Gaze Dispersion Research Articles

Deep learning–based eye tracking system to detect distracted driving

To investigate drivers’ gaze behavior and the characteristics of their gaze positions while driving, a natural driving behavior test method was employed alongside a non-contact eye-tracking device to conduct an in-vehicle experiment for collecting gaze data. Initially, we utilized the traditional approach to delineate the area of interest, analyzing variations in pupil diameter, gaze positions, and the duration spent in each area throughout the driving task, thereby compiling statistics on drivers’ gaze patterns. Subsequently, harnessing the You Only Look Once version 5 architecture, we can precisely identify the position of vehicles and obstacles from the captured images. Enhancements to the network model—including streamlining and integrating an attention mechanism—have significantly refined target detection accuracy. In the final analysis, by correlating drivers’ gaze data with the positional information of upcoming obstacles, we can accurately assess where drivers are looking. This fusion of data allows for a more nuanced observation of gaze dispersion and position within a one-second timeframe, providing valuable insights into drivers’ attention distribution and driving behaviors.

Pupil dilation reflects effortful action invigoration in overcoming aversive Pavlovian biases

“Pavlovian” or “motivational” biases describe the phenomenon that the valence of prospective outcomes modulates action invigoration: Reward prospect invigorates action, whereas punishment prospect suppresses it. The adaptive role of these biases in decision-making is still unclear. One idea is that they constitute a fast-and-frugal decision strategy in situations characterized by high arousal, e.g., in presence of a predator, which demand a quick response. In this pre-registered study (N = 35), we tested whether such a situation—induced via subliminally presented angry versus neutral faces—leads to increased reliance on Pavlovian biases. We measured trial-by-trial arousal by tracking pupil diameter while participants performed an orthogonalized Motivational Go/NoGo Task. Pavlovian biases were present in responses, reaction times, and even gaze, with lower gaze dispersion under aversive cues reflecting “freezing of gaze.” The subliminally presented faces did not affect responses, reaction times, or pupil diameter, suggesting that the arousal manipulation was ineffective. However, pupil dilations reflected facets of bias suppression, specifically the physical (but not cognitive) effort needed to overcome aversive inhibition: Particularly strong and sustained dilations occurred when participants managed to perform Go responses to aversive cues. Conversely, no such dilations occurred when they managed to inhibit responses to Win cues. These results suggest that pupil diameter does not reflect response conflict per se nor the inhibition of prepotent responses, but specifically effortful action invigoration as needed to overcome aversive inhibition. We discuss our results in the context of the “value of work” theory of striatal dopamine.

Pupil Size and Eye Movements Differently Index Effort in Both Younger and Older Adults.

The assessment of mental effort is increasingly relevant in neurocognitive and life span domains. Pupillometry, the measure of the pupil size, is often used to assess effort but has disadvantages. Analysis of eye movements may provide an alternative, but research has been limited to easy and difficult task demands in younger adults. An effort measure must be sensitive to the whole effort profile, including "giving up" effort investment, and capture effort in different age groups. The current study comprised three experiments in which younger (n = 66) and older (n = 44) adults listened to speech masked by background babble at different signal-to-noise ratios associated with easy, difficult, and impossible speech comprehension. We expected individuals to invest little effort for easy and impossible speech (giving up) but to exert effort for difficult speech. Indeed, pupil size was largest for difficult but lower for easy and impossible speech. In contrast, gaze dispersion decreased with increasing speech masking in both age groups. Critically, gaze dispersion during difficult speech returned to levels similar to easy speech after sentence offset, when acoustic stimulation was similar across conditions, whereas gaze dispersion during impossible speech continued to be reduced. These findings show that a reduction in eye movements is not a byproduct of acoustic factors, but instead suggest that neurocognitive processes, different from arousal-related systems regulating the pupil size, drive reduced eye movements during high task demands. The current data thus show that effort in one sensory domain (audition) differentially impacts distinct functional properties in another sensory domain (vision).

Can I see it in the eyes? An investigation of freezing-like motion patterns in response to avoidable threat.

Freezing is one of the most extensively studied defensive behaviors in rodents. Both reduced body and gaze movements during anticipation of threat also occur in humans and have been discussed as translational indicators of freezing but their relationship remains unclear. We thus set out to elucidate body and eye movements and concomitant autonomic dynamics in anticipation of avoidable threat. Specifically, 50 participants viewed naturalistic pictures that were preceded by a colored fixation cross, signaling them whether to expect an inevitable (shock), no (safety), or a potential shock (flight) that could be avoided by a quick button press. Body sway, eye movements, the heart rate and skin conductance were recorded. We replicated previously described reductions in body sway, gaze dispersion, and the heart rate, and a skin conductance increase in flight trials. Stronger reductions in gaze but not in body sway predicted faster motor reactions on a trial-wise basis, highlighting their functional role in action preparation. We failed to find a trait-like relationship between body and gaze movements across participants, but their temporal profiles were positively related within individuals, suggesting that both metrics partly reflect the same construct. However, future research is desirable to assess these response patterns in naturalistic environments. A more ethological examination of different movement dynamics upon threat would not only warrant better comparability between rodent and human research but also help determine whether and how eye-tracking could be implemented as a proxy for fear-related movements in restricted brain imaging environments.

Fear lies in the eyes of the beholder-Robust evidence for reduced gaze dispersion upon avoidable threat.

A rapid detection and processing of relevant information in our environment is crucial for survival. The human eyes are drawn to social or threatening stimuli as they may carry essential information on how to behave appropriately in a given context. Recent studies further showed a centralization of gaze that reminded of freezing behaviors in rodents. Probably constituting a component of an adaptive defense mode, centralized eye movements predicted the speed of motor actions. Here we conducted two experiments to examine if and how these presumably survival-relevant gaze patterns interact. Subjects viewed images including social, that is, faces (Experiment 1, N = 50) or threatening stimuli, that is, snakes or spiders (Experiment 2, N = 50) while awaiting an inevitable (shock), no (safety), or an avoidable shock (flight) they could escape from by a fast button press. The social and threatening cues within the scenes differed in their distance from the image center and we acquired eye-tracking and autonomic physiological data. Although we observed an initial orienting toward social and threatening stimulus aspects, this exploration pattern vanished towards the end of flight trials when a pronounced centralization of gaze emerged. Replicating previous findings, the amount of this center bias predicted the speed of motor reactions, and we observed a concurrent activation of the sympathetic and parasympathetic nervous system. Taken together, the exploration of potentially relevant cues seems to be part of a reflexive-orienting response regardless of contextual valence. However, centralization of gaze may be a threat-specific action-preparatory response that occurs across a wide range of stimulus contexts.

Eye movements decrease during effortful speech listening.

Hearing impairment affects many older adults but is often diagnosed decades after speech comprehension in noisy situations has become effortful. Accurate assessment of listening effort may thus help diagnose hearing impairment earlier. However, pupillometry - the most used approach to assess listening effort - has limitations that hinder its use in practice. The current study explores a novel way to assess listening effort through eye movements. Building on cognitive and neurophysiological work, we examine the hypothesis that eye movements decrease when speech listening becomes challenging. In three experiments with human participants from both sexes, we demonstrate, consistent with this hypothesis, that fixation duration increases and spatial gaze dispersion decreases with increasing speech masking. Eye movements decreased during effortful speech listening for different visual scenes (free viewing; object tracking) and speech materials (simple sentences; naturalistic stories). In contrast, pupillometry was less sensitive to speech masking during story listening, suggesting pupillometric measures may not be as effective for the assessments of listening effort in naturalistic speech-listening paradigms. Our results reveal a critical link between eye movements and cognitive load, suggesting that neural activity in the brain regions that support the regulation of eye movements, such as frontal eye field and superior colliculus, are modulated when listening is effortful.Significance statementAssessment of listening effort is critical for early diagnosis of age-related hearing loss. Pupillometry is most used but has several disadvantages. The current study explores a novel way to assess listening effort through eye movements. We examine the hypothesis that eye movements decrease when speech listening becomes effortful. We demonstrate, consistent with this hypothesis, that fixation duration increases and gaze dispersion decreases with increasing speech masking. Eye movements decreased during effortful speech listening for different visual scenes (free viewing; object tracking) and speech materials (sentences; naturalistic stories). Our results reveal a critical link between eye movements and cognitive load, suggesting that neural activity in brain regions that support the regulation of eye movements are modulated when listening is effortful.

The effects of task difficulty on gaze behaviour during landing with visual flight rules in low-time pilots.

Eye movements have been used to examine the cognitive function of pilots and understand how information processing abilities impact performance. Traditional and advanced measures of gaze behaviour effectively reflect changes in cognitive load, situational awareness, and expert-novice differences. However, the extent to which gaze behaviour changes during the early stages of skill development has yet to be addressed. The current study investigated the impact of task difficulty on gaze behaviour in low-time pilots (N=18) while they completed simulated landing scenarios. An increase in task difficulty resulted in longer fixation of the runway, and a reduction in the stationary gaze entropy (gaze dispersion) and gaze transition entropy (sequence complexity). These findings suggest that pilots' gaze became less complex and more focused on fewer areas of interest when task difficulty increased. Additionally, a novel approach to identify and track instances when pilots restrict their attention outside the cockpit (i.e., gaze tunneling) was explored and shown to be sensitive to changes in task difficulty. Altogether, the gaze-related metrics used in the present study provide valuable information for assessing pilots gaze behaviour and help further understand how gaze contributes to better performance in low-time pilots.

Bears in our midst: Familiarity with Level 2 driving automation and attending to surprise on-road events

This study presents an on-road paradigm to measure the effect of Level 2 (L2) system familiarity on attention strategies to salient, but non-hazardous, driving-related events when using the driving automation. A vehicle with an oversized pink teddy bear on the back overtook participants three times while they drove a 2019 Mercedes-Benz C300 equipped with a L2 system for 1 h. This L2 system requires drivers to keep their hands on the wheel while activated. The L2 system was turned on or off, depending on the assigned condition, and participants varied in their familiarity with L2 systems. Cameras recorded participant eye glance behavior. After the drive, participants were asked to recall the bear and the number of times their mind had wandered from the driving task during the drive. Results show that the driving automation support gave only participants familiar with L2 systems an advantage for greater bear recall. Unfamiliar participants were at a relative disadvantage when assisted by the L2 system, with generally poorer bear recall than unfamiliar participants who drove with the system off. Better bear recall corresponded with wider on-road gaze dispersion and more instances of mind wandering. Our findings support the effectiveness of this paradigm to measure driver attention when using a L2 system under real-world conditions and highlight the need to consider the role of driving automation familiarity in future research.

Classification of Driver Cognitive Load: Exploring the Benefits of Fusing Eye-Tracking and Physiological Measures

In-vehicle infotainment systems can increase cognitive load and impair driving performance. These effects can be alleviated through interfaces that can assess cognitive load and adapt accordingly. Eye-tracking and physiological measures that are sensitive to cognitive load, such as pupil diameter, gaze dispersion, heart rate (HR), and galvanic skin response (GSR), can enable cognitive load estimation. The advancement in cost-effective and nonintrusive sensors in wearable devices provides an opportunity to enhance driver state detection by fusing eye-tracking and physiological measures. As a preliminary investigation of the added benefits of utilizing physiological data along with eye-tracking data in driver cognitive load detection, this paper explores the performance of several machine learning models in classifying three levels of cognitive load imposed on 33 drivers in a driving simulator study: no external load, lower difficulty 1-back task, and higher difficulty 2-back task. We built five machine learning models, including k-nearest neighbor, support vector machine, feedforward neural network, recurrent neural network, and random forest (RF) on (1) eye-tracking data only, (2) HR and GSR, (3) eye-tracking and HR, (4) eye-tracking and GSR, and (5) eye-tracking, HR, and GSR. Although physiological data provided 1%–15% lower classification accuracies compared with eye-tracking data, adding physiological data to eye-tracking data increased model accuracies, with an RF classifier achieving 97.8% accuracy. GSR led to a larger boost in accuracy (29.3%) over HR (17.9%), with the combination of the two factors boosting accuracy by 34.5%. Overall, utilizing both physiological and eye-tracking measures shows promise for driver state detection applications.

Change Blindness in Adolescents With Attention-Deficit/Hyperactivity Disorder: Use of Eye-Tracking.

ObjectiveThis study investigated change detection of central or marginal interest in images using a change-blindness paradigm with eye tracking.MethodEighty-four drug-naïve adolescents [44 with attention-deficit/hyperactivity disorder (ADHD)/40 controls with typical development] searched for a change in 36 pairs of original and modified images, with an item of central or marginal interest present or absent, presented in rapid alternation. Collected data were detection rate, response time, and gaze fixation duration, latency, and dispersion data.ResultsBoth groups' change-detection times were similar, with no speed–accuracy trade-off. No between-group differences were found in time to first fixation, fixation duration, or scan paths. Both groups performed better for items of central level of interest. The ADHD group demonstrated greater fixation dispersion in scan paths for central- and marginal-interest items.ConclusionResults suggest the greater gaze dispersion may lead to greater fatigue in tasks that require longer attention duration.

The Compatibility between the Takeover Process in Conditional Automated Driving and the Current Geometric Design of the Deceleration Lane in Highway

In recent years, the takeover process of conditional automated driving has attached a great deal of attention. However, most of the existing research has focused on the effects of human-machine interactions or driver-related features (e.g., non-driving-related tasks), while there is little knowledge about the compatibility between the takeover process and existing road geometric design. As there is a high possibility that drivers must take over the vehicle before they diverge from the mainline of the highway, this explanatory study aimed to examine the compatibility between the takeover process and the current deceleration lane geometric design. The distribution range of existing deceleration lanes’ lengths were obtained through a geo-based survey. Nine scenarios were recreated in the driving simulator which were designed with various deceleration lane lengths and driving modes (different takeover time budgets and manual driving as the baseline group). A total of 31 participants were recruited to take part in the experiment, their gaze behaviors were recorded simultaneously. Results showed that, compared with manual driving, both drivers’ horizontal and vertical gaze dispersion increased, while drivers adopted higher deceleration in the mainline and merged into the deceleration lane later under takeover conditions. Moreover, a longer deceleration lane could benefit vehicle control. However, its marginal effect was reduced with the increase of deceleration lane length. These findings can help automated vehicle manufacturers design dedicated takeover schemes for different deceleration lane lengths.

Displays for Productive Non-Driving Related Tasks: Visual Behavior and Its Impact in Conditionally Automated Driving

(1) Background: Primary driving tasks are increasingly being handled by vehicle automation so that support for non-driving related tasks (NDRTs) is becoming more and more important. In SAE L3 automation, vehicles can require the driver-passenger to take over driving controls, though. Interfaces for NDRTs must therefore guarantee safe operation and should also support productive work. (2) Method: We conducted a within-subjects driving simulator study (N=53) comparing Heads-Up Displays (HUDs) and Auditory Speech Displays (ASDs) for productive NDRT engagement. In this article, we assess the NDRT displays’ effectiveness by evaluating eye-tracking measures and setting them into relation to workload measures, self-ratings, and NDRT/take-over performance. (3) Results: Our data highlights substantially higher gaze dispersion but more extensive glances on the road center in the auditory condition than the HUD condition during automated driving. We further observed potentially safety-critical glance deviations from the road during take-overs after a HUD was used. These differences are reflected in self-ratings, workload indicators and take-over reaction times, but not in driving performance. (4) Conclusion: NDRT interfaces can influence visual attention even beyond their usage during automated driving. In particular, the HUD has resulted in safety-critical glances during manual driving after take-overs. We found this impacted workload and productivity but not driving performance.

Visual scanning strategies in the cockpit are modulated by pilots' expertise: A flight simulator study.

During a flight, pilots must rigorously monitor their flight instruments since it is one of the critical activities that contribute to update their situation awareness. The monitoring is cognitively demanding, but is necessary for timely intervention in the event of a parameter deviation. Many studies have shown that a large part of commercial aviation accidents involved poor cockpit monitoring from the crew. Research in eye-tracking has developed numerous metrics to examine visual strategies in fields such as art viewing, sports, chess, reading, aviation, and space. In this article, we propose to use both basic and advanced eye metrics to study visual information acquisition, gaze dispersion, and gaze patterning among novices and pilots. The experiment involved a group of sixteen certified professional pilots and a group of sixteen novice during a manual landing task scenario performed in a flight simulator. The two groups landed three times with different levels of difficulty (manipulated via a double task paradigm). Compared to novices, professional pilots had a higher perceptual efficiency (more numerous and shorter dwells), a better distribution of attention, an ambient mode of visual attention, and more complex and elaborate visual scanning patterns. We classified pilot's profiles (novices-experts) by machine learning based on Cosine KNN (K-Nearest Neighbors) using transition matrices. Several eye metrics were also sensitive to the landing difficulty. Our results can benefit the aviation domain by helping to assess the monitoring performance of the crews, improve initial and recurrent training and ultimately reduce incidents, and accidents due to human error.

The Effects of Smartphone Spectatorship on Attention, Arousal, Engagement, and Comprehension.

The popularity of watching movies and videos on handheld devices is rising, yet little attention has been paid to its impact on viewer behaviour. Smartphone spectatorship is characterized by the small handheld screen as well as the viewing environment where various unrelated stimuli can occur, providing possible distractions from viewing. Previous research suggests that screen size, handheld control, and external stimuli can affect viewing experience; however, no prior studies have combined these factors or applied them for the specific case of smartphones. In the present study, we compared smartphone and large-screen viewing of feature films in the presence and absence of external distractors. Using a combination of eye tracking, electrodermal activity measures, self-reports, and recollection accuracy tests, we measured smartphone-accustomed viewers’ attention, arousal, engagement, and comprehension. The results revealed the impact of viewing conditions on eye movements, gaze dispersion, electrodermal activity, self-reports of engagement, as well as comprehension. These findings show that smartphone viewing is more effective when there are no distractions, and smartphone viewers are more likely to be affected by external stimuli. In addition, watching large stationary screens in designated viewing environments increases engagement with a movie.

Monitoring army drivers’ workload during off-road missions: An experimental controlled field study

We studied the validity of electroencephalographic (EEG) and gaze indices to discriminate task load variations in professional Army drivers while performing real training exercises with a Light Multirole Vehicle in non-combat scenarios. Twenty-two non-commissioned officers from the Spanish Army carried out two sets of standardized driving exercises, with low and high maneuver complexity (off-road navigation vs. slalom on dirt road). They performed both exercises with and without a secondary auditory-vocal digit span forward task. Throughout the exercises, we simultaneously recorded drivers’ EEG and gaze activity. We also assessed perceived task load and performance. We found that drivers’ neural activation changed with exercise complexity. Particularly, the EEG signal ratio between Frontal-Theta and Parietal-Alpha power spectra, known as the EEG workload index, was higher during the most complex exercise. This index was not affected by dual tasking. Furthermore, the level of uncertainty of the gaze position, as measured by gaze entropy, increased during the most complex exercise. Dual tasking did increase drivers’ gaze dispersion, but only when performing the less complex exercise. Perceived task load was sensitive to maneuver complexity and dual tasking. Performance indices did not vary across exercises. Our results support that physiological monitoring in real training, even in extreme environments, is feasible and can give objective measurements of changes in task load over time in a minimally invasive fashion.

Psychophysiological responses to takeover requests in conditionally automated driving

In SAE Level 3 automated driving, taking over control from automation raises significant safety concerns because drivers out of the vehicle control loop have difficulty negotiating takeover transitions. Existing studies on takeover transitions have focused on drivers’ behavioral responses to takeover requests (TORs). As a complement, this exploratory study aimed to examine drivers’ psychophysiological responses to TORs as a result of varying non-driving-related tasks (NDRTs), traffic density and TOR lead time. A total number of 102 drivers were recruited and each of them experienced 8 takeover events in a high fidelity fixed-base driving simulator. Drivers’ gaze behaviors, heart rate (HR) activities, galvanic skin responses (GSRs), and facial expressions were recorded and analyzed during two stages. First, during the automated driving stage, we found that drivers had lower heart rate variability, narrower horizontal gaze dispersion, and shorter eyes-on-road time when they had a high level of cognitive load relative to a low level of cognitive load. Second, during the takeover transition stage, 4 s lead time led to inhibited blink numbers and larger maximum and mean GSR phasic activation compared to 7 s lead time, whilst heavy traffic density resulted in increased HR acceleration patterns than light traffic density. Our results showed that psychophysiological measures can indicate specific internal states of drivers, including their workload, emotions, attention, and situation awareness in a continuous, non-invasive and real-time manner. The findings provide additional support for the value of using psychophysiological measures in automated driving and for future applications in driver monitoring systems and adaptive alert systems.

The effect of motor control requirements on drivers’ eye-gaze pattern during automated driving

This driving simulator study compared drivers’ eye movements during a series of lane-changes, which required different levels of motor control for their execution. Participants completed 12 lane-changing manoeuvres in three drives, categorised by degree of manual engagement with the driving task: Fully Manual Drive, Manual Intervention Required, Fully Automated Drive (Manual drive, Partial automation, Full automation). For Partial automation, drivers resumed control from the automated system and changed lane manually. For Full automation, the automated system managed the lane change, but participants initiated the manoeuvre by pulling the indicator lever. Results were compared to the Manual drive condition, where drivers controlled the vehicle at all times. For each driving condition, lane changing was initiated by drivers, at their discretion, in response to a slow-moving lead vehicle, which entered their lane. Failure to change lane did not result in a collision. To understand how different motor control requirements affected driver visual attention, eye movements to the road centre, and drivers' vertical and horizontal gaze dispersion were compared during different stages of the lane change manoeuvre, for the three drives. Results showed that drivers' attention to the road centre was generally lower for drives with less motor control requirements, especially when they were not engaged in the lane change process. However, as drivers moved closer to the lead vehicle, and prepared to change lane, the pattern of eye movements to the road centre converged, regardless of whether drivers were responsible for the manual control of the lane change. While there were no significant differences in horizontal gaze dispersion between the three drives, vertical dispersion for the two levels of automation was quite different, with higher dispersion during Partial automation, which was due to a higher reliance on the HMI placed in the centre console.

Risk prediction model using eye movements during simulated driving with logistic regressions and neural networks

BackgroundMany studies have found that eye movement behavior provides a real-time index of mental activity. Risk management architectures embedded in autonomous vehicles fail to include human cognitive aspects. We set out to evaluate whether eye movements during a risk driving detection task are able to predict risk situations. MethodsThirty-two normally sighted subjects (15 female) saw 20 clips of recorded driving scenes while their gaze was tracked. They reported when they considered the car should brake, anticipating any hazard. We applied both a mixed-effect logistic regression model and feedforward neural networks between hazard reports and eye movement descriptors. ResultsAll subjects reported at least one major collision hazard in each video (average 3.5 reports).We found that hazard situations were predicted by larger saccades, more and longer fixations, fewer blinks, and a smaller gaze dispersion in both horizontal and vertical dimensions.Performance between models incorporating a different combination of descriptors was compared running a test equality of receiver operating characteristic areas. Feedforward neural networks outperformed logistic regressions in accuracies. The model including saccadic magnitude, fixation duration, dispersion in ×, and pupil returned the highest ROC area (0.73). ConclusionWe evaluated each eye movement descriptor successfully and created separate models that predicted hazard events with an average efficacy of 70% using both logistic regressions and feedforward neural networks.The use of driving simulators and hazard detection videos can be considered a reliable methodology to study risk prediction.

Novice and Expert Anesthesiologists' Eye-Tracking Metrics During Simulated Epidural Block: A Preliminary, Brief Observational Report.

IntroductionEye tracking is the process of measuring an individual’s eye movements to register their attentional behavior by using a device called an eye-tracker. Studies conducted using eye-tracking techniques have demonstrated a number of differences in eye movement parameters and patterns between experts and novices. The aim of this preliminary study was to evaluate if there are any differences in eye-tracking metrics between novice and expert anesthesiologists during the performance of an epidural block using an epidural simulator.MethodsSeven experts and seven novices who gave their consent to this preliminary study were asked to perform an epidural technique using an epidural simulator while wearing a pair of Tobii Pro glasses. Number of fixations, fixation duration, heat maps and scan-paths were examined by Tobii Pro Lab Software. Duration of the procedure was also recorded.ResultsThe observation of the attentional heat map and gaze plot showed different gaze dispersion between experts and novices. The mean total duration of fixations during needle insertion and advancement and catheter introduction was lower in experts than trainees (respectively, 0.18 vs 3.56 sec; P<0.05 and 0.73 vs 2.48 sec; P<0.05). The mean fixation count was greater in experts vs trainees (5 vs 2; P<0.05). The mean duration of the epidural procedure was 104.16 (41) (trainees) vs 65.3 (32.6) seconds (experts) (P<0.05). Expert anesthesiologists spent more time fixating a more specific target location (eg, the point of the epidural needle rather than the syringe’s barrel) whilst novices split their attention between tracking their tools and the target location.DiscussionEye tracking may have interesting implications for the creation of assessment programs, which distinguish skill level through the use of gaze behavior, and may be a promising tool for monitoring training progress towards the development of expertise.

Individual face- and house-related eye movement patterns distinctively activate FFA and PPA

We investigated if the fusiform face area (FFA) and the parahippocampal place area (PPA) contain a representation of fixation sequences that are typically used when looking at faces or houses. Here, we instructed observers to follow a dot presented on a uniform background. The dot’s movements represented gaze paths acquired separately from observers looking at face or house pictures. Even when gaze dispersion differences were controlled, face- and house-associated gaze patterns could be discriminated by fMRI multivariate pattern analysis in FFA and PPA, more so for the current observer’s own gazes than for another observer’s gaze. The discrimination of the observer’s own gaze patterns was not observed in early visual areas (V1 – V4) or superior parietal lobule and frontal eye fields. These findings indicate a link between perception and action—the complex gaze patterns that are used to explore faces and houses—in the FFA and PPA.