Oxytocin administration does not influence eye gaze of volunteers towards physicians nor their self-perceived bonding with physicians

The patient-physician relationship is a critical determinant for patient health outcomes. Verbal and non-verbal communication, such as eye gaze, are vital aspects of this bond. Neurobiological studies indicate that oxytocin may serve as a link between increased eye gaze and social bonding. Therefore, oxytocin signaling could serve as a key factor influencing eye gaze as well as the patient-physician relationship. We aimed to test the effects of oxytocin on gaze to the eyes of the physician and the patient-physician relationship by conducting a randomized placebo-controlled crossover trial in healthy volunteers with intranasally administered oxytocin (24IU). Eye gaze of sixty-eight male volunteers was studied using eye-tracking. Volunteers engaged in a simulated video call consultation with a physician who provided information about vaccination against the human papilloma virus. Relationship outcomes (including trust, satisfaction and perceived physician communication style) were measured using questionnaires and corrected for possible confounders (social anxiety and attachment orientation). Additional secondary outcome measures were recall of information and pupil diameter and exploratory outcomes were mood and anxiety. Oxytocin did not affect eye tracking parameters of volunteers’ gaze towards the eyes of the physician. Moreover, oxytocin did not affect parameters of bonding between volunteers and the physician, nor other secondary and exploratory outcomes. Bayesian hypothesis testing provided evidence for the absence of effects. These results contradict the notion that oxytocin affects eye gaze patterns or bonding.

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LO82: Exploring eye-tracking technology to assess competency in point-of-care ultrasound

CJEM ◽

10.1017/cem.2020.136 ◽

2020 ◽

Vol 22 (S1) ◽

pp. S37-S37

Author(s):

W. Lee ◽

J. Chenkin

Keyword(s):

Eye Tracking ◽

Visual Processing ◽

Average Duration ◽

Point Of Care ◽

Secondary Outcome ◽

Great Promise ◽

Point Of Care Ultrasound ◽

The Gaze ◽

Area Of Interest ◽

Gaze Patterns

Introduction: Assessment of point-of-care ultrasound (POCUS) competency has been reliant on practical, visual and written examinations performed 1-on-1 with an examiner. These tools attempt to assess competency through subjective ratings, checklists and multiple-choice questions that are labour intensive using surrogate measures. Eye-tracking has been used on a limited basis in various fields of medicine for training and assessment. This technology explores visual processing and holds great promise as a tool to monitor training progress towards the development of expertise. We hypothesize that eye-tracking may differentiate novices and experts as they progress to become competent in interpretation of POCUS images and provide an objective measure in assessment of competency. Methods: Medical students, residents and attending physicians working in an academic emergency department were recruited. Participants viewed a series of 16 ultrasound video clips in a POCUS protocol for Focused Assessment using Sonography in Trauma (FAST). The gaze pattern of the participants was recorded using a commercially available eye-tracking device. The primary outcome was the gaze parameters including total gaze time in the area of interest (AOI), average time to fixation on the AOI, number of fixations in the AOI and average duration of first fixation on the AOI. Secondary outcome was the accuracy on the interpretation of the FAST scan. Results: Four novices and eight experts completed this study. The total gaze time in the AOI (mean +/- SD) was 76.72 +/- 18.84s among experts vs 53.64 +/- 10.33s among novices (p = 0.048), average time to fixation on the AOI was 0.561 +/- 0.319s vs 1.048 +/- 0.280s (p = 0.027), number of fixations in the AOI was 158.9 +/- 29.0 vs 121.8 +/- 17.5 (p = 0.042) and average duration of first fixation was 0.444 +/- 0.119s vs 0.390 +/- 0.024s (p = 0.402). The accuracy of the answers was 79.7 +/- 14.1% vs 45.3 +/- 21.9% (p = 0.007). Conclusion: In this pilot study, eye tracking shows potential to differentiate between POCUS experts and novices by their gaze patterns. Gaze patterns captured by eye tracking may not necessarily translate to cognitive processing. However, it allows educators to visualise the thought processes of the learner by their gaze patterns and provide insight on how to guide them towards competency. Future studies are needed to further validate the metrics for competency in POCUS applications.

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Eye-Tracking the Emergence of Attentional Anchors in a Mathematics Learning Tablet Activity

Eye-Tracking Technology Applications in Educational Research - Advances in Educational Technologies and Instructional Design ◽

10.4018/978-1-5225-1005-5.ch009 ◽

2017 ◽

pp. 166-194 ◽

Cited By ~ 4

Author(s):

Shakila Shayan ◽

Dor Abrahamson ◽

Arthur Bakker ◽

Carolien A. C. G. Duijzer ◽

Marieke van der Schaaf

Keyword(s):

Eye Tracking ◽

Conceptual Development ◽

Eye Gaze ◽

Mathematics Learning ◽

School Students ◽

Clinical Interviews ◽

Reflective Abstraction ◽

Gaze Patterns ◽

Sensorimotor Interaction ◽

Embodiment Theory

Little is known about micro-processes by which sensorimotor interaction gives rise to conceptual development. Per embodiment theory, these micro-processes are mediated by dynamical attentional structures. Accordingly this study investigated eye-gaze behaviors during engagement in solving tablet-based bimanual manipulation tasks designed to foster proportional reasoning. Seventy-six elementary- and vocational-school students (9-15 yo) participated in individual task-based clinical interviews. Data gathered included action-logging, eye-tracking, and videography. Analyses revealed the emergence of stable eye-path gaze patterns contemporaneous with first enactments of effective manipulation and prior to verbal articulations of manipulation strategies. Characteristic gaze patterns included consistent or recurring attention to screen locations that bore non-salient stimuli or no stimuli at all yet bore invariant geometric relations to dynamical salient features. Arguably, this research validates empirically hypothetical constructs from constructivism, particularly reflective abstraction.

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Combined frequency-tagging EEG and eye-tracking measures provide no support for the “excess mouth/diminished eye attention” hypothesis in autism

Molecular Autism ◽

10.1186/s13229-020-00396-5 ◽

2020 ◽

Vol 11 (1) ◽

Author(s):

Sofie Vettori ◽

Stephanie Van der Donck ◽

Jannes Nys ◽

Pieter Moors ◽

Tim Van Wesemael ◽

...

Keyword(s):

Eye Tracking ◽

Clinical Symptoms ◽

Eye Gaze ◽

Autism Spectrum ◽

Covert Attention ◽

Neural Responses ◽

Lower Face ◽

Facial Region ◽

Gaze Patterns ◽

The Face

Abstract Background Scanning faces is important for social interactions. Difficulty with the social use of eye contact constitutes one of the clinical symptoms of autism spectrum disorder (ASD). It has been suggested that individuals with ASD look less at the eyes and more at the mouth than typically developing (TD) individuals, possibly due to gaze aversion or gaze indifference. However, eye-tracking evidence for this hypothesis is mixed. While gaze patterns convey information about overt orienting processes, it is unclear how this is manifested at the neural level and how relative covert attention to the eyes and mouth of faces might be affected in ASD. Methods We used frequency-tagging EEG in combination with eye tracking, while participants watched fast flickering faces for 1-min stimulation sequences. The upper and lower halves of the faces were presented at 6 Hz and 7.5 Hz or vice versa in different stimulation sequences, allowing to objectively disentangle the neural saliency of the eyes versus mouth region of a perceived face. We tested 21 boys with ASD (8–12 years old) and 21 TD control boys, matched for age and IQ. Results Both groups looked longer at the eyes than the mouth, without any group difference in relative fixation duration to these features. TD boys looked significantly more to the nose, while the ASD boys looked more outside the face. EEG neural saliency data partly followed this pattern: neural responses to the upper or lower face half were not different between groups, but in the TD group, neural responses to the lower face halves were larger than responses to the upper part. Face exploration dynamics showed that TD individuals mostly maintained fixations within the same facial region, whereas individuals with ASD switched more often between the face parts. Limitations Replication in large and independent samples may be needed to validate exploratory results. Conclusions Combined eye-tracking and frequency-tagged neural responses show no support for the excess mouth/diminished eye gaze hypothesis in ASD. The more exploratory face scanning style observed in ASD might be related to their increased feature-based face processing style.

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Look before you Authorize: Using Eye-Tracking to Enforce User Attention towards Application Permissions

Proceedings on Privacy Enhancing Technologies ◽

10.1515/popets-2017-0014 ◽

2017 ◽

Vol 2017 (2) ◽

pp. 23-37 ◽

Cited By ~ 7

Author(s):

Yousra Javed ◽

Mohamed Shehab

Keyword(s):

Eye Tracking ◽

User Study ◽

Eye Gaze ◽

Third Party ◽

Security And Privacy ◽

Control Group ◽

Eye Tracker ◽

Key Factor ◽

User Attention ◽

Gaze Fixations

Abstract Habituation is a key factor behind the lack of attention towards permission authorization dialogs during third party application installation. Various solutions have been proposed to combat the problem of achieving attention switch towards permissions. However, users continue to ignore these dialogs, and authorize dangerous permissions, which leads to security and privacy breaches. We leverage eye-tracking to approach this problem, and propose a mechanism for enforcing user attention towards application permissions before users are able to authorize them. We deactivate the dialog’s decision buttons initially, and use feedback from the eye-tracker to ensure that the user has looked at the permissions. After determining user attention, the buttons are activated. We implemented a prototype of our approach as a Chrome browser extension, and conducted a user study on Facebook’s application authorization dialogs. Using participants’ permission identification, eye-gaze fixations, and authorization decisions, we evaluate participants’ attention towards permissions. The participants who used our approach on authorization dialogs were able to identify the permissions better, compared to the rest of the participants, even after the habituation period. Their average number of eye-gaze fixations on the permission text was significantly higher than the other group participants. However, examining the rate in which participants denied a dangerous and unnecessary permission, the hypothesized increase from the control group to the treatment group was not statistically significant.

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Eye gaze patterns reflect how young fraction learners approach numerical comparisons

Journal of Numerical Cognition ◽

10.5964/jnc.v6i1.119 ◽

2020 ◽

Vol 6 (1) ◽

pp. 83-107

Author(s):

Alison T. Miller Singley ◽

Jeffrey Lynn Crawford ◽

Silvia A. Bunge

Keyword(s):

Academic Achievement ◽

Eye Movements ◽

Problem Solving ◽

Eye Tracking ◽

Conceptual Development ◽

Eye Gaze ◽

Proficiency Levels ◽

Gaze Patterns ◽

Different Levels ◽

Fraction Comparison

Learning fractions is notoriously difficult, yet critically important to mathematical and general academic achievement. Eye-tracking studies are beginning to characterize the strategies that adults use when comparing fractions, but we know relatively little about the strategies used by children. We used eye-tracking to analyze how novice children and mathematically-proficient adults approached a well-studied fraction comparison paradigm. Specifically, eye-tracking can provide insights into the nature of differences: whether they are quantitative—reflecting differences in efficiency—or qualitative—reflecting a fundamentally different approach. We found that children who had acquired the basic fraction rules made more eye movements than did either adults or less proficient children, suggesting a thorough but inefficient problem solving approach. Additionally, correct responses were associated with normative gaze patterns, regardless of age or proficiency levels. However, children paid more attention to irrelevant numerical relationships on conditions that were conceptually difficult. An exploratory analysis points to the possibility that children on the verge of making a conceptual leap attend to the relevant relationships even when they respond incorrectly. These findings indicate the potential of eye-tracking methodology to better characterize the behavior associated with different levels of fraction proficiency, as well as to provide insights for educators regarding how to best support novices at different levels of conceptual development.

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Assessing expertise using eye tracking in a Virtual Reality flight simulation

10.31234/osf.io/ue58a ◽

2022 ◽

Author(s):

David Harris ◽

Tom Arthur ◽

Toby de Burgh ◽

Mike Duxbury ◽

Ross Lockett-Kirk ◽

...

Keyword(s):

Virtual Reality ◽

Eye Movements ◽

Eye Tracking ◽

Real World ◽

Eye Gaze ◽

Cost Effective ◽

Flight Simulation ◽

Training Tool ◽

Gaze Patterns ◽

Scaling Analyses

Objective: The aim of this work was to examine the fidelity and validity of an aviation simulation using eye tracking. Background: Commercial head-mounted virtual reality (VR) systems offer a convenient and cost-effective alternative to existing aviation simulation (e.g., for refresher exercises). We performed pre-implementation testing of a novel aviation simulation, designed for head-mounted VR, to determine its fidelity and validity as a training device. Method: Eighteen airline pilots, with varying levels of flight experience, completed a sequence of training ‘flows’. Self-reported measures of presence and workload and users’ perceptions of fidelity were taken. Pilots’ eye movements and performance were recorded to determine whether more experienced pilots showed distinct performance and eye gaze profiles in the simulation, as they would in the real-world. Results: Real-world expertise correlated with eye gaze patterns characterised by fewer, but longer, fixations and a scan path that was more structured and less random. Multidimensional scaling analyses also indicated differential clustering of strategies in more versus less experienced pilots. Subjective ratings of performance, however, showed little relationship with real-world expertise or eye movements. Conclusion: We adopted an evidence-based approach to assessing the fidelity and validity of a VR flight training tool. Pilot reports indicated the simulation was realistic and potentially useful for training, while direct measurement of eye movements was useful for establishing construct validity and psychological fidelity of the simulation.

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Evaluating fMRI-Based Estimation of Eye Gaze During Naturalistic Viewing

Cerebral Cortex ◽

10.1093/cercor/bhz157 ◽

2019 ◽

Vol 30 (3) ◽

pp. 1171-1184 ◽

Cited By ~ 4

Author(s):

Jake Son ◽

Lei Ai ◽

Ryan Lim ◽

Ting Xu ◽

Stanley Colcombe ◽

...

Keyword(s):

Eye Tracking ◽

Eye Gaze ◽

Area Under The Curve ◽

Neural Correlates ◽

Brain Network ◽

Support Vector ◽

Angular Deviation ◽

Eye Fixations ◽

Gaze Patterns ◽

Primary Determinant

Abstract The collection of eye gaze information during functional magnetic resonance imaging (fMRI) is important for monitoring variations in attention and task compliance, particularly for naturalistic viewing paradigms (e.g., movies). However, the complexity and setup requirements of current in-scanner eye tracking solutions can preclude many researchers from accessing such information. Predictive eye estimation regression (PEER) is a previously developed support vector regression-based method for retrospectively estimating eye gaze from the fMRI signal in the eye’s orbit using a 1.5-min calibration scan. Here, we provide confirmatory validation of the PEER method’s ability to infer eye gaze on a TR-by-TR basis during movie viewing, using simultaneously acquired eye tracking data in five individuals (median angular deviation < 2°). Then, we examine variations in the predictive validity of PEER models across individuals in a subset of data (n = 448) from the Child Mind Institute Healthy Brain Network Biobank, identifying head motion as a primary determinant. Finally, we accurately classify which of the two movies is being watched based on the predicted eye gaze patterns (area under the curve = 0.90 ± 0.02) and map the neural correlates of eye movements derived from PEER. PEER is a freely available and easy-to-use tool for determining eye fixations during naturalistic viewing.

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Evaluating fMRI-Based Estimation of Eye Gaze during Naturalistic Viewing

10.1101/347765 ◽

2018 ◽

Cited By ~ 1

Author(s):

Jake Son ◽

Lei Ai ◽

Ryan Lim ◽

Ting Xu ◽

Stanley Colcombe ◽

...

Keyword(s):

Eye Tracking ◽

Eye Gaze ◽

Area Under The Curve ◽

Neural Correlates ◽

Brain Network ◽

Support Vector ◽

Angular Deviation ◽

Eye Fixations ◽

Gaze Patterns ◽

Primary Determinant

ABSTRACTThe collection of eye gaze information during functional magnetic resonance imaging (fMRI) is important for monitoring variations in attention and task compliance, particularly for naturalistic viewing paradigms (e.g., movies). However, the complexity and setup requirements of current in-scanner eye-tracking solutions can preclude many researchers from accessing such information. Predictive eye estimation regression (PEER) is a previously developed support vector regression-based method for retrospectively estimating eye gaze from the fMRI signal in the eye’s orbit using a 1.5-minute calibration scan. Here, we provide confirmatory validation of the PEER method’s ability to infer eye gaze on a TR-by-TR basis during movie viewing, using simultaneously acquired eye tracking data in five individuals (median angular deviation < 2°). Then, we examine variations in the predictive validity of PEER models across individuals in a subset of data (n=448) from the Child Mind Institute Healthy Brain Network Biobank, identifying head motion as a primary determinant. Finally, we accurately classify which of two movies is being watched based on the predicted eye gaze patterns (area under the curve = .90 ± .02) and map the neural correlates of eye movements derived from PEER. PEER is a freely available and easy-to-use tool for determining eye fixations during naturalistic viewing.

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