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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., Competing Interests: Declarations. Competing interests: RA is since 2017 an employee of Tobii AB. The other authors declare no conflicts of interest. Ethics approval: Not applicable. Consent to participate: Not applicable. Consent for publication: Not applicable. Open Practices Statement: There are no data or code associated with the present article., (© 2025. The Author(s).)

Irrespective of the precision, the inaccuracy of a pupil-based eye tracker is about 0.5 ∘ . This paper delves into two factors that potentially increase the inaccuracy of the gaze signal, namely, 1) Pupil-size changes and the pupil-size artefact (PSA) and 2) the putative inability of experienced individuals to precisely refixate a visual target. Experiment 1 utilizes a traditional pupil-CR eye tracker, while Experiment 2 employs a retinal eye tracker, the FreezeEye tracker, eliminating the pupil-based estimation. Results reveal that the PSA significantly affects gaze accuracy, introducing up to 0.5 ∘ inaccuracies during calibration and validation. Corrections based on the relation between pupil size and apparent gaze shift substantially reduce inaccuracies, underscoring the PSA's influence on eye-tracking quality. Conversely, Experiment 2 demonstrates humans' precise refixation abilities, suggesting that the accuracy of the gaze signal is not limited by human refixation inconsistencies., Competing Interests: Declarations. Competing interests: RA is since 2017 an employee of Tobii AB. MNo, AS and MS are co-owners and RK is an employee of Inoko Vision. Ethics approval: This research project does not belong to the regimen of the Dutch Act on Medical Research Involving Human Subjects, and therefore there is no need for approval of a Medical Ethics Committee. However, the present study is approved by the Ethics Committee of the Faculty of Social and Behavioural Sciences of Utrecht University and filed under number 24-0055 (Experiment 1) and 24-0060 (Experiment 2). Consent to participate: Participants were authors on the paper gave consent to participate. Consent for publication: Not applicable. Open Practices Statement: There are no data associated with the present article., (© 2024. The Author(s).)

Eye tracking technology has become increasingly prevalent in scientific research, offering unique insights into oculomotor and cognitive processes. The present article explores the relationship between scientific theory, the research question, and the use of eye-tracking technology. It aims to guide readers in determining if eye tracking is suitable for their studies and how to formulate relevant research questions. Examples from research on oculomotor control, reading, scene perception, task execution, visual expertise, and instructional design are used to illustrate the connection between theory and eye-tracking data. These examples may serve as inspiration to researchers new to eye tracking. In summarizing the examples, three important considerations emerge: (1) whether the study focuses on describing eye movements or uses them as a proxy for e.g., perceptual, or cognitive processes, (2) the logical chain from theory to predictions, and (3) whether the study is of an observational or idea-testing nature. We provide a generic scheme and a set of specific questions that may help researchers formulate and explicate their research question using eye tracking., Competing Interests: Declarations. Competing interests: RA is since 2017 an employee of Tobii AB. The other authors declare no competing interests. Ethics approval: Not applicable. Consent to participate: Not applicable. Consent for publication: Not applicable. Open practices statement: There are no data or code associated with the present article., (© 2024. The Author(s).)

When lab resources are shared among multiple research projects, issues such as experimental integrity, replicability, and data safety become important. Different research projects often need different software and settings that may well conflict with one another, and data collected for one project may not be safeguarded from exposure to researchers from other projects. In this paper we provide an infrastructure design and an open-source tool, labManager, that render multi-user lab facilities in the behavioral sciences accessible to research projects with widely varying needs. The solutions proposed ensure ease of management while simultaneously offering maximum flexibility by providing research projects with fully separated bare metal environments. This solution also ensures that collected data is kept separate, and compliant with relevant ethical standards and regulations such as General Data Protection Regulation (GDPR) legislation. Furthermore, we discuss preconditions for running shared lab facilities and provide practical advice., (© 2024. The Author(s).)

In human interactions, gaze may be used to acquire information for goal-directed actions, to acquire information related to the interacting partner's actions, and in the context of multimodal communication. At present, there are no models of gaze behavior in the context of vision that adequately incorporate these three components. In this study, we aimed to uncover and quantify patterns of within-person gaze-action coupling, gaze-gesture and gaze-speech coupling, and coupling between one person's gaze and another person's manual actions, gestures, or speech (or exogenous attraction of gaze) during dyadic collaboration. We showed that in the context of a collaborative Lego Duplo-model copying task, within-person gaze-action coupling is strongest, followed by within-person gaze-gesture coupling, and coupling between gaze and another person's actions. When trying to infer gaze location from one's own manual actions, gestures, or speech or that of the other person, only one's own manual actions were found to lead to better inference compared to a baseline model. The improvement in inferring gaze location was limited, contrary to what might be expected based on previous research. We suggest that inferring gaze location may be most effective for constrained tasks in which different manual actions follow in a quick sequence, while gaze-gesture and gaze-speech coupling may be stronger in unconstrained conversational settings or when the collaboration requires more negotiation. Our findings may serve as an empirical foundation for future theory and model development, and may further be relevant in the context of action/intention prediction for (social) robotics and effective human-robot interaction., Competing Interests: Declarations. Competing Interests: The authors report that there are no competing interests to declare. Ethics Approval: This study was performed in line with the principles of the Declaration of Helsinki. The study was approved by the Ethics Committee of the Faculty of Social and Behavioural Sciences of Utrecht University (protocol number 22-0206) Consent to Participate: All participants gave written informed consent. Consent for Publication: The authors affirm that human research participants provided informed consent for publication of the videos available at https://osf.io/2q6f4/. Open Practices Statement: Data files and example videos are available at https://osf.io/2q6f4/. The experiment and analyses were not preregistered., (© 2024. The Author(s).)

We built a novel setup to record large gaze shifts (up to 140 ∘ ). The setup consists of a wearable eye tracker and a high-speed camera with fiducial marker technology to track the head. We tested our setup by replicating findings from the classic eye-head gaze shift literature. We conclude that our new inexpensive setup is good enough to investigate the dynamics of large eye-head gaze shifts. This novel setup could be used for future research on large eye-head gaze shifts, but also for research on gaze during e.g., human interaction. We further discuss reference frames and terminology in head-free eye tracking. Despite a transition from head-fixed eye tracking to head-free gaze tracking, researchers still use head-fixed eye movement terminology when discussing world-fixed gaze phenomena. We propose to use more specific terminology for world-fixed phenomena, including gaze fixation, gaze pursuit, and gaze saccade., (© 2024. The Author(s).)

A guideline is proposed that comprises the minimum items to be reported in research studies involving an eye tracker and human or non-human primate participant(s). This guideline was developed over a 3-year period using a consensus-based process via an open invitation to the international eye tracking community. This guideline will be reviewed at maximum intervals of 4 years., (© 2023. The Author(s).)

We present a deep learning method for accurately localizing the center of a single corneal reflection (CR) in an eye image. Unlike previous approaches, we use a convolutional neural network (CNN) that was trained solely using synthetic data. Using only synthetic data has the benefit of completely sidestepping the time-consuming process of manual annotation that is required for supervised training on real eye images. To systematically evaluate the accuracy of our method, we first tested it on images with synthetic CRs placed on different backgrounds and embedded in varying levels of noise. Second, we tested the method on two datasets consisting of high-quality videos captured from real eyes. Our method outperformed state-of-the-art algorithmic methods on real eye images with a 3-41.5% reduction in terms of spatial precision across data sets, and performed on par with state-of-the-art on synthetic images in terms of spatial accuracy. We conclude that our method provides a precise method for CR center localization and provides a solution to the data availability problem, which is one of the important common roadblocks in the development of deep learning models for gaze estimation. Due to the superior CR center localization and ease of application, our method has the potential to improve the accuracy and precision of CR-based eye trackers., (© 2023. The Author(s).)

Blinks, the closing and opening of the eyelids, are used in a wide array of fields where human function and behavior are studied. In data from video-based eye trackers, blink rate and duration are often estimated from the pupil-size signal. However, blinks and their parameters can be estimated only indirectly from this signal, since it does not explicitly contain information about the eyelid position. We ask whether blinks detected from an eye openness signal that estimates the distance between the eyelids (EO blinks) are comparable to blinks detected with a traditional algorithm using the pupil-size signal (PS blinks) and how robust blink detection is when data quality is low. In terms of rate, there was an almost-perfect overlap between EO and PS blink (F1 score: 0.98) when the head was in the center of the eye tracker's tracking range where data quality was high and a high overlap (F1 score 0.94) when the head was at the edge of the tracking range where data quality was worse. When there was a difference in blink rate between EO and PS blinks, it was mainly due to data loss in the pupil-size signal. Blink durations were about 60 ms longer in EO blinks compared to PS blinks. Moreover, the dynamics of EO blinks was similar to results from previous literature. We conclude that the eye openness signal together with our proposed blink detection algorithm provides an advantageous method to detect and describe blinks in greater detail., (© 2024. The Author(s).)

According to the proposal for a minimum reporting guideline for an eye tracking study by Holmqvist et al. (2022), the accuracy (in degrees) of eye tracking data should be reported. Currently, there is no easy way to determine accuracy for wearable eye tracking recordings. To enable determining the accuracy quickly and easily, we have produced a simple validation procedure using a printable poster and accompanying Python software. We tested the poster and procedure with 61 participants using one wearable eye tracker. In addition, the software was tested with six different wearable eye trackers. We found that the validation procedure can be administered within a minute per participant and provides measures of accuracy and precision. Calculating the eye-tracking data quality measures can be done offline on a simple computer and requires no advanced computer skills., (© 2023. The Author(s).)

How well can modern wearable eye trackers cope with head and body movement? To investigate this question, we asked four participants to stand still, walk, skip, and jump while fixating a static physical target in space. We did this for six different eye trackers. All the eye trackers were capable of recording gaze during the most dynamic episodes (skipping and jumping). The accuracy became worse as movement got wilder. During skipping and jumping, the biggest error was 5.8 ∘ . However, most errors were smaller than 3 ∘ . We discuss the implications of decreased accuracy in the context of different research scenarios., (© 2022. The Author(s).)

Estimating the gaze direction with a digital video-based pupil and corneal reflection (P-CR) eye tracker is challenging partly since a video camera is limited in terms of spatial and temporal resolution, and because the captured eye images contain noise. Through computer simulation, we evaluated the localization accuracy of pupil-, and CR centers in the eye image for small eye rotations (≪ 1 deg). Results highlight how inaccuracies in center localization are related to 1) how many pixels the pupil and CR span in the eye camera image, 2) the method to compute the center of the pupil and CRs, and 3) the level of image noise. Our results provide a possible explanation to why the amplitude of small saccades may not be accurately estimated by many currently used video-based eye trackers. We conclude that eye movements with arbitrarily small amplitudes can be accurately estimated using the P-CR eye-tracking principle given that the level of image noise is low and the pupil and CR span enough pixels in the eye camera, or if localization of the CR is based on the intensity values in the eye image instead of a binary representation., (© 2022. The Author(s).)

In this paper, we present a review of how the various aspects of any study using an eye tracker (such as the instrument, methodology, environment, participant, etc.) affect the quality of the recorded eye-tracking data and the obtained eye-movement and gaze measures. We take this review to represent the empirical foundation for reporting guidelines of any study involving an eye tracker. We compare this empirical foundation to five existing reporting guidelines and to a database of 207 published eye-tracking studies. We find that reporting guidelines vary substantially and do not match with actual reporting practices. We end by deriving a minimal, flexible reporting guideline based on empirical research (Section "An empirically based minimal reporting guideline")., (© 2022. The Author(s).)

Eye trackers are applied in many research fields (e.g., cognitive science, medicine, marketing research). To give meaning to the eye-tracking data, researchers have a broad choice of classification methods to extract various behaviors (e.g., saccade, blink, fixation) from the gaze signal. There is extensive literature about the different classification algorithms. Surprisingly, not much is known about the effect of fixation and saccade selection rules that are usually (implicitly) applied. We want to answer the following question: What is the impact of the selection-rule parameters (minimal saccade amplitude and minimal fixation duration) on the distribution of fixation durations? To answer this question, we used eye-tracking data with high and low quality and seven different classification algorithms. We conclude that selection rules play an important role in merging and selecting fixation candidates. For eye-tracking data with good-to-moderate precision (RMSD < 0.5 ∘ ), the classification algorithm of choice does not matter too much as long as it is sensitive enough and is followed by a rule that selects saccades with amplitudes larger than 1.0 ∘ and a rule that selects fixations with duration longer than 60 ms. Because of the importance of selection, researchers should always report whether they performed selection and the values of their parameters., (© 2021. The Author(s).)

The pupil size artefact (PSA) is the gaze deviation reported by an eye tracker during pupil size changes if the eye does not rotate. In the present study, we ask three questions: 1) how stable is the PSA over time, 2) does the PSA depend on properties of the eye tracker set up, and 3) does the PSA depend on the participants' viewing direction? We found that the PSA is very stable over time for periods as long as 1 year, but may differ between participants. When comparing the magnitude of the PSA between eye trackers, we found the magnitude of the obtained PSA to be related to the direction of the eye-tracker-camera axis, suggesting that the angle between the participants' viewing direction and the camera axis affects the PSA. We then investigated the PSA as a function of the participants' viewing direction. The PSA was non-zero for viewing direction 0 ∘ and depended on the viewing direction. These findings corroborate the suggestion by Choe et al. (Vision Research 118(6755):48-59, 2016), that the PSA can be described by an idiosyncratic and a viewing direction-dependent component. Based on a simulation, we cannot claim that the viewing direction-dependent component of the PSA is caused by the optics of the cornea., (© 2021. The Author(s).)

Due to its reported high sampling frequency and precision, the Tobii Pro Spectrum is of potential interest to researchers who want to study small eye movements during fixation. We test how suitable the Tobii Pro Spectrum is for research on microsaccades by computing data-quality measures and common properties of microsaccades and comparing these to the currently most used system in this field: the EyeLink 1000 Plus. Results show that the EyeLink data provide higher RMS precision and microsaccade rates compared with data acquired with the Tobii Pro Spectrum. However, both systems provide microsaccades with similar directions and shapes, as well as rates consistent with previous literature. Data acquired at 1200 Hz with the Tobii Pro Spectrum provide results that are more similar to the EyeLink, compared to data acquired at 600 Hz. We conclude that the Tobii Pro Spectrum is a useful tool for researchers investigating microsaccades.

We present Titta, an open-source toolbox for controlling eye trackers manufactured by Tobii AB from MATLAB and Python. The toolbox provides a wrapper around the Tobii Pro SDK, providing a convenient graphical participant setup, calibration and validation interface implemented using the PsychToolbox and PsychoPy toolboxes. The toolbox furthermore enables MATLAB and Python experiments to communicate with Tobii Pro Lab through the TalkToProLab tool. This enables experiments to be created and run using the freedom of MATLAB and Python, while the recording can be visualized and analyzed in Tobii Pro Lab. All screen-mounted Tobii eye trackers that are supported by the Tobii Pro SDK are also supported by Titta. At the time of writing, these are the Spectrum, Nano, TX300, T60XL, X3-120, X2-60, X2-30, X60, X120, T60 and T120 from Tobii Pro, and the 4C from Tobii Tech.

Mathematical modeling of nystagmus oscillations is a technique with applications in diagnostics, treatment evaluation, and acuity testing. Modeling is a powerful tool for the analysis of nystagmus oscillations but quality assessment of the input data is needed in order to avoid misinterpretation of the modeling results. In this work, we propose a signal quality metric for nystagmus waveforms, the normalized segment error (NSE). The NSE is based on the energy in the error signal between the observed oscillations and a reconstruction from a harmonic sinusoidal model called the normalized waveform model (NWM). A threshold for discrimination between nystagmus oscillations and disturbances is estimated using simulated signals and receiver operator characteristics (ROC). The ROC is optimized to find noisy segments and abrupt waveform and frequency changes in the simulated data that disturb the modeling. The discrimination threshold, 𝜖, obtained from the ROC analysis, is applied to real recordings of nystagmus data in order to determine whether a segment is of high quality or not. The NWM parameters from both the simulated dataset and the nystagmus recordings are analyzed for the two classes suggested by the threshold. The optimized 𝜖 yielded a true-positive rate and a false-positive rate of 0.97 and 0.07, respectively, for the simulated data. The results from the NWM parameter analysis show that they are consistent with the known values of the simulated signals, and that the method estimates similar model parameters when performing analysis of repeated recordings from one subject.

Mobile head-worn eye trackers allow researchers to record eye-movement data as participants freely move around and interact with their surroundings. However, participant behavior may cause the eye tracker to slip on the participant's head, potentially strongly affecting data quality. To investigate how this eye-tracker slippage affects data quality, we designed experiments in which participants mimic behaviors that can cause a mobile eye tracker to move. Specifically, we investigated data quality when participants speak, make facial expressions, and move the eye tracker. Four head-worn eye-tracking setups were used: (i) Tobii Pro Glasses 2 in 50 Hz mode, (ii) SMI Eye Tracking Glasses 2.0 60 Hz, (iii) Pupil-Labs' Pupil in 3D mode, and (iv) Pupil-Labs' Pupil with the Grip gaze estimation algorithm as implemented in the EyeRecToo software. Our results show that whereas gaze estimates of the Tobii and Grip remained stable when the eye tracker moved, the other systems exhibited significant errors (0.8-3.1 ∘ increase in gaze deviation over baseline) even for the small amounts of glasses movement that occurred during the speech and facial expressions tasks. We conclude that some of the tested eye-tracking setups may not be suitable for investigating gaze behavior when high accuracy is required, such as during face-to-face interaction scenarios. We recommend that users of mobile head-worn eye trackers perform similar tests with their setups to become aware of its characteristics. This will enable researchers to design experiments that are robust to the limitations of their particular eye-tracking setup.

We present SMITE, a toolbox for the measurement of eye movements using eye trackers manufactured by SMI GmbH. The toolbox provides a wrapper around the iViewX SDK provided by SMI, allowing simple integration of SMI eye trackers into Psychophysics Toolbox and PsychoPy programs. The toolbox provides a graphical interface for participant setup and calibration that is implemented natively in Psychophysics Toolbox and PsychoPy drawing commands, as well as providing several convenience features for, inter alia, creating gaze-contingent experiments and working with two-computer setups. Given that SMI GmbH and its support department have closed down, it is expected that this toolbox will provide owners of SMI eye trackers with an important new way to continue to create experiments with their systems. The eye trackers supported by this toolbox are the SMI HiSpeed 1250, SMI RED systems, SMI RED-m, SMI RED250mobile, and SMI REDn.

Eye tracking is a useful tool when studying the oscillatory eye movements associated with nystagmus. However, this oscillatory nature of nystagmus is problematic during calibration since it introduces uncertainty about where the person is actually looking. This renders comparisons between separate recordings unreliable. Still, the influence of the calibration protocol on eye movement data from people with nystagmus has not been thoroughly investigated. In this work, we propose a calibration method using Procrustes analysis in combination with an outlier correction algorithm, which is based on a model of the calibration data and on the geometry of the experimental setup. The proposed method is compared to previously used calibration polynomials in terms of accuracy, calibration plane distortion and waveform robustness. Six recordings of calibration data, validation data and optokinetic nystagmus data from people with nystagmus and seven recordings from a control group were included in the study. Fixation errors during the recording of calibration data from the healthy participants were introduced, simulating fixation errors caused by the oscillatory movements found in nystagmus data. The outlier correction algorithm improved the accuracy for all tested calibration methods. The accuracy and calibration plane distortion performance of the Procrustes analysis calibration method were similar to the top performing mapping functions for the simulated fixation errors. The performance in terms of waveform robustness was superior for the Procrustes analysis calibration compared to the other calibration methods. The overall performance of the Procrustes calibration methods was best for the datasets containing errors during the calibration.

Manual classification is still a common method to evaluate event detection algorithms. The procedure is often as follows: Two or three human coders and the algorithm classify a significant quantity of data. In the gold standard approach, deviations from the human classifications are considered to be due to mistakes of the algorithm. However, little is known about human classification in eye tracking. To what extent do the classifications from a larger group of human coders agree? Twelve experienced but untrained human coders classified fixations in 6 min of adult and infant eye-tracking data. When using the sample-based Cohen's kappa, the classifications of the humans agreed near perfectly. However, we found substantial differences between the classifications when we examined fixation duration and number of fixations. We hypothesized that the human coders applied different (implicit) thresholds and selection rules. Indeed, when spatially close fixations were merged, most of the classification differences disappeared. On the basis of the nature of these intercoder differences, we concluded that fixation classification by experienced untrained human coders is not a gold standard. To bridge the gap between agreement measures (e.g., Cohen's kappa) and eye movement parameters (fixation duration, number of fixations), we suggest the use of the event-based F1 score and two new measures: the relative timing offset (RTO) and the relative timing deviation (RTD).

Technological advancements in combination with significant reductions in price have made it practically feasible to run experiments with multiple eye trackers. This enables new types of experiments with simultaneous recordings of eye movement data from several participants, which is of interest for researchers in, e.g., social and educational psychology. The Lund University Humanities Laboratory recently acquired 25 remote eye trackers, which are connected over a local wireless network. As a first step toward running experiments with this setup, demanding situations with real time sharing of gaze data were investigated in terms of network performance as well as clock and screen synchronization. Results show that data can be shared with a sufficiently low packet loss (0.1 %) and latency (M = 3 ms, M A D = 2 ms) across 8 eye trackers at a rate of 60 Hz. For a similar performance using 24 computers, the send rate needs to be reduced to 20 Hz. To help researchers conduct similar measurements on their own multi-eye-tracker setup, open source software written in Python and PsychoPy are provided. Part of the software contains a minimal working example to help researchers kick-start experiments with two or more eye trackers.

Almost all eye-movement researchers use algorithms to parse raw data and detect distinct types of eye movement events, such as fixations, saccades, and pursuit, and then base their results on these. Surprisingly, these algorithms are rarely evaluated. We evaluated the classifications of ten eye-movement event detection algorithms, on data from an SMI HiSpeed 1250 system, and compared them to manual ratings of two human experts. The evaluation focused on fixations, saccades, and post-saccadic oscillations. The evaluation used both event duration parameters, and sample-by-sample comparisons to rank the algorithms. The resulting event durations varied substantially as a function of what algorithm was used. This evaluation differed from previous evaluations by considering a relatively large set of algorithms, multiple events, and data from both static and dynamic stimuli. The main conclusion is that current detectors of only fixations and saccades work reasonably well for static stimuli, but barely better than chance for dynamic stimuli. Differing results across evaluation methods make it difficult to select one winner for fixation detection. For saccade detection, however, the algorithm by Larsson, Nyström and Stridh (IEEE Transaction on Biomedical Engineering, 60(9):2484-2493,2013) outperforms all algorithms in data from both static and dynamic stimuli. The data also show how improperly selected algorithms applied to dynamic data misestimate fixation and saccade properties.

Recording eye movement data with high quality is often a prerequisite for producing valid and replicable results and for drawing well-founded conclusions about the oculomotor system. Today, many aspects of data quality are often informally discussed among researchers but are very seldom measured, quantified, and reported. Here we systematically investigated how the calibration method, aspects of participants' eye physiologies, the influences of recording time and gaze direction, and the experience of operators affect the quality of data recorded with a common tower-mounted, video-based eyetracker. We quantified accuracy, precision, and the amount of valid data, and found an increase in data quality when the participant indicated that he or she was looking at a calibration target, as compared to leaving this decision to the operator or the eyetracker software. Moreover, our results provide statistical evidence of how factors such as glasses, contact lenses, eye color, eyelashes, and mascara influence data quality. This method and the results provide eye movement researchers with an understanding of what is required to record high-quality data, as well as providing manufacturers with the knowledge to build better eyetrackers.

Eye movement sequences-or scanpaths-vary depending on the stimulus characteristics and the task (Foulsham & Underwood Journal of Vision, 8(2), 6:1-17, 2008; Land, Mennie, & Rusted, Perception, 28, 1311-1328, 1999). Common methods for comparing scanpaths, however, are limited in their ability to capture both the spatial and temporal properties of which a scanpath consists. Here, we validated a new method for scanpath comparison based on geometric vectors, which compares scanpaths over multiple dimensions while retaining positional and sequential information (Jarodzka, Holmqvist, & Nyström, Symposium on Eye-Tracking Research and Applications (pp. 211-218), 2010). "MultiMatch" was tested in two experiments and pitted against ScanMatch (Cristino, Mathôt, Theeuwes, & Gilchrist, Behavior Research Methods, 42, 692-700, 2010), the most comprehensive adaptation of the popular Levenshtein method. In Experiment 1, we used synthetic data, demonstrating the greater sensitivity of MultiMatch to variations in spatial position. In Experiment 2, real eye movement recordings were taken from participants viewing sequences of dots, designed to elicit scanpath pairs with commonalities known to be problematic for algorithms (e.g., when one scanpath is shifted in locus or when fixations fall on either side of an AOI boundary). The results illustrate the advantages of a multidimensional approach, revealing how two scanpaths differ. For instance, if one scanpath is the reverse copy of another, the difference is in the direction but not the positions of fixations; or if a scanpath is scaled down, the difference is in the length of the saccadic vectors but not in the overall shape. As well as having enormous potential for any task in which consistency in eye movements is important (e.g., learning), MultiMatch is particularly relevant for "eye movements to nothing" in mental imagery and embodiment-of-cognition research, where satisfactory scanpath comparison algorithms are lacking.

Inherited pathogenic mutations in the mismatch repair (MMR) genes, MSH2, MLH1, MSH6, and PMS2 predispose to Lynch syndrome (LS). However, the finding of a variant or variants of uncertain significance (VUS) in affected family members complicates the risk assessment. Here, we describe a putative LS family carrying VUS in both MSH2 (c.2768T>A, p.Val923Glu) and MSH6 (c.3563G>A, p.Ser1188Asn). Two colorectal cancer (CRC) patients were studied for mutations and identified as carriers of both variants. In spite of a relatively high mean age of cancer onset (59.5 years) in the family, many CRC patients and the tumor pathological data suggested that the missense variation in MSH2, the more common susceptibility gene in LS, would be the predisposing alteration. However, MSH2 VUS was surprisingly found to be MMR proficient in an in vitro MMR assay and a tolerant alteration in silico. By supplying evidence that instead of MSH2 p.Val923Glu the MSH6 p.Ser1188Asn variant is completely MMR-deficient, the present study confirms the previous findings, and suggests that MSH6 (c.3563G>A, p.Ser1188Asn) is the pathogenic mutation in the family. Moreover, our results strongly support the strategy to functionally assess all identified VUS before predictive gene testing and genetic counseling are offered to a family.

Event detection is used to classify recorded gaze points into periods of fixation, saccade, smooth pursuit, blink, and noise. Although there is an overall consensus that current algorithms for event detection have serious flaws and that a de facto standard for event detection does not exist, surprisingly little work has been done to remedy this problem. We suggest a new velocity-based algorithm that takes several of the previously known limitations into account. Most important, the new algorithm identifies so-called glissades, a wobbling movement at the end of many saccades, as a separate class of eye movements. Part of the solution involves designing an adaptive velocity threshold that makes the event detection less sensitive to variations in noise level and the algorithm settings-free for the user. We demonstrate the performance of the new algorithm on eye movements recorded during reading and scene perception and compare it with two of the most commonly used algorithms today. Results show that, unlike the currently used algorithms, fixations, saccades, and glissades are robustly identified by the new algorithm. Using this algorithm, we found that glissades occur in about half of the saccades, during both reading and scene perception, and that they have an average duration close to 24 msec. Due to the high prevalence and long durations of glissades, we argue that researchers must actively choose whether to assign the glissades to saccades or fixations; the choice affects dependent variables such as fixation and saccade duration significantly. Current algorithms do not offer this choice, and their assignments of each glissade are largely arbitrary.

Recently, we have performed a population based study to analyse the frequency of colorectal cancer related MLH1 and MSH2 missense mutations in the Danish population. Half of the analyzed mutations were rare and most likely only present in the families where they were identified originally. Some of the missense mutations were located in conserved regions in the MLH1 and MSH2 proteins indicating a relation to disease development. In the present study, we functionally characterized 10 rare missense mutations in MLH1 and MSH2 identified in 13 Danish CRC families. To elucidate the pathogenicity of the missense mutations, we carried out in vitro functional analyses. The missense mutations were analyzed for their effect on protein expression and repair efficiency. The results of the functional analysis were correlated with clinical data on the families carrying these mutations. Eight missense mutations resulted in proteins with expression and repair efficiency similar to the wild type. One missense mutation (MSH2 p.Met688Val) caused reduced protein expression and one (MSH2 p.Leu187Arg) caused both reduced protein expression and repair deficiency. The MSH2 p.Leu187Arg mutation was found in an Amsterdam II family presenting with high microsatellite instability and loss of MSH2 and MSH6 proteins in tumours. In conclusion, only 1/10 missense mutations displayed repair deficiency and could be classified as pathogenic. No final conclusion can be drawn on the MSH2 p.Met688Val mutation, which caused reduced protein expression. Although, no deficiencies have been identified in the proteins harbouring the other missense mutations, pathogenicity of these variants cannot be unambiguously excluded.

Lynch syndrome is an inherited cancer syndrome caused by germline mutations in mismatch repair (MMR) genes MLH1, MSH2, MSH6 and PMS2. LS predisposes to high risk of early-onset colorectal, endometrial and other tumors. Patients with Lynch syndrome have also been shown to have an elevated risk for pancreatic cancer (PC). In this study, we aimed to estimate the frequency of suspected Lynch syndrome among a series of 135 PC patients. Further, we wanted to determine the frequency of MMR gene mutations in the suspected Lynch syndrome cases. We also aimed to verify the pathogenicity of any novel non-truncating variants we might detect with a functional assay. Based on personal and/or familial cancer history, 19 patients were classified as suspected Lynch syndrome cases. DNA material for mutation analysis was available for eleven of them. Four patients were found to carry a total of five MLH1 or MSH2 variants. Of these, MSH2-Q402X, MSH2-G322D, and MLH1-K618A had been previously reported, while the MSH2-E205Q and MSH2-V367I variants were novel. MSH2-Q402X is a known stop mutation and reported here for the first time here in association with PC. MLH1-K618A was found in the unaffected branch of a kindred, suggesting that it may be a polymorphism or a low penetrance variant. MSH2-G322D likely does not cause a MMR defect, although this variant has also been associated with breast cancer as indeed seen in our patient. The novel variants MSH2-E205Q and MSH2-V367I were found in the same patient. Both novel variants were however functional in the applied MMR assay. Our findings suggest that only a small subset of pancreatic cancer patients carry pathogenic MMR mutations.

Objective: The adenomatous polyposis coli (APC) and beta-catenin (CTNNB1) genes are the two major components of the Wnt signaling pathway that has been shown to play an important role in the formation of certain cancers. The overactivation of the pathway, which results in abnormal accumulation of beta-catenin protein in nuclei, contributes to most colorectal cancers (CRCs), both sporadic and hereditary, as well as sporadic endometrial cancers (ECs). Here, we studied the involvement of APC and beta-catenin in hereditary nonpolyposis colorectal cancer (HNPCC)-related ECs, and compared the expression patterns to those in HNPCC-related CRCs., Materials and Methods: Nineteen ECs and 31 CRCs derived from HNPCC patients were immunohistochemically stained with anti-APC- and anti-beta-catenin-antibodies., Results: Tumor-specific loss of APC was observed in 16 of endometrial cancers (3 of 19) and in 39 of colorectal cancers (12 of 31). Consistently, the loss of APC expression was associated with nuclear beta-catenin staining. Altogether, aberrant beta-catenin localization was observed in 53 of ECs (10 of 19) as compared to 84 of CRCs (26 of 31) (P=0.02)., Conclusion: Our results suggest a frequent overactivation of the Wnt signaling pathway in hereditary endometrial cancer. In accordance with studies on sporadic cancers, abnormal accumulation of beta-catenin protein in nuclei occurred much less frequently in HNPCC-related ECs than CRCs, which may reflect organ-specific differences in their pathogenesis.