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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.

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”).

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.

Gaze—where one looks, how long, and when—plays an essential part in human social behavior. While many aspects of social gaze have been reviewed, there is no comprehensive review or theoretical framework that describes how gaze to faces supports face-to-face interaction. In this review, I address the following questions: (1) When does gaze need to be allocated to a particular region of a face in order to provide the relevant information for successful interaction; (2) How do humans look at other people, and faces in particular, regardless of whether gaze needs to be directed at a particular region to acquire the relevant visual information; (3) How does gaze support the regulation of interaction? The work reviewed spans psychophysical research, observational research, and eye-tracking research in both lab-based and interactive contexts. Based on the literature overview, I sketch a framework for future research based on dynamic systems theory. The framework holds that gaze should be investigated in relation to sub-states of the interaction, encompassing sub-states of the interactors, the content of the interaction as well as the interactive context. The relevant sub-states for understanding gaze in interaction vary over different timescales from microgenesis to ontogenesis and phylogenesis. The framework has important implications for vision science, psychopathology, developmental science, and social robotics.

Eye contact is a fundamental aspect of nonverbal communication and therefore important for understanding human interaction. Eye contact has been the subject of research in many disciplines, including communication sciences, social psychology, and psychiatry, and a variety of techniques have been used to measure it. The choice of measurement method has consequences for research outcomes and their interpretation. To ensure that research findings align with study aims and populations, it is essential that methodological choices are well substantiated. Therefore, to enhance the effective examination of eye contact, we performed a literature review of the methods used to study eye contact. We searched Medline, PsycINFO and Web of Science for empirical peer-reviewed articles published in English that described quantitative studies on human eye contact and included a methodological description. The identified studies (N = 109) used two approaches to assess eye contact: direct, i.e., assessing eye contact while it is occurring, and indirect, i.e., assessing eye contact retrospectively (e.g., from video recordings). Within these categories, eight specific techniques were distinguished. Variation was found regarding the reciprocity of eye contact between two individuals, the involvement of an assessor and the behavior of participants while being studied. Measures not involving the interactors in assessment of eye contact and have a higher spatial and temporal resolution, such as eye tracking, have gained popularity. Our results show wide methodological diversity regarding the measurement of eye contact. Although studies often define eye contact as gaze towards an exact location, this may not do justice to the subjective character of eye contact. The various methodologies have hardly ever been compared, limiting the ability to compare findings between studies. Future studies should take notice of the controversy surrounding eye contact measures.

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. Electronic supplementary material The online version of this article (10.3758/s13428-019-01307-0) contains supplementary material, which is available to authorized users.

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.

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 (RMSD0.5

Face-to-face interaction is a primary mode of human social behavior which includes verbal and non-verbal expressions, e.g. speech, gazing, eye contact, facial displays, and gestures (Holler & Levinson, 2019). In this study, we investigated the relation between speech and gaze behavior during 'face-to-face' dialogues between parents and their preadolescent children (9-11 years). 79 child-parent dyads engaged in two semi-structured conversations about family-related topics. We used a state-of-the-art dual-eye tracking setup (Hessels et al. 2019) that is capable of concurrently recording eye movements, frontal video recordings, and audio from two conversational partners. Crucially, the setup is designed in such a way that eye contact can be maintained using half-silvered mirrors, as opposed to e.g. Skype where the camera is located above the screen. Parents and children conversed about two different topics for five minutes each, one 'conflict' (e.g. bedtime, homework) and one 'cooperation' (e.g. organize a party) topic. Preliminary analyses of speech behavior (Figure 1) show that children talked more in the cooperative task and talked less when discussing a topic of disagreement with their parents. Conversely, parents talked more during the conflict-task and less during the cooperative-task. The next step is to combine measures of speech and gaze to investigate the interplay and temporal characteristics of verbal and non-verbal behavior during face-to-face interactions.

Highlights • YOUth is a longitudinal cohort study in the Netherlands that aims to produce and safely store FAIR and high-quality data. • We share our experience and expertise in setting up a high-quality research data infrastructure for sensitive cohort data. • We describe our procedures and the technical aspects of our data and data infrastructure. • We highlight the importance of collaboration between organizations., The YOUth cohort study aims to be a trailblazer for open science. Being a large-scale, longitudinal cohort following children in their development from gestation until early adulthood, YOUth collects a vast amount of data through a variety of research techniques. Data are collected through multiple platforms, including facilities managed by Utrecht University and the University Medical Center Utrecht. In order to facilitate appropriate use of its data by research organizations and researchers, YOUth aims to produce high-quality, FAIR data while safeguarding the privacy of participants. This requires an extensive data infrastructure, set up by collaborative efforts of researchers, data managers, IT departments, and the Utrecht University Library. In the spirit of open science, YOUth will share its experience and expertise in setting up a high-quality research data infrastructure for sensitive cohort data. This paper describes the technical aspects of our data and data infrastructure, and the steps taken throughout the study to produce and safely store FAIR and high-quality data. Finally, we will reflect on the organizational aspects that are conducive to the success of setting up such an enterprise, and we consider the financial challenges posed by individual studies investing in sustainable science.

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).

A long-standing hypothesis is that humans have a bias for fixating the eye region in the faces of others. Most studies have tested this hypothesis with static images or videos of faces, yet recent studies suggest that the use of such "nonresponsive" stimuli might overlook an influence of social context. The present study addressed whether the bias for fixating the eye region in faces would persist in a situation that allowed for social interaction. In Experiment 1, we demonstrate a setup in which a duo could engage in social interaction while their eye movements were recorded. Here, we show that there is a bias for fixating the eye region of a partner that is physically present. Moreover, we report that the time 1 partner in a duo spends looking at the eyes is a good predictor of how long the other partner looks at the eyes. In Experiment 2, we investigate whether participants attune to the level of eye contact instigated by a partner by having a confederate pose as one of the partners. The confederate was subsequently instructed to either fixate the eyes of the observer or scan the entire face. Gaze behaviour of the confederate did not affect gaze behaviour of the observers. We conclude that there is a bias to fixate the eyes when partners can engage in social interaction. In addition, the amount of time spent looking at the eyes is duo-dependent, but not easily manipulated by instructing the gaze behaviour of 1 partner. (PsycINFO Database Record

Understanding the development of attention is key to understanding cognitive maturation. The gap-overlap task can be administered at all ages and is widely used to study the development of overt visual attention. However, studies using the gap-overlap task report different measures and little is known about the tasks’ psychometric properties, especially in infants. We tested the 1-week test–retest reliability of two frequently used gap-overlap measures of attentional disengagement in 10-month-old infants; the gap effect as measured by the difference between the gap and overlap condition and the gap effect as measured by the difference between the gap and baseline condition. Sixty-seven infants performed the gap-overlap task twice, of which 45 infants had sufficient data quality for further analyses. Test–retest reliability of the overlap-gap gap effect was higher (r = .50) than the baseline-gap gap effect (r = .29). Moreover, the shared variance between overlap and baseline saccadic reaction times was moderate to high across sessions. In light of these results and the methodological challenges and limitations of infant research, we consider the overlap-gap gap effect to be a good measure to study the development of attentional disengagement in infants and suggest the exclusion of the baseline condition in future studies.

Video stream: https://vimeo.com/357473408 Wearable mobile eye trackers have great potential as they allow the measurement of eye movements during daily activities such as driving, navigating the world and doing groceries. Although mobile eye trackers have been around for some time, developing and operating these eye trackers was generally a highly technical affair. As such, mobile eye-tracking research was not feasible for most labs. Nowadays, many mobile eye trackers are available from eye-tracking manufacturers (e.g. Tobii, Pupil labs, SMI, Ergoneers) and various implementations in virtual/augmented reality have recently been released.The wide availability has caused the number of publications using a mobile eye tracker to increase quickly. Mobile eye tracking is now applied in vision science, educational science, developmental psychology, marketing research (using virtual and real supermarkets), clinical psychology, usability, architecture, medicine, and more. Yet, transitioning from lab-based studies where eye trackers are fixed to the world to studies where eye trackers are fixed to the head presents researchers with a number of problems. These problems range from the conceptual frameworks used in world-fixed and head-fixed eye tracking and how they relate to each other, to the lack of data quality comparisons and field tests of the different mobile eye trackers and how the gaze signal can be classified or mapped to the visual stimulus. Such problems need to be addressed in order to understand how world-fixed and head-fixed eye-tracking research can be compared and to understand the full potential and limits of what mobile eye-tracking can deliver. In this symposium, we bring together presenting researchers from five different institutions (Lund University, Utrecht University, Clemson University, Birkbeck University of London and Rochester Institute of Technology) addressing problems and innovative solutions across the entire breadth of mobile eye-tracking research. Hooge, presenting Hessels et al. paper, focus on the definitions of fixations and saccades held by researchers in the eyemovement field and argue how they need to be clarified in order to allow comparisons between world-fixed and head-fixed eye-tracking research. - Diaz et al. introduce machine-learning techniques for classifying the gaze signal in mobile eye-tracking contexts where head and body are unrestrained. Niehorster et al. compare data quality of mobile eye trackers during natural behavior and discuss the application range of these eye trackers. Duchowski et al. introduce a method for automatically mapping gaze to faces using computer vision techniques. Pelz et al. employ state-of-the-art techniques to map fixations to objects of interest in the scene video and align grasp and eye-movement data in the same reference frame to investigate the guidance of eye movements during manual interaction.

The goal of this dissertation was to explore two possible early markers of Autism Spectrum Disorder (ASD): visual search superiority, and gaze behavior during face perception. These possible markers were explored as they pertain to both the social deficits in ASD (gaze during face perception) and visual peculiarities (visual search superiority), thereby tackling both diagnostic criteria for ASD. Moreover, visual search superiority and gaze during face perception have been widely studied with older children and adults with ASD. The main reasons for investigating early markers of ASD is to get a better understanding of the atypicalities in ASD as they emerge during development, and to enable earlier diagnosis and intervention. Although exploring possible early markers of ASD was the main focus at the outset of the research conducted in this dissertation, it quickly became clear that the available methodology was critically lacking. Both early markers for ASD described above are dependent on eye-tracking technology. However, as infants cannot be instructed and are difficult to restrict in movement, adult eye-tracking methodology with regard to experimental setup and data processing might not suffice for infant participants. Methodological innovations were introduced that allow a better argumentation for the choice of eye tracker, achieving high data quality, and eye-tracking data analysis in infant research. These innovations are crucial in order to push the developmental eye-tracking field forward. Investigating early markers for ASD not only depends on adequate methodology, but also on knowledge of typical development. With respect to the first of the possible early markers, visual search superiority, relatively little knowledge on typical development of visual search behavior was available. Saccadic search behavior in typically-developing infants was investigated: Infants searched for discrepant items in the absence of instructions, and saccadic search behavior was similar to that observed in adults. These findings serve as a benchmark for the identification of search patterns of infants at-risk for ASD. The conclusions drawn from studies investigating the second possible early marker for ASD, gaze behavior during face perception, have been highly inconsistent. Therefore, a novel method for investigating gaze behavior during face perception was developed. A setup was developed through which people could see and hear each other (akin to a Skype call), while their eye movement were being recorded. First, gaze behavior to faces in this interaction setup revealed important corroborations of research using non-responsive stimuli (e.g. pictures). Second, gaze behavior in interaction revealed intriguing links to ASD traits. In conclusion, the present dissertation demonstrates important methodological advances that are crucial in order to grasp typical and atypical gaze behavior both early in development and in adults. Moreover, a novel setup was introduced for the investigation of gaze behavior during interaction, which has already revealed intriguing links between gaze behavior and traits of ASD. Our setup opens up entirely new avenues for the investigation of (a)typical gaze behavior in social interaction, and may help us grasp the core social deficits in ASD.

The marketing materials of remote eye-trackers suggest that data quality is invariant to the position and orientation of the participant as long as the eyes of the participant are within the eye-tracker's headbox, the area where tracking is possible. As such, remote eye-trackers are marketed as allowing the reliable recording of gaze from participant groups that cannot be restrained, such as infants, schoolchildren and patients with muscular or brain disorders. Practical experience and previous research, however, tells us that eye-tracking data quality, e.g. the accuracy of the recorded gaze position and the amount of data loss, deteriorates (compared to well-trained participants in chinrests) when the participant is unrestrained and assumes a non-optimal pose in front of the eye-tracker. How then can researchers working with unrestrained participants choose an eye-tracker? Here we investigated the performance of five popular remote eye-trackers from EyeTribe, SMI, SR Research, and Tobii in a series of tasks where participants took on non-optimal poses. We report that the tested systems varied in the amount of data loss and systematic offsets observed during our tasks. The EyeLink and EyeTribe in particular had large problems. Furthermore, the Tobii eye-trackers reported data for two eyes when only one eye was visible to the eye-tracker. This study provides practical insight into how popular remote eye-trackers perform when recording from unrestrained participants. It furthermore provides a testing method for evaluating whether a tracker is suitable for studying a certain target population, and that manufacturers can use during the development of new eye-trackers.

In the manuscript, we write that saccadic reaction time was determined as the time between the offset of the last fixation on the central stimulus and the onset of the peripheral stimulus (the target).

A problem in eyetracking research is choosing areas of interest (AOIs): Researchers in the same field often use widely varying AOIs for similar stimuli, making cross-study comparisons difficult or even impossible. Subjective choices while choosing AOIs cause differences in AOI shape, size, and location. On the other hand, not many guidelines for constructing AOIs, or comparisons between AOI-production methods, are available. In the present study, we addressed this gap by comparing AOI-production methods in face stimuli, using data collected with infants and adults (with autism spectrum disorder [ASD] and matched controls). Specifically, we report that the attention-attracting and attention-maintaining capacities of AOIs differ between AOI-production methods, and that this matters for statistical comparisons in one of three groups investigated (the ASD group). In addition, we investigated the relation between AOI size and an AOI's attention-attracting and attention-maintaining capacities, as well as the consequences for statistical analyses, and report that adopting large AOIs solves the problem of statistical differences between the AOI methods. Finally, we tested AOI-production methods for their robustness to noise, and report that large AOIs-using the Voronoi tessellation method or the limited-radius Voronoi tessellation method with large radii-are most robust to noise. We conclude that large AOIs are a noise-robust solution in face stimuli and, when implemented using the Voronoi method, are the most objective of the researcher-defined AOIs. Adopting Voronoi AOIs in face-scanning research should allow better between-group and cross-study comparisons.

Eye-tracking research in infants and older children has gained a lot of momentum over the last decades. Although eye-tracking research in these participant groups has become easier with the advance of the remote eye-tracker, this often comes at the cost of poorer data quality than in research with well-trained adults (Hessels, Andersson, Hooge, Nystrom, & Kemner Infancy, 20, 601-633, 2015; Wass, Forssman, & Leppanen Infancy, 19, 427-460, 2014). Current fixation detection algorithms are not built for data from infants and young children. As a result, some researchers have even turned to hand correction of fixation detections (Saez de Urabain, Johnson, & Smith Behavior Research Methods, 47, 53-72, 2015). Here we introduce a fixation detection algorithm-identification by two-means clustering (I2MC)-built specifically for data across a wide range of noise levels and when periods of data loss may occur. We evaluated the I2MC algorithm against seven state-of-the-art event detection algorithms, and report that the I2MC algorithm's output is the most robust to high noise and data loss levels. The algorithm is automatic, works offline, and is suitable for eye-tracking data recorded with remote or tower-mounted eye-trackers using static stimuli. In addition to application of the I2MC algorithm in eye-tracking research with infants, school children, and certain patient groups, the I2MC algorithm also may be useful when the noise and data loss levels are markedly different between trials, participants, or time points (e.g., longitudinal research).

Contains fulltext : 127064.pdf (Publisher’s version ) (Closed access) Superiority in visual search for individuals diagnosed with autism spectrum disorder (ASD) is a well-reported finding. We administered two visual search tasks to individuals with ASD and matched controls. One showed no difference between the groups, and one did show the expected superior performance for individuals with ASD. These results offer an explanation, formulated in terms of load theory. We suggest that there is a limit to the superiority in visual search for individuals with ASD, related to the perceptual load of the stimuli. When perceptual load becomes so high that no additional task-(ir)relevant information can be processed, performance will be based on single stimulus identification, in which no differences between individuals with ASD and controls have been demonstrated. 01 juli 2013 9 p.

When each of our two eyes is presented with a dissimilar image, the intriguing phenomenon of binocular rivalry occurs: Perception will start alternating between the images. Since Wheatstone’s (1838) invention of the stereoscope, which initiated the scientific study of this fascinating phenomenon, it has been debated whether binocular rivalry is subject to attentional control1 (for a review, see Paffen & Alais, 2011). In recent years, evidence has converged toward the view that attentional control over which of the images is dominant in perception is limited but possible (Chong, Tadin, & Blake, 2005; Lack, 1979; Meng & Tong, 2004; van Ee, van Dam, & Brouwer, 2005). What is more, it has become evident that object-based attention influences which of the two images is dominant first (Chong & Blake, 2006; Mitchell, Stoner, & Reynolds, 2004), while spatial attention modulates the temporal dynamics of the alternations (Ooi & He, 1999; Paffen & Van der Stigchel, 2010). Moreover, alternations in perception occur more frequently when more attentional resources are available for reporting them (Paffen, Alais, & Verstraten, 2006). In contrast to the question of whether and how attention affects binocular rivalry, our aim was to investigate whether binocular rivalry is capable of attracting attention. Previous studies concerned with this issue have answered this question by investigating the degree to which interocular conflict (i.e., the situation leading to binocular rivalry) attracts attention during visual search (Paffen, Hooge, Benjamins, & Hogendoorn, 2011; Wolfe & Franzel, 1988). The results of the previous studies have been inconclusive. On the one hand, Wolfe and Franzel showed that search for interocular conflict was far from efficient: A rival target did not pop out when searching for it. On the other hand, Paffen et al. (2011) recently showed that participants searching for interocular conflict can approach efficient search behavior. Although the search in that study might not warrant the claim that interocular conflict pops out (search slopes were around 15 ms/item), the result is suggestive of the fact that binocular rivalry can attract attention. The present study is motivated by the question of whether interocular conflict is able to attract attention in a situation in which observers do not explicitly know what they are looking for in stimuli depicting natural and man-made scenes. To investigate the attention-attracting potency of interocular conflict, we employed a change blindness paradigm (Rensink, O’Regan, & Clark, 1997; Simons & Levin, 1997) in which two scenes are presented sequentially with a blank screen in-between. The observer is required to detect the change from one view to the next. These scenes are presented continuously until the change is detected. Previous studies have shown that observers are generally quite poor in detecting such a change unless visual attention is allocated to the location of the change (Cavanaugh & Wurtz, 2004; Scholl, 2000). From this finding, it can be inferred that an increase in performance on change detection is related to a shift of attention to the location of the change. This also predicts that change blindness will be attenuated when the changed location contains an attention-grabbing feature. In the present study, participants had to detect a change that could be (1) binocular, in which the same change occurred in a small region of two identical images presented to both eyes; (2) monocular, in which the change occurred in a small region of only one of the images (leading to interocular conflict); or (3) transparent, in which there was a transparent overlap of the changed and unchanged regions for each eye (see Fig. 1). The latter condition was included to assess whether superior change detection in the monocular condition could be due to normal fusion of both images, and not to interocular conflict. If detection of monocular changes is faster than detection of transparent changes, interocular conflict and not binocular fusion is the driving force underlying superior monocular change detection. We thus reasoned that if interocular conflict attracts attention, monocular changes (inducing interocular conflict) would be detected faster than both binocular and transparent changes. Fig. 1 Stimuli. Observers detected changes as quickly and accurately as possible in two images presented in alternation. The image on the left is an example of the images, presented in two frames to the left and the right eyes. In one of the two frames, a change ...

Erratum to: Atten Percept Psychophys DOI 10.3758/s13414-011-0256-x The abstract that appears below was inadvertently left out of the original article. Abstract During binocular rivalry, perception alternates between dissimilar images presented dichoptically. Since its discovery, researchers have debated whether the phenomenon is subject to attentional control. While it is now clear that attentional control over binocular rivalry is possible, the opposite is less evident: Is interocular conflict (i.e., the situation leading to binocular rivalry) able to attract attention? In order to answer this question, we used a change blindness paradigm in which observers looked for salient changes in two alternating frames depicting natural scenes. Each frame contained two images: one for the left and one for the right eye. Changes occurring in a single image (monocular) were detected faster than those occurring in both images (binocular). In addition, monocular change detection was also faster than detection in fused versions of the changed and unchanged regions. These results show that interocular conflict is capable of attracting attention, since it guides visual attention toward salient changes that otherwise would remain unnoticed for longer. The results of a second experiment indicated that interocular conflict attracts attention during the first phase of presentation, a phase during which the stimulus is abnormally fused.