How task demands influence scanpath similarity in a sequential number-search task

The fundamentals of eye tracking part 4: Tools for conducting an eye tracking study

Researchers using eye tracking are heavily dependent on software and hardware tools to perform their studies, from recording eye tracking data and visualizing it, to processing and analyzing it. This article provides an overview of available tools for research using eye trackers and discusses considerations to make when choosing which tools to adopt for one's study.

Internal coupling: Eye behavior coupled to visual imagery

Our eyes do not only respond to visual perception but also to internal cognition involving visual imagery, which can be referred to as internal coupling. This review synthesizes evidence on internal coupling across diverse domains including episodic memory and simulation, visuospatial memory, numerical cognition, object movement, body movement, and brightness imagery. In each domain, eye movements consistently reflect distinct aspects of mental imagery typically akin to those seen in corresponding visual experiences. Several findings further suggest that internal coupling may not only coincide with but also supports internal cognition as evidenced by improved cognitive performance. Available theoretical accounts suggest that internal coupling may serve at least two functional roles in visual imagery: facilitating memory reconstruction and indicating shifts in internal attention. Moreover, recent insights into the neurobiology of internal coupling highlight substantially shared neural pathways in externally and internally directed cognition. The review concludes by identifying open questions and promising avenues for future research such as exploring moderating roles of context and individual differences in internal coupling.

Scene construction in healthy aging - Exploring the interplay between task complexity and oculomotor behaviour

Mounting evidence indicates a close correspondence between episodic memory, mental imagery, and oculomotor behaviour. It remains unclear, however, how oculomotor variables support endogenously driven forms of mental imagery and how this relationship changes across the adult lifespan. In this study we investigated age-related changes in oculomotor signatures during scene construction and explored how task complexity impacts these processes. Younger and cognitively healthy older participants completed a guided scene construction paradigm where scene complexity was manipulated according to the number of elements to be sequentially integrated. We recorded participants' eye movements and collected subjective ratings regarding their phenomenological experience. Overall, older adults rated their constructions as more vivid and more spatially integrated, while also generating more fixations and saccades relative to the younger group, specifically on control trials. Analyses of participants' total scan paths revealed that, in the early stages of scene construction, oculomotor behaviour changed as a function of task complexity within each group. Following the introduction of a second stimulus, older but not younger adults showed a significant decrease in the production of eye movements. Whether this shift in oculomotor behaviour serves a compensatory function to bolster task performance represents an important question for future research.

Predicting choice behaviour in economic games using gaze data encoded as scanpath images

Eye movement data has been extensively utilized by researchers interested in studying decision-making within the strategic setting of economic games. In this paper, we demonstrate that both deep learning and support vector machine classification methods are able to accurately identify participants' decision strategies before they commit to action while playing games. Our approach focuses on creating scanpath images that best capture the dynamics of a participant's gaze behaviour in a way that is meaningful for predictions to the machine learning models. Our results demonstrate a higher classification accuracy by 18% points compared to a baseline logistic regression model, which is traditionally used to analyse gaze data recorded during economic games. In a broader context, we aim to illustrate the potential for eye-tracking data to create information asymmetries in strategic environments in favour of those who collect and process the data. These information asymmetries could become especially relevant as eye-tracking is expected to become more widespread in user applications, with the seemingly imminent mass adoption of virtual reality systems and the development of devices with the ability to record eye movement outside of a laboratory setting.

Mining attention distribution paradigm: Discover gaze patterns and their association rules behind the visual image

BACKGROUND AND OBJECTIVE

Attention allocation reflects the way of humans filtering and organizing the information. On one hand, different task scenarios seriously affect human's rule of attention distribution, on the other hand, visual attention reflecting the cognitive and psychological process. Most of the previous studies on visual attention allocation are based on cognitive models, predicted models, or statistical analysis of eye movement data or visual images, however, these methods are inadequate to provide an inside view of gaze behavior to reveal the attention distribution pattern within scenario context. Moreover, they seldom study the association rules of these patterns. Therefore, we adopted the big data mining approach to discover the paradigm of visual attention distribution.

METHODS

We applied the data mining method to extract the gaze patterns to discover the regularities of attention distribution behavior within the scenario context. The proposed method consists of three components, tasks scenario segmented and clustered, gaze pattern mining, and association rule of frequent pattern mining.

RESULTS

The proposed approach is tested on the operation platform. The complex operation task is simultaneously segmented and clustered with the TICC-based method and evaluated by the BCI index. The operator's eye movement frequent patterns and their association rule are discovered. The results demonstrate that our method can associate the eye-tracking data with the task-oriented scene data.

DISCUSSION

The proposed method provides the benefits of being able to explicitly express and quantitatively analyze people's visual attention patterns. The proposed method can not only be applied in the field of aerospace medicine and aviation psychology, but also can likely be applied to computer-aided diagnosis and follow-up tool for neurological disease and cognitive impairment related disease, such as ADHD (Attention Deficit Hyperactivity Disorder), neglect syndrome, social attention differences in ASD (Autism spectrum disorder).

Towards tacit knowledge mining within context: Visual cognitive graph model and eye movement image interpretation

Visual attention is one of the most important brain cognitive functions, which filters the rich information of the outside world to ensure the efficient operation of limited cognitive resources. The underlying knowledge, i.e., tacit knowledge, hidden in the human attention allocation performances, is context-related and is hard to be expressed by experts, but it is essential for novice operator training and interaction system design. Traditional models of visual attention allocation and corresponding analysis methods seldomly involve task contextual information or present the tacit knowledge in an explicit and quantified way. Thus, it is challenging to pass on the expert's tacit knowledge to the novice or utilize it to construct an interaction system by employing traditional methods. Therefore, this paper first proposes a new model called the visual cognitive graph model based on graph theory to model the visual attention allocation associated with the task context. Then, based on this graph model, utilize the data mining method to reveal attention patterns within context to quantitatively analyze the operator's tacit knowledge during operation tasks. We introduced three physical quantities derived from graph theory to describe the tacit knowledge, which can be used directly to construct an interaction system or operator training. For example, discover the essential information within the task context, the relevant information affecting critical information, and the bridge information revealing the decision-making process. We tested the proposed method in the example of flight operation, the comparison results with the traditional eye movement graph model demonstrate that the proposed visual cognitive model can compromise the task context. The comparison results with the statistical analysis method demonstrate that our tacit knowledge mining method can reveal the underlying knowledge hidden in the visual information. Finally, we give practical applications in the examples of operator training guidance and adaptive interaction system. Our proposed method can explore more in-depth knowledge of visual information, such as the correlations of different obtained information and the way operator obtains information, most of which are even not noticed by operators themselves.

SoftMatch: Comparing Scanpaths Using Combinatorial Spatio-Temporal Sequences with Fractal Curves

Recent studies matching eye gaze patterns with those of others contain research that is heavily reliant on string editing methods borrowed from early work in bioinformatics. Previous studies have shown string editing methods to be susceptible to false negative results when matching mutated genes or unordered regions of interest in scanpaths. Even as new methods have emerged for matching amino acids using novel combinatorial techniques, scanpath matching is still limited by a traditional collinear approach. This approach reduces the ability to discriminate between free viewing scanpaths of two people looking at the same stimulus due to the heavy weight placed on linearity. To overcome this limitation, we here introduce a new method called SoftMatch to compare pairs of scanpaths. SoftMatch diverges from traditional scanpath matching in two different ways: firstly, by preserving locality using fractal curves to reduce dimensionality from 2D Cartesian (x,y) coordinates into 1D (h) Hilbert distances, and secondly by taking a combinatorial approach to fixation matching using discrete Fréchet distance measurements between segments of scanpath fixation sequences. These matching "sequences of fixations over time" are a loose acronym for SoftMatch. Results indicate high degrees of statistical and substantive significance when scoring matches between scanpaths made during free-form viewing of unfamiliar stimuli. Applications of this method can be used to better understand bottom up perceptual processes extending to scanpath outlier detection, expertise analysis, pathological screening, and salience prediction.

Similar mechanisms of temporary bindings for identity and location of objects in healthy ageing: an eye-tracking study with naturalistic scenes

The ability to maintain visual working memory (VWM) associations about the identity and location of objects has at times been found to decrease with age. To date, however, this age-related difficulty was mostly observed in artificial visual contexts (e.g., object arrays), and so it is unclear whether it may manifest in naturalistic contexts, and in which ways. In this eye-tracking study, 26 younger and 24 healthy older adults were asked to detect changes in a critical object situated in a photographic scene (192 in total), about its identity (the object becomes a different object but maintains the same position), location (the object only changes position) or both (the object changes in location and identity). Aging was associated with a lower change detection performance. A change in identity was harder to detect than a location change, and performance was best when both features changed, especially in younger adults. Eye movements displayed minor differences between age groups (e.g., shorter saccades in older adults) but were similarly modulated by the type of change. Latencies to the first fixation were longer and the amplitude of incoming saccades was larger when the critical object changed in location. Once fixated, the target object was inspected for longer when it only changed in identity compared to location. Visually salient objects were fixated earlier, but saliency did not affect any other eye movement measures considered, nor did it interact with the type of change. Our findings suggest that even though aging results in lower performance, it does not selectively disrupt temporary bindings of object identity, location, or their association in VWM, and highlight the importance of using naturalistic contexts to discriminate the cognitive processes that undergo detriment from those that are instead spared by aging.

Eye-movement replay supports episodic remembering

When we bring to mind something we have seen before, our eyes spontaneously unfold in a sequential pattern strikingly similar to that made during the original encounter, even in the absence of supporting visual input. Oculomotor movements of the eye may then serve the opposite purpose of acquiring new visual information; they may serve as self-generated cues, pointing to stored memories. Over 50 years ago Donald Hebb, the forefather of cognitive neuroscience, posited that such a sequential replay of eye movements supports our ability to mentally recreate visuospatial relations during episodic remembering. However, direct evidence for this influential claim is lacking. Here we isolate the sequential properties of spontaneous eye movements during encoding and retrieval in a pure recall memory task and capture their encoding-retrieval overlap. Critically, we show that the fidelity with which a series of consecutive eye movements from initial encoding is sequentially retained during subsequent retrieval predicts the quality of the recalled memory. Our findings provide direct evidence that such scanpaths are replayed to assemble and reconstruct spatio-temporal relations as we remember and further suggest that distinct scanpath properties differentially contribute depending on the nature of the goal-relevant memory.

Restricted Visual Scanpaths During Emotion Recognition in Childhood Social Anxiety Disorder

Background: Social anxiety disorder (SAD) has its typical onset in childhood and adolescence. Maladaptive processing of social information may contribute to the etiology and maintenance of SAD. During face perception, individuals execute a succession of visual fixations known as a scanpath which facilitates information processing. Atypically long scanpaths have been reported in adults with SAD, but no data exists from pediatric samples. SAD has also been linked to atypical arousal during face perception. Both metrics were examined in one of the largest eye-tracking studies of pediatric SAD to date. Methods: Participants were children and adolescents with SAD (n = 61) and healthy controls (n = 39) with a mean age of 14 years (range 10-17) who completed an emotion recognition task. The visual scanpath and pupil dilation (an indirect index of arousal) were examined using eye tracking. Results: Scanpaths of youth with SAD were shorter, less distributed, and consisted of a smaller number of fixations than those of healthy controls. These findings were supported by both frequentist and Bayesian statistics. Higher pupil dilation was also observed in the SAD group, but despite a statistically significant group difference, this result was not supported by the Bayesian analysis. Conclusions: The results were contrary to findings from adult studies, but similar to what has been reported in neurodevelopmental conditions associated with social interaction impairments. Restricted scanpaths may disrupt holistic representation of faces known to favor adaptive social understanding.

Scan path during change-detection visual search

When observing a particular image or object, one's perception depends upon prior expectations, memory, and cognitive abilities. It is hypothesized that cognitive processing in the form of top-down or bottom-up processing could be determined via analysis of the eye fixation scan path. To assess the variations in scan paths, 7 subjects underwent 5 change-detection trials. During each trial, they were presented with a specific set of images via a MATLAB program, in which the original image alternated with a modified image consisting of a single change. An open-source program called GazeRecorder was used to track the subject's eye movements and to record the eye fixations. The scan path was then analyzed through the use of a 4 by 4 grid pattern superimposed on the image to determine the subject's eye fixation distribution pattern in terms of Boxes Viewed and Concentration within a single area. It was determined that higher Concentration was positively correlated with faster Detection Speed (R = 0.84), while higher number of Boxes Viewed was negatively correlated with Detection Speed (R = -0.71). Among the subjects, the more optimal scan paths were found in those with a balance between Concentration and Boxes Viewed, as subjects with a more balanced approach had the greatest Accuracy (p = 0.02). This indicates an optimal scan path involves both top-down and bottom-up processing to more efficiently identify a change. Moreover, the methodology developed in this study could be used in the home or clinic for quantitative assessment of improvement following therapy in patients with neurological deficits.

Scanpath Analysis of Student Attention During Problem Solving with Worked Examples

We report on the analysis of scanpath data captured by an eye tracker as students solved problems with access to worked examples. Our work makes two contributions: (1) it reports on scanpath analysis using the MultiMatch tool, (2) it investigates how type of problem-example similarity and assistance influenced attention patterns captured by scanpaths. We show that both problem-example similarity and type of assistance impact scanpaths.