. In order to investigate this, we tested observers' relative speed perception of moving objects (both abstract and more detailed objects) moving in depth towards the observer, presented on a computer display and eye movements recorded with an eyetracker. Experiment 1 confirmed first the size-speed illusion when the observers were situated further away (18, 36m) from the simulated rail crossing or intersection. It also revealed that the eye movement behaviour of our participants was different when they judged the speeds of the small and large objects; eye fixations were localised around the visual centroid of longer objects and hence were further from the front of the moving large objects than the smaller ones. Experiment 2 found that manipulating eye movements could reduce the magnitude of the illusion. When observers tracked targets (dots) that were placed at corresponding locations at the front of the small object and the long object respectively, they perceived the speeds of the two objects as equal. When target dots were placed closer to the visual centroid, observers perceived the larger object to be moving slower. These results demonstrate that there is a close relationship between eye movement behaviour and our perceived judgement of an approaching train's speed.

Position tracking and identity tracking are separate systems: Evidence from eye movements

How do we track multiple moving objects in our visual environment? Some investigators argue that tracking is based on a parallel mechanism (e.g., Cavanagh & Alvarez, 2005; Pylyshyn, 1989), others argue that tracking contains a serial component (e.g. Holcombe & Chen, 2013; Oksama & Hyönä, 2008). In the present study, we put previous theories into a direct test by registering observers' eye movements when they tracked identical moving targets (the MOT task) or when they tracked distinct object identities (the MIT task). The eye movement technique is a useful tool to study whether overt focal attention is exploited during tracking. We found a qualitative difference between these tasks in terms of eye movements. When the participants tracked only position information (MOT), the observers had a clear preference for keeping their eyes fixed for a rather long time on the same screen position. In contrast, active eye behavior was observed when the observers tracked the identities of moving objects (MIT). The participants updated over four target identities with overt attention shifts. These data suggest that there are two separate systems involved in multiple object tracking. The position tracking system keeps track of the positions of the moving targets in parallel without the need of overt attention shifts in the form of eye movements. On the other hand, the identity tracking system maintains identity-location bindings in a serial fashion by utilizing overt attention shifts.

An eye-tracking study of exploitations of spatial constraints in diagrammatic reasoning

Semantic studies on diagrammatic notations (Barwise & Etchemendy, 1990; Shimojima, 1995; Stenning & Lemon, 2001) have revealed that the "non-deductive," "emergent," or "perceptual" effects of diagrams (Chandrasekaran, Kurup, Banerjee, Josephson, & Winkler, 2004; Kulpa, 2003; Larkin & Simon, 1987; Lindsay, 1988) are all rooted in the exploitation of spatial constraints on graphical structures. Thus, theoretically, this process is a key factor in inference with diagrams, explaining the frequently observed reduction of inferential load. The purpose of this study was to examine the empirical basis for this theoretical suggestion, focusing on the reality of the constraint-exploitation strategy in actual practices of diagrammatic reasoning. Eye movements were recorded while participants used simple position diagrams to solve three- or four-term transitive inference problems. Our experiments revealed that the participants could exploit spatial constraints on graphical structures even when (a) they were not in the position of actually manipulating diagrams, (b) the semantic rule for the provided diagrams did not match their preferences, and (c) the constraint-exploitation strategy invited a partly adverse effect. These findings indicate that the hypothesized process is in fact robust, with the potential to broadly account for the inferential advantage of diagrams.