Models Of Eye Movements Research Articles

Model-Based Separation, Detection, and Classification of Eye Movements.

We present a physiologically motivated eye movement analysis framework for model-based separation, detection, and classification (MBSDC) of eye movements. By estimating kinematic and neural controller signals for saccades, smooth pursuit, and fixational eye movements in a mechanistic model of the oculomotor system we are able to separate and analyze these eye movements independently. We extended an established oculomotor model for horizontal eye movements by neural controller signals and by a blink artifact model. To estimate kinematic (position, velocity, acceleration, forces) and neural controller signals from eye position data, we employ Kalman smoothing and sparse input estimation techniques. The estimated signals are used for detecting saccade start and end points, and for classifying the recording into saccades, smooth pursuit, fixations, post-saccadic oscillations, and blinks. On simulated data, the reconstruction error of the velocity profiles is about half the error value obtained by the commonly employed approach of filtering and numerical differentiation. In experiments with smooth pursuit data from human subjects, we observe an accurate signal separation. In addition, in neural recordings from non-human primates, the estimated neural controller signals match the real recordings strikingly well. The MBSDC framework enables the analysis of multi-type eye movement recordings and provides a physiologically motivated approach to study motor commands and might aid the discovery of new digital biomarkers. The proposed framework provides a model-based approach for a wide variety of eye movement analysis tasks.

A New Type of Eye Movement Model Based on Recurrent Neural Networks for Simulating the Gaze Behavior of Human Reading

Traditional eye movement models are based on psychological assumptions and empirical data that are not able to simulate eye movement on previously unseen text data. To address this problem, a new type of eye movement model is presented and tested in this paper. In contrast to conventional psychology‐based eye movement models, ours is based on a recurrent neural network (RNN) to generate a gaze point prediction sequence, by using the combination of convolutional neural networks (CNN), bidirectional long short‐term memory networks (LSTM), and conditional random fields (CRF). The model uses the eye movement data of a reader reading some texts as training data to predict the eye movements of the same reader reading a previously unseen text. A theoretical analysis of the model is presented to show its excellent convergence performance. Experimental results are then presented to demonstrate that the proposed model can achieve similar prediction accuracy while requiring fewer features than current machine learning models.

Supplemental Material for Word Frequency, Predictability, and Return-Sweep Saccades: Towards the Modeling of Eye Movements During Paragraph Reading

Supplemental Material for Word Frequency, Predictability, and Return-Sweep Saccades: Towards the Modeling of Eye Movements During Paragraph Reading

The influence of target distance on perceptual self-motion thresholds and the vestibulo-ocular reflex during interaural translation.

An elegant and influential mathematical model of eye movements is the geometric compensation required for visual fixation location in the translational vestibulo-ocular reflex (VOR). Compensatory eye velocity scales with the inverse of fixation distance during head translation because larger angular eye movements are required to minimize retinal slip during head translation when targets are closer. This model has been extensively verified in experiments. Since the VOR and vestibular perception have shared anatomic pathways, we asked whether the same scaling may affect motion perception. Since perception does not require the linear-to-angular transformation required for the translational VOR, we hypothesized that perception would not scale with target distance. Subjects were tested with a motion direction-recognition threshold task in which they reported their perception of small translations of their body. Thresholds were measured in three conditions: (1) with a near target (0.20m) that extinguished just before each motion; (2) with a far target (0.47m); 3) with no target. The subject was always in darkness during motion. Thresholds were 0.59, 0.61 and 0.61cm/s, respectively. Translational VOR sensitivity (eye angular velocity divided by head translation velocity) was also measured and modulated with target distance. The scaling ratio of responses for the near vs. far target was 0.97 for perceptual thresholds, which was significantly different from the compensatory ratio (2.35; P<0.001) and the translational VOR scaling ratio (1.59; P=0.007) but not from no compensation (1.00; P=0.93). Thus, we conclude that despite shared anatomy for the VOR and perception, the brain processes signals according to the geometric functional constraints of each task.

Design analysis of distributed control system (DCS) room with curved monitor

This paper presents the design analysis of distributed control system room with curved monitor. The objective of this research is to seek the possibility of replacement current monitor using eye ergonomic and human factor analysis. The research are backed up with three theories of Fitts’s Law, Horopter Theory, and Westheimer’s Saccadic Eye Movement Model. Fitts Law used to illustrate the general powers and faults of humans and machines. Horopter used to match another distinctive of our visual ergonomic: the placement of surfaces of monitors. Saccadic eye movements used to describe the express movements of eyes with monitor shape. The survey was conducted to operators seeking possibility to use curved monitor to replace the flat monitor. The researcher used simulator for Boiling Water Reactor (BWR) and its training movies and asking the participant doing the experiment then filling up questionnaires. Participants will be selected from the panel DCS operator doing their job in oil, gas and petrochemical manufacturing plants. The questionnaires are analysed by Rasch Model Analysis, to seek the benefit of curved monitor than flat monitor. Rasch analysis to find internal test reliability and conclusion out the each item analysis on visual ergonomic and human factor interaction.

OB1-reader: A model of word recognition and eye movements in text reading.

Decades of reading research have led to sophisticated accounts of single-word recognition and, in parallel, accounts of eye-movement control in text reading. Although these two endeavors have strongly advanced the field, their relative independence has precluded an integrated account of the reading process. To bridge the gap, we here present a computational model of reading, OB1-reader, which integrates insights from both literatures. Key features of OB1 are as follows: (1) parallel processing of multiple words, modulated by an attentional window of adaptable size; (2) coding of input through a layer of open bigram nodes that represent pairs of letters and their relative position; (3) activation of word representations based on constituent bigram activity, competition with other word representations and contextual predictability; (4) mapping of activated words onto a spatiotopic sentence-level representation to keep track of word order; and (5) saccade planning, with the saccade goal being dependent on the length and activation of surrounding word units, and the saccade onset being influenced by word recognition. A comparison of simulation results with experimental data shows that the model provides a fruitful and parsimonious theoretical framework for understanding reading behavior. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Does face-drawing experience enhance face processing abilities? Evidence from hidden Markov modeling of eye movements

Does face-drawing experience enhance face processing abilities? Evidence from hidden Markov modeling of eye movements

Effectiveness of eye movement modeling examples in problem solving: The role of verbal ambiguity and prior knowledge

Eye movement modeling examples (EMME) are video modeling examples with the model's eye movements superimposed. Thus far, EMME on problem-solving tasks seem to be effective for guiding students' attention, but this does not translate into higher learning outcomes. We therefore investigated the role of ambiguity of the verbal explanation and prior knowledge in the effectiveness of EMME on geometry problems. In Experiment 1, 57 university students observed EMME or regular video modeling examples (ME) with ambiguous verbal explanations. Eye-tracking data revealed that –as in prior research with unambiguous explanations- EMME successfully guided students' attention but did not improve test performance, possibly due to students' high prior knowledge. Therefore, Experiment 2, was conducted with 108 secondary education students who had less prior knowledge, using a 2 (EMME/ME) x 2 (ambiguous/unambiguous explanations) between-subjects design. Verbal ambiguity did not affect learning, but students in the EMME conditions outperformed those in the ME conditions.

注意引导和认知加工：眼动榜样样例的教学作用

注意引导和认知加工：眼动榜样样例的教学作用

Choosing a foveal goal recruits the saccadic system during smooth pursuit.

Models of smooth pursuit eye movements stabilize an object's retinal image, yet pursuit is peppered with small, destabilizing "catch-up" saccades. Catch-up saccades might help follow a small, spot stimulus used in most pursuit experiments, since fewer of them occur with large stimuli. However, they can return when a large stimulus has a small central feature. It may be that a central feature on a large object automatically recruits the saccadic system. Alternatively, a cognitive choice is made that the feature is the pursuit goal, and the saccadic system is then recruited to pursue it. Observers pursued a 5-dot stimulus composed of a central dot surrounded by four peripheral dots arranged as a diamond. An attention task specified the pursuit goal as either the central element, or the diamond gestalt. Fewer catch-up saccades occurred with the Gestalt goal than with the central goal, although the additional saccades with the central goal neither enhanced nor impeded pursuit. Furthermore, removing the central element from the diamond goal further reduced catch-up saccade frequency, indicating that the central element automatically triggered some saccades. Higher saccade frequency was not simply due to narrowly focused attention, since attending a small peripheral diamond during pursuit elicited fewer saccades than attending the diamond positioned foveally. The results suggest some saccades are automatically elicited by a small central element, but when it is chosen as the pursuit goal the saccadic system is further recruited to pursue it. NEW & NOTEWORTHY Smooth-pursuit eye movements stabilize retinal image motion to prevent blur. Curiously, smooth pursuit is frequently supplemented by small catchup saccades that could reduce image clarity. Catchup saccades might only be needed to pursue small laboratory stimuli, as they are infrequent during large object pursuit. Yet large objects with central features revive them. Here, we show that voluntarily selecting a feature as the pursuit goal elicits saccades that do not help pursuit.

A Mathematical Model of Optimal Saccadic Eye Movement by a Pair of Muscles

This paper presents a model of saccadic eye movements. Eye movements are considered as being ballistic, since saccades (rapid concurrent movements of both eyes) occur several hundred thousand times per day; visual perception of the environment is interrupted by a saccade. The optimal control was constructed for the motion considered in three consecutively refined assumptions. The controls included in the time-optimal problem were the resultant moment of force exerted by the extraocular muscles, individual moments of force exerted by either muscle of the agonist–antagonist pair, and finally, the rate of change of these moments. This approach is consistent with the view that is currently upheld by physiologists, who believe that a saccade is programmed by the central nervous system before the beginning of an eye movement and is scarcely adjusted during the movement itself. The solution of the optimal control problem and the results obtained by subsequent numerical modeling of saccadic trajectories were compared with the published experimental data. The saccadic trajectories were compared based on the main sequence, the known consistent relationship between saccade amplitude and duration, which is the most widely applied and commonly accepted way of describing saccade data. The main sequence of saccades obtained from the solution of the optimal control problem formulated in the most complete form agreed well with published experimental results.

Dynamic Characteristics of a New Three-Dimensional Linear Homeomorphic Saccade Model.

A linear homeomorphic eye movement model that produces 3D saccadic eye movements consistent with anatomical and physiological evidence is introduced in this second part of a two-paper sequence. Central to the model is the implementation of a time-optimal neural control strategy involving six linear muscle models that faithfully represent the dynamic characteristics of 3D saccades. The muscle is modeled as a parallel combination of viscosity [Formula: see text] and series elasticity [Formula: see text], connected to the parallel combination of active-state tension generator [Formula: see text], viscosity element [Formula: see text], and length tension elastic element [Formula: see text]. The neural input for each muscle is separately maintained while the effective pulling direction is modulated by its respective pulley. The results demonstrate that a time-optimal, 2D commutative neural controller, together with the pulley system, actively functions to implement Listing's law during both static and dynamic simulations and provide an excellent match with the experimental data. The parameters and neural input to the muscles are estimated using a time domain system identification technique from saccade data, with an excellent match between the model estimates and the data. A total of 20 horizontal, 5 vertical and 62 oblique saccades are analyzed.

Word skipping: Effects of word length, predictability, spelling and reading skill.

Readers’ eyes often skip over words as they read. Skipping rates are largely determined by word length; short words are skipped more than long words. However, the predictability of a word in context also impacts skipping rates. Rayner, Slattery, Drieghe and Liversedge reported an effect of predictability on word skipping for even long words (10-13 characters) that extend beyond the word identification span. Recent research suggests that better readers and spellers have an enhanced perceptual span. We explored that whether reading and spelling skill interact with word length and predictability to impact word skipping rates in a large sample (N = 92) of average and poor adult readers. Participants read the items from Rayner et al., while their eye movements were recorded. Spelling skill (zSpell) was assessed using the dictation and recognition tasks developed by Sally Andrews and colleagues. Reading skill (zRead) was assessed from reading speed (words per minute) and comprehension accuracy of three 120 word passages each with 10 comprehension questions. We fit linear mixed models to the target gaze duration data and generalized linear mixed models to the target word skipping data. Target word gaze durations were significantly predicted by zRead, while the skipping likelihoods were significantly predicted by zSpell. Additionally, for gaze durations, zRead significantly interacted with word predictability as better readers relied less on context to support word processing. These effects are discussed in relation to the lexical quality hypothesis and eye movement models of reading.

A self-avoiding walk with neural delays as a model of fixational eye movements

Fixational eye movements show scaling behaviour of the positional mean-squared displacement with a characteristic transition from persistence to antipersistence for increasing time-lag. These statistical patterns were found to be mainly shaped by microsaccades (fast, small-amplitude movements). However, our re-analysis of fixational eye-movement data provides evidence that the slow component (physiological drift) of the eyes exhibits scaling behaviour of the mean-squared displacement that varies across human participants. These results suggest that drift is a correlated movement that interacts with microsaccades. Moreover, on the long time scale, the mean-squared displacement of the drift shows oscillations, which is also present in the displacement auto-correlation function. This finding lends support to the presence of time-delayed feedback in the control of drift movements. Based on an earlier non-linear delayed feedback model of fixational eye movements, we propose and discuss different versions of a new model that combines a self-avoiding walk with time delay. As a result, we identify a model that reproduces oscillatory correlation functions, the transition from persistence to antipersistence, and microsaccades.

The saccadic flow baseline: Accounting for image-independent biases in fixation behavior

Much effort has been made to explain eye guidance during natural scene viewing. However, a substantial component of fixation placement appears to be a set of consistent biases in eye movement behavior. We introduce the concept of saccadic flow, a generalization of the central bias that describes the image-independent conditional probability of making a saccade to (xi+1, yi+1), given a fixation at (xi, yi). We suggest that saccadic flow can be a useful prior when carrying out analyses of fixation locations, and can be used as a submodule in models of eye movements during scene viewing. We demonstrate the utility of this idea by presenting bias-weighted gaze landscapes, and show that there is a link between the likelihood of a saccade under the flow model, and the salience of the following fixation. We also present a minor improvement to our central bias model (based on using a multivariate truncated Gaussian), and investigate the leftwards and coarse-to-fine biases in scene viewing.

Self-regulated learning from illustrated text: Eye movement modelling to support use and regulation of cognitive processes during learning from multimedia.

When learning with text and pictures, learners often fail to adequately process the materials, which can be explained as a failure to self-regulate one's learning by choosing adequate cognitive learning processes. Eye movement modelling examples (EMME) showing how to process multimedia instruction have improved elementary school children's learning from text and pictures in previous studies. We tested whether the positive effects of EMME for improving self-regulated multimedia learning extend to university students and teaching of more comprehensive processing strategies. Moreover, we investigated whether EMME's effectiveness depends upon a learner's cognitive prerequisites. Participants were 50 university students (38 female; M=26.88years) with different study majors. Different prior knowledge aspects were assessed as cognitive prerequisites. Before learning about mitosis from a multimedia instruction, students either received no intervention or saw EMME demonstrating various multimedia learning processes. Learning outcomes and eye movements served as dependent variables. Learners in the EMME group showed more intense processing of pictures and more frequent transitions between text and pictures. Weaker learners showed poorer recall performance after having studied EMME, whereas EMME had no effect on stronger students. In the forced-choice verification task, stronger students benefitted from EMME, whereas no effect occurred for weaker students. The picture-processing time was suited to explain the positive effects of EMME for stronger students. Our results indicate that EMME illustrating a comprehensive set of cognitive processes support multimedia learning for stronger university students.

Effects of eye movement modeling examples on adaptive expertise in medical image diagnosis

Research indicates that expert performance is domain specific and hardly transfers to novel tasks or domains. However, due to technological changes in dynamic work settings, experts sometimes need to adapt and transfer their skills to new task affordances. The present mixed method study investigates whether eye movement modeling examples (EMME) can promote adaptive expertise in medical image diagnosis. Performance, eye tracking, and think-aloud protocol data were obtained from nine medical experts and fourteen medical students. Participants interpreted dynamic visualizations before (baseline) and after (retention, transfer) viewing an expert model's eye movements. Findings indicate that studying eye movement modeling examples had positive effects on performance, task-relevant fixations, and the use of cognitive and metacognitive comprehension strategies. Effects were stronger for the retention than for the transfer task. Medical experts benefitted more from the modeling examples than did medical students. Directions for future research and implications for related domains are discussed.

Using eye movements to model the sequence of text–picture processing for multimedia comprehension

AbstractThis study used eye movement modeling examples (EMME) to support students' integrative processing of verbal and graphical information during the reading of an illustrated text. EMME consists of a replay of eye movements of a model superimposed onto the materials that are processed for accomplishing the task. Specifically, the study investigated the effects of modeling the temporal sequence of text and picture processing as shown in various replays of a model's gazes. Eighty‐four 7th graders were randomly assigned to one of the four experimental conditions: text‐first processing sequence (text‐first EMME), picture‐first processing sequence (picture‐first EMME), picture‐last processing sequence (picture‐last EMME) and no‐EMME (control). Online and offline measures were used.Eye movement indices indicate that only readers in the picture‐first EMME condition spent significantly longer processing the picture and showed stronger integrative processing of verbal and graphical information than students in the no‐EMME condition. Moreover, readers in all EMME conditions outperformed those in the control condition for recall. However, for learning and transfer, only readers in the picture‐first EMME condition were significantly superior to readers of the control condition. Furthermore, both the frequency and duration of integrative processing of verbal and graphical information mediated the effect of condition on learning outcomes.

Optimisation of an exemplar oculomotor model using multi-objective genetic algorithms executed on a GPU-CPU combination

BackgroundParameter optimisation is a critical step in the construction of computational biology models. In eye movement research, computational models are increasingly important to understanding the mechanistic basis of normal and abnormal behaviour. In this study, we considered an existing neurobiological model of fast eye movements (saccades), capable of generating realistic simulations of: (i) normal horizontal saccades; and (ii) infantile nystagmus – pathological ocular oscillations that can be subdivided into different waveform classes. By developing appropriate fitness functions, we optimised the model to existing experimental saccade and nystagmus data, using a well-established multi-objective genetic algorithm. This algorithm required the model to be numerically integrated for very large numbers of parameter combinations. To address this computational bottleneck, we implemented a master-slave parallelisation, in which the model integrations were distributed across the compute units of a GPU, under the control of a CPU.ResultsWhile previous nystagmus fitting has been based on reproducing qualitative waveform characteristics, our optimisation protocol enabled us to perform the first direct fits of a model to experimental recordings. The fits to normal eye movements showed that although saccades of different amplitudes can be accurately simulated by individual parameter sets, a single set capable of fitting all amplitudes simultaneously cannot be determined. The fits to nystagmus oscillations systematically identified the parameter regimes in which the model can reproduce a number of canonical nystagmus waveforms to a high accuracy, whilst also identifying some waveforms that the model cannot simulate. Using a GPU to perform the model integrations yielded a speedup of around 20 compared to a high-end CPU.ConclusionsThe results of both optimisation problems enabled us to quantify the predictive capacity of the model, suggesting specific modifications that could expand its repertoire of simulated behaviours. In addition, the optimal parameter distributions we obtained were consistent with previous computational studies that had proposed the saccadic braking signal to be the origin of the instability preceding the development of infantile nystagmus oscillations. Finally, the master-slave parallelisation method we developed to accelerate the optimisation process can be readily adapted to fit other highly parametrised computational biology models to experimental data.

Eye tracking in Educational Science: Theoretical frameworks and research agendas

Eye tracking is increasingly being used in Educational Science and so has the interest of the eye tracking community grown in this topic. In this paper we briefly introduce the discipline of Educational Science and why it might be interesting to couple it with eye tracking research. We then introduce three major research areas in Educational Science that have already successfully used eye tracking: First, eye tracking has been used to improve the instructional design of computer-based learning and testing environments, often using hyper- or multimedia. Second, eye tracking has shed light on expertise and its development in visual domains, such as chess or medicine. Third, eye tracking has recently been also used to promote visual expertise by means of eye movement modeling examples. We outline the main educational theories for these research areas and indicate where further eye tracking research is needed to expand them.