Judging qualifcation, gender, and age of the observer based on gaze patterns when looking at faces

The research aimed to compare eye movement patterns of people looking at faces with different but subtle teeth imperfections. Both non-specialists and dental experts took part in the experiment. The research outcome includes the analysis of eye movement patterns depending on the specialization, gender, age, face gender, and level of teeth deformation. The study was performed using a novel, not widely explored features of eye movements, derived from recurrence plots and Gaze Self Similarity Plots. It occurred that most features are significantly different for laypeople and specialists. Signifcant differences were also found for gender and age among the observers. There were no differences found when comparing the gender of the face being observed and levels of imperfection. Interestingly, it was possible to defne which features are sensitive to gender and which to qualifcation

Gaze Self-Similarity Plot - A New Visualization Technique

Eye tracking has become a valuable way for extending knowledge of human behavior based on visual patterns. One of the most important elements of such an analysis is the presentation of obtained results, which proves to be a challenging task. Traditional visualization techniques such as scan-paths or heat maps may reveal interesting information, nonetheless many useful features are still not visible, especially when temporal characteristics of eye movement is taken into account. This paper introduces a technique called gaze self-similarity plot (GSSP) that may be applied to visualize both spatial and temporal eye movement features on the single two-dimensional plot. The technique is an extension of the idea of recurrence plots, commonly used in time series analysis. The paper presents the basic concepts of the proposed approach (two types of GSSP) complemented with some examples of what kind of information may be disclosed and finally showing areas of the GSSP possible applications

Using Eye Movement Data Visualization to Enhance Training of Air Traffic Controllers: A Dynamic Network Approach

The Federal Aviation Administration (FAA) forecasted substantial increase in the US air traffic volume creating a high demand in Air Traffic Control Specialists (ATCSs). Training times and passing rates for ATCSs might be improved if expert ATCSs’ eye movement (EM) characteristics can be utilized to support effective training. However, effective EM visualization is difficult for a dynamic task (e.g. aircraft conflict detection and mitigation) that includes interrogating multi-element targets that are dynamically moving, appearing, disappearing, and overlapping within a display. To address the issues, a dynamic network-based approach is introduced that integrates adapted visualizations (i.e. time-frame networks and normalized dot/bar plots) with measures used in network science (i.e. indegree, closeness, and betweenness) to provide in-depth EM analysis. The proposed approach was applied in an aircraft conflict task using a high-fidelity simulator; employing the use of veteran ATCSs and pseudo pilots. Results show that, ATCSs’ visual attention to multi-element dynamic targets can be effectively interpreted and supported through multiple evidences obtained from the various visualization and associated measures. In addition, we discovered that fewer eye fixation numbers or shorter eye fixation durations on a target may not necessarily indicate the target is less important when analyzing the flow of visual attention within a network. The results show promise in cohesively analyzing and visualizing various eye movement characteristics to better support training. 

Visual attention deficits in schizophrenia can arise from inhibitory dysfunction in thalamus or cortex

Schizophrenia is associated with diverse cognitive deficits, including disorders of attention-related oculomotor behavior. At the structural level, schizophrenia is associated with abnormal inhibitory control in the circuit linking cortex and thalamus. We developed a spiking neural network model that demonstrates how dysfunctional inhibition can degrade attentive gaze control. Our model revealed that perturbations of two functionally distinct classes of cortical inhibitory neurons, or of the inhibitory thalamic reticular nucleus, disrupted processing vital for sustained attention to a stimulus, leading to distractibility. Because perturbation at each circuit node led to comparable but qualitatively distinct disruptions in attentive tracking or fixation, our findings support the search for new eye movement metrics that may index distinct underlying neural defects. Moreover, because the cortico-thalamic circuit is a common motif across sensory, association, and motor systems, the model and extensions can be broadly applied to study normal function and the neural bases of other cognitive deficits in schizophrenia.R01 MH057414 - NIMH NIH HHS; R01 MH101209 - NIMH NIH HHS; R01 NS024760 - NINDS NIH HHSPublished versio

Dummy eye measurements of microsaccades: testing the influence of system noise and head movements on microsaccade detection in a popular video-based eye tracker

Whereas early studies of microsaccades have predominantly relied on custom-built eye trackers and manual tagging of microsaccades, more recent work tends to use video-based eye tracking and automated algorithms for microsaccade detection. While data from these newer studies suggest that microsaccades can be reliably detected with video-based systems, this has not been systematically evaluated. I here present a method and data examining microsaccade detection in an often used video-based system (the Eyelink II system) and a commonly used detection algorithm (Engbert & Kliegl, 2003; Engbert & Mergenthaler, 2006). Recordings from human participants and those obtained using a pair of dummy eyes, mounted on a pair of glasses either worn by a human participant (i.e., with head motion) or a dummy head (no head motion) were compared. Three experiments were conducted. The first experiment suggests that when microsaccade measurements make use of the pupil detection mode, microsaccade detections in the absence of eye movements are sparse in the absence of head movements, but frequent with head movements (despite the use of a chin rest). A second experiment demonstrates that by using measurements that rely on a combination of corneal reflection and pupil detection, false microsaccade detections can be largely avoided as long as a binocular criterion is used. A third experiment examines whether past results may have been affected by possible incorrect detections due to small head movements. It shows that despite the many detections due to head movements, the typical modulation of microsaccade rate after stimulus onset is found only when recording from the participants’ eyes

Repeatability of the measurement of the horizontal phoria in near vision with cover test and modified thorington method

Objectiu- Estudiar la repetibilitat del cover test alternant i el mètode modificat de Thorington. Mètode- En aquest estudi han participat 10 persones joves i sanes amb agudesa visual de prop igual o superior a 20/20 amb la seva correcció habitual. El cover test es va realitzar amb un test a 40 cm d'agudesa visual de 20/25 i màxima il·luminació. Thorington es va realitzar a 40 cm amb la vareta Maddox davant de l'ull dret i la targeta corresponent, la il·luminació de la sala era reduïda. Ambdues mesures es van realizar dues vegades pel mateix examinador amb un interval de 24 hores. L'anàlisi estadística es va realitzar amb la versió SPSS 22.0. Resultats- La mitjana absoluta de les diferències i la desviació estàndard entre les mesures del cover test va ser d'1.000±0.943 i 0.400±0.943 per Thorington (p=0.000). Bland & Altman mostren que hi ha una diferència d'aproximadament 0,5 entre les dues proves delcovertest i no hi ha diferència apreciable entre les dues mesures amb el mètode de Thorington. S'obté una bona concordança en tots dos mètodes. Conclusions- El cover test alternant i Thorington modificat van presentar una bona repetibilitat intraexaminador en visió de prop. Tots dos mètodes són precisos per quantificar la fòria en visió propera

Cross-Recurrence Quantification Analysis of Categorical and Continuous Time Series: an R package

This paper describes the R package crqa to perform cross-recurrence quantification analysis of two time series of either a categorical or continuous nature. Streams of behavioral information, from eye movements to linguistic elements, unfold over time. When two people interact, such as in conversation, they often adapt to each other, leading these behavioral levels to exhibit recurrent states. In dialogue, for example, interlocutors adapt to each other by exchanging interactive cues: smiles, nods, gestures, choice of words, and so on. In order for us to capture closely the goings-on of dynamic interaction, and uncover the extent of coupling between two individuals, we need to quantify how much recurrence is taking place at these levels. Methods available in crqa would allow researchers in cognitive science to pose such questions as how much are two people recurrent at some level of analysis, what is the characteristic lag time for one person to maximally match another, or whether one person is leading another. First, we set the theoretical ground to understand the difference between 'correlation' and 'co-visitation' when comparing two time series, using an aggregative or cross-recurrence approach. Then, we describe more formally the principles of cross-recurrence, and show with the current package how to carry out analyses applying them. We end the paper by comparing computational efficiency, and results' consistency, of crqa R package, with the benchmark MATLAB toolbox crptoolbox. We show perfect comparability between the two libraries on both levels

Neuronal processing of translational optic flow in the visual system of the shore crab Carcinus maenas

This paper describes a search for neurones sensitive to optic flow in the visual system of the shore crab Carcinus maenas using a procedure developed from that of Krapp and Hengstenberg. This involved determining local motion sensitivity and its directional selectivity at many points within the neurone's receptive field and plotting the results on a map. Our results showed that local preferred directions of motion are independent of velocity, stimulus shape and type of motion (circular or linear). Global response maps thus clearly represent real properties of the neurones' receptive fields. Using this method, we have discovered two families of interneurones sensitive to translational optic flow. The first family has its terminal arborisations in the lobula of the optic lobe, the second family in the medulla. The response maps of the lobula neurones (which appear to be monostratified lobular giant neurones) show a clear focus of expansion centred on or just above the horizon, but at significantly different azimuth angles. Response maps such as these, consisting of patterns of movement vectors radiating from a pole, would be expected of neurones responding to self-motion in a particular direction. They would be stimulated when the crab moves towards the pole of the neurone's receptive field. The response maps of the medulla neurones show a focus of contraction, approximately centred on the horizon, but at significantly different azimuth angles. Such neurones would be stimulated when the crab walked away from the pole of the neurone's receptive field. We hypothesise that both the lobula and the medulla interneurones are representatives of arrays of cells, each of which would be optimally activated by self-motion in a different direction. The lobula neurones would be stimulated by the approaching scene and the medulla neurones by the receding scene. Neurones tuned to translational optic flow provide information on the three-dimensional layout of the environment and are thought to play a role in the judgment of heading

Eye fixation related potentials in a target search task

Typically BCI (Brain Computer Interfaces) are found in rehabilitative or restorative applications, often allowing users a medium of communication that is otherwise unavailable through conventional means. Recently, however, there is growing interest in using BCI to assist users in searching for images. A class of neural signals often leveraged in common BCI paradigms are ERPs (Event Related Potentials), which are present in the EEG (Electroencephalograph) signals from users in response to various sensory events. One such ERP is the P300, and is typically elicited in an oddball experiment where a subject’s attention is orientated towards a deviant stimulus among a stream of presented images. It has been shown that these types of neural responses can be used to drive an image search or labeling task, where we can rank images by examining the presence of such ERP signals in response to the display of images. To date, systems like these have been demonstrated when presenting sequences of images containing targets at up to 10Hz, however, the target images in these tasks do not necessitate any kind of eye movement for their detection because the targets in the images are quite salient. In this paper we analyse the presence of discriminating signals when they are offset to the time of eye fixations in a visual search task where detection of target images does require eye fixations

New Uses for Sensitivity Analysis: How Different Movement Tasks Effect Limb Model Parameter Sensitivity

Original results for a newly developed eight-order nonlinear limb antagonistic muscle model of elbow flexion and extension are presented. A wider variety of sensitivity analysis techniques are used and a systematic protocol is established that shows how the different methods can be used efficiently to complement one another for maximum insight into model sensitivity. It is explicitly shown how the sensitivity of output behaviors to model parameters is a function of the controller input sequence, i.e., of the movement task. When the task is changed (for instance, from an input sequence that results in the usual fast movement task to a slower movement that may also involve external loading, etc.) the set of parameters with high sensitivity will in general also change. Such task-specific use of sensitivity analysis techniques identifies the set of parameters most important for a given task, and even suggests task-specific model reduction possibilities