Eyes as windows to the soul: Gazing behavior is related to personality

The way we look at an image or a webpage can reveal personality traits

Personality is a central concept and a cross-domain explanatory factor in psychology to characterize and differentiate individuals. Surprisingly, among the many studies on oculomotor behavior, only a few have investigated how personality influences the exploration of a visual stimulus. Due to the limited number of existing studies, it is still uncertain if markers of personality in eye movements are always observable in eye movements across various exploration contexts. Here, introducing a novel concept of gaze-based signatures of personality, we used visual exploration metrics to detect personality signatures across various exploration contexts (visual search and free-viewing on images and webpages) in 91 participants. Personality data were collected as in the reference paper that validated the French version of the Big Five Inventory. Linear regression analyses demonstrated that while Extraversion and Openness to Experience did not correlate with any particular exploration metric, the other three traits-Conscientiousness, Agreeableness, and Neuroticism-correlated robustly with all exploration metrics in different visual exploration contexts. Our study provides evidence for the capture of the gaze-based signature of personality from very brief eye movement recordings.

Taking another look at intelligence and personality using an eye-tracking approach

Intelligence and personality are both key drivers of learning. This study extends prior research on intelligence and personality by adopting a behavioral-process-related eye-tracking approach. We tested 182 adults on fluid intelligence and the Big Five personality traits. Eye-tracking information (gaze patterns) was recorded while participants completed the intelligence test. Machine learning models showed that personality explained 3.18% of the variance in intelligence test scores, with Openness and, surprisingly, Agreeableness most meaningfully contributing to the prediction. Facet-level measures of personality explained a larger amount of variance (7.67%) in intelligence test scores than the trait-level measures, with the largest coefficients obtained for Ideas and Values (Openness) and Compliance and Trust (Agreeableness). Gaze patterns explained a substantial amount of variance in intelligence test performance (35.91%). Gaze patterns were unrelated to the Big Five personality traits, but some of the facets (especially Self-Consciousness from Neuroticism and Assertiveness from Extraversion) were related to gaze. Gaze patterns reflected the test-solving strategies described in the literature (constructive matching, response elimination) to some extent. A combined feature vector consisting of gaze-based predictions and personality traits explained 37.50% of the variance in intelligence test performance, with significant unique contributions from both personality and gaze patterns. A model that included personality facets and gaze explained 38.02% of the variance in intelligence test performance. Although behavioral data thus clearly outperformed "traditional" psychological measures (Big Five personality) in predicting intelligence test performance, our results also underscore the independent contributions of personality and gaze patterns in predicting intelligence test performance.

Individual differences in visual search: A systematic review of the link between visual search performance and traits or abilities

Visual search (VS) comprises a class of tasks that we typically perform several times during a day and requires intentionally scanning (with or without moving the eyes) the environment for a specific target (be it an object or a feature) among distractor stimuli. Experimental research in lab-based or real-world settings has offered insight into its underlying neurocognitive mechanisms from a nomothetic point of view. A lesser-known but rapidly growing body of quasi-experimental and correlational research has explored the link between individual differences and VS performance. This combines different research traditions and covers a wide range of individual differences in studies deploying a vast array of VS tasks. As such, it is a challenge to determine whether any associations highlighted in single studies are robust when considering the wider literature. However, clarifying such relationships systematically and comprehensively would help build more accurate models of VS, and it would highlight promising directions for future research. This systematic review provides an up to date and comprehensive synthesis of the existing literature investigating associations between common indices of performance in VS tasks and measures of individual differences mapped onto four categories of cognitive abilities (short-term working memory, fluid reasoning, visual processing and processing speed) and seven categories of traits (Big Five traits, trait anxiety and autistic traits). Consistent associations for both traits (in particular, conscientiousness, autistic traits and trait anxiety - the latter limited to emotional stimuli) and cognitive abilities (particularly visual processing) were identified. Overall, however, informativeness of future studies would benefit from checking and reporting the reliability of all measurement tools, applying multiplicity correction, using complementary techniques, study preregistration and testing why, rather than only if, a robust relation between certain individual differences and VS performance exists.

Insights into the relationship between eye movements and personality traits in restricted visual fields

Previous studies have suggested behavioral patterns, such as visual attention and eye movements, relate to individual personality traits. However, these studies mainly focused on free visual tasks, and the impact of visual field restriction remains inadequately understood. The primary objective of this study is to elucidate the patterns of conscious eye movements induced by visual field restriction and to examine how these patterns relate to individual personality traits. Building on previous research, we aim to gain new insights through two behavioral experiments, unraveling the intricate relationship between visual behaviors and individual personality traits. As a result, both Experiment 1 and Experiment 2 revealed differences in eye movements during free observation and visual field restriction. Particularly, simulation results based on the analyzed data showed clear distinctions in eye movements between free observation and visual field restriction conditions. This suggests that eye movements during free observation involve a mixture of conscious and unconscious eye movements. Furthermore, we observed significant correlations between conscious eye movements and personality traits, with more pronounced effects in the visual field restriction condition used in Experiment 2 compared to Experiment 1. These analytical findings provide a novel perspective on human cognitive processes through visual perception.

Grandiose narcissism associates with higher cognitive performance under stress through more efficient attention distribution: An eye-tracking study

Narcissism is a part of the Dark Triad that consists also of the traits of Machiavellianism and psychopathy. Two main types of narcissism exist: grandiose and vulnerable narcissism. Being a Dark Triad trait, narcissism is typically associated with negative outcomes. However, recent research suggests that at least the grandiose type may be linked (directly or indirectly) to positive outcomes including lower levels of psychopathology, higher school grades in adolescents, deeper and more strategic learning in university students and higher cognitive performance in experimental settings. The current pre-registered, quasi-experimental study implemented eye-tracking to assess whether grandiose narcissism indirectly predicts cognitive performance through wider distribution of attention on the Raven's Progressive Matrices task. Fifty-four adults completed measures of the Dark Triad, self-esteem and psychopathology. Eight months to one year later, participants completed the Raven's, while their eye-movements were monitored during high stress conditions. When controlling for previous levels of psychopathology, grandiose narcissism predicted higher Raven's scores indirectly, through increased variability in the number of fixations across trials. These findings suggest that grandiose narcissism predicts higher cognitive performance, at least in experimental settings, and call for further research to understand the implications of this seemingly dark trait for performance across various settings.

How do personality traits modulate real-world gaze behavior? Generated gaze data shows situation-dependent modulations

It has both scientific and practical benefits to substantiate the theoretical prediction that personality (Big Five) traits systematically modulate gaze behavior in various real-world (working) situations. Nevertheless, previous methods that required controlled situations and large numbers of participants failed to incorporate real-world personality modulation analysis. One cause of this research gap is the mixed effects of individual attributes (e.g., the accumulated attributes of age, gender, and degree of measurement noise) and personality traits in gaze data. Previous studies may have used larger sample sizes to average out the possible concentration of specific individual attributes in some personality traits, and may have imposed control situations to prevent unexpected interactions between these possibly biased individual attributes and complex, realistic situations. Therefore, we generated and analyzed real-world gaze behavior where the effects of personality traits are separated out from individual attributes. In Experiment 1, we successfully provided a methodology for generating such sensor data on head and eye movements for a small sample of participants who performed realistic nonsocial (data-entry) and social (conversation) work tasks (i.e., the first contribution). In Experiment 2, we evaluated the effectiveness of generated gaze behavior for real-world personality modulation analysis. We successfully showed how openness systematically modulates the autocorrelation coefficients of sensor data, reflecting the period of head and eye movements in data-entry and conversation tasks (i.e., the second contribution). We found different openness modulations in the autocorrelation coefficients from the generated sensor data of the two tasks. These modulations could not be detected using real sensor data because of the contamination of individual attributes. In conclusion, our method is a potentially powerful tool for understanding theoretically expected, systematic situation-specific personality modulation of real-world gaze behavior.

AI for Psychometrics: Validating Machine Learning Models in Measuring Emotional Intelligence with Eye-Tracking Techniques

AI, or artificial intelligence, is a technology of creating algorithms and computer systems that mimic human cognitive abilities to perform tasks. Many industries are undergoing revolutions due to the advances and applications of AI technology. The current study explored a burgeoning field-Psychometric AI, which integrates AI methodologies and psychological measurement to not only improve measurement accuracy, efficiency, and effectiveness but also help reduce human bias and increase objectivity in measurement. Specifically, by leveraging unobtrusive eye-tracking sensing techniques and performing 1470 runs with seven different machine-learning classifiers, the current study systematically examined the efficacy of various (ML) models in measuring different facets and measures of the emotional intelligence (EI) construct. Our results revealed an average accuracy ranging from 50-90%, largely depending on the percentile to dichotomize the EI scores. More importantly, our study found that AI algorithms were powerful enough to achieve high accuracy with as little as 5 or 2 s of eye-tracking data. The research also explored the effects of EI facets/measures on ML measurement accuracy and identified many eye-tracking features most predictive of EI scores. Both theoretical and practical implications are discussed.

Using Gaze for Behavioural Biometrics

A principled approach to the analysis of eye movements for behavioural biometrics is laid down. The approach grounds in foraging theory, which provides a sound basis to capture the uniqueness of individual eye movement behaviour. We propose a composite Ornstein-Uhlenbeck process for quantifying the exploration/exploitation signature characterising the foraging eye behaviour. The relevant parameters of the composite model, inferred from eye-tracking data via Bayesian analysis, are shown to yield a suitable feature set for biometric identification; the latter is eventually accomplished via a classical classification technique. A proof of concept of the method is provided by measuring its identification performance on a publicly available dataset. Data and code for reproducing the analyses are made available. Overall, we argue that the approach offers a fresh view on either the analyses of eye-tracking data and prospective applications in this field.

The Influence of Personality Traits on User Interaction with Recommendation Interfaces

Users’ personality traits can take an active role in affecting their behavior when they interact with a computer interface. However, in the area of recommender systems (RS), though personality-based RS has been extensively studied, most works focus on algorithm design, with little attention paid to studying whether and how the personality may influence users’ interaction with the recommendation interface. In this manuscript, we report the results of a user study (with 108 participants) that not only measured the influence of users’ personality traits on their perception and performance when using the recommendation interface but also employed an eye-tracker to in-depth reveal how personality may influence users’ eye-movement behavior. Moreover, being different from related work that has mainly been conducted in a single product domain, our user study was performed in three typical application domains (i.e., electronics like smartphones, entertainment like movies, and tourism like hotels). Our results show that mainly three personality traits, i.e., Openness to experience , Conscientiousness , and Agreeableness , significantly influence users’ perception and eye-movement behavior, but the exact influences vary across the domains. Finally, we provide a set of guidelines that might be constructive for designing a more effective recommendation interface based on user personality.

Personality Assessment Based on Multimodal Attention Network Learning With Category-Based Mean Square Error

Personality analysis is widely used in occupational aptitude tests and entrance psychological tests. However, answering hundreds of questions at once seems to be a burden. Inspired by personality psychology, we propose a multimodal attention network with Category-based mean square error (CBMSE) for personality assessment. With this method, we can obtain information about one's behaviour from his or her daily videos, including his or her gaze distribution, speech features, and facial expression changes, to accurately determine personality traits. In particular, we propose a new approach to implementing an attention mechanism based on the facial Region of No Interest (RoNI), which can achieve higher accuracy and reduce the number of network parameters. Simultaneously, we use CBMSE, a loss function with a higher penalty for the fuzzy boundary in personality assessment, to help the network distinguish boundary data. After effective data fusion, this method achieves an average prediction accuracy of 92.07%, which is higher than any other state-of-the-art model on the dataset of the ChaLearn Looking at People challenge in association with ECCV 2016.

Face Masks Impair Basic Emotion Recognition

Abstract. With the widespread adoption of masks, there is a need for understanding how facial obstruction affects emotion recognition. We asked 120 participants to identify emotions from faces with and without masks. We also examined if recognition performance was related to autistic traits and personality. Masks impacted recognition of expressions with diagnostic lower face features the most and those with diagnostic upper face features the least. Persons with higher autistic traits were worse at identifying unmasked expressions, while persons with lower extraversion and higher agreeableness were better at recognizing masked expressions. These results show that different features play different roles in emotion recognition and suggest that obscuring features affects social communication differently as a function of autistic traits and personality.

Twenty seconds of visual behaviour on social media gives insight into personality

Eye tracking allows the researcher to capture individual differences in the expression of visual exploration behaviour, which in certain contexts has been found to reflect aspects of the user's preferences and personality. In a novel approach, we recorded the eye movements of 180 participants whilst they browsed their Facebook News Feed and employed a machine learning approach to predict each of the self-reported Big Five personality traits from this viewing behaviour. We identify that specific visual behaviours are informative of an individual's personality trait information, and can be used to psychologically profile social networking site users significantly better than chance after collecting only 20 seconds of viewing behaviour. We discuss potential applications for user engagement during human-computer interactions, and highlight potential privacy concerns.

Expressing Personality Through Non-verbal Behaviour in Real-Time Interaction

The attribution of traits plays an important role as a heuristic for how we interact with others. Many psychological models of personality are analytical in that they derive a classification from reported or hypothesised behaviour. In the work presented here, we follow the opposite approach: Our personality model generates behaviour that leads an observer to attribute personality characteristics to the actor. Concretely, the model controls all relevant aspects of non-verbal behaviour such as gaze, facial expression, gesture, and posture. The model, embodied in a virtual human, affords to realistically interact with participants in real-time. Conceptually, our model focuses on the two dimensions of extra/introversion and stability/neuroticism. In the model, personality parameters influence both, the internal affective state as well as the characteristic of the behaviour execution. Importantly, the parameters of the model are based on empirical findings in the behavioural sciences. To evaluate our model, we conducted two types of studies. Firstly, passive experiments where participants rated videos showing variants of behaviour driven by different personality parameter configurations. Secondly, presential experiments where participants interacted with the virtual human, playing rounds of the Rock-Paper-Scissors game. Our results show that the model is effective in conveying the impression of the personality of a virtual character to users. Embodying the model in an artificial social agent capable of real-time interactive behaviour is the only way to move from an analytical to a generative approach to understanding personality, and we believe that this methodology raises a host of novel research questions in the field of personality theory.

Visual exploration dynamics are low-dimensional and driven by intrinsic factors

When looking at visual images, the eyes move to the most salient and behaviourally relevant objects. Saliency and semantic information significantly explain where people look. Less is known about the spatiotemporal properties of eye movements (i.e., how people look). We show that three latent variables explain 60% of eye movement dynamics of more than a hundred observers looking at hundreds of different natural images. The first component explaining 30% of variability loads on fixation duration, and it does not relate to image saliency or semantics; it approximates a power-law distribution of gaze steps, an intrinsic dynamic measure, and identifies observers with two viewing styles: static and dynamic. Notably, these viewing styles were also identified when observers look at a blank screen. These results support the importance of endogenous processes such as intrinsic dynamics to explain eye movement spatiotemporal properties.

Influence of personality traits on users’ viewing behaviour

Different views on the role of personal factors in moderating individual viewing behaviour exist. This study examined the impact of personality traits on individual viewing behaviour of facial stimulus. A total of 96 students (46 males and 50 females, age 23–28 years) were participated in this study. The Big-Five personality traits of all the participants together with data related to their eye-movements were collected and analysed. The results showed three groups of users who scored high on the personality traits of neuroticism, agreeableness and conscientiousness. Individuals who scored high in a specific personality trait were more probably to interpret the visual image differently from individuals with other personality traits. To determine the extent to which a specific personality trait is associated with users’ viewing behaviour of visual stimulus, a predictive model was developed and validated. The prediction results showed that 96.73% of the identified personality traits can potentially be predicted by the viewing behaviour of users. The findings of this study can expand the current understanding of human personality and choice behaviour. The study also contributes to the perceptual encoding process of faces and the perceptual mechanism in the holistic face processing theory.

Age-related changes in gaze behaviour during social interaction: An eye-tracking study with an embodied conversational agent

Previous research has highlighted age-related differences in social perception, in particular emotional expression processing. To date, such studies have largely focused on approaches that use static emotional stimuli that the participant has to identify passively without the possibility of any interaction. In this study, we propose an interactive virtual environment to better address age-related variations in social and emotional perception. A group of 22 young (18-30 years) and 20 older (60-80 years) adults were engaged in a face-to-face conversation with an embodied conversational agent. Participants were invited to interact naturally with the agent and to identify his facial expression. Their gaze behaviour was captured by an eye-tracking device throughout the interaction. We also explored whether the Big Five personality traits (particularly extraversion) and anxiety modulated gaze during the social interaction. Findings suggested that age-related differences in gaze behaviour were only apparent when decoding social signals (i.e., listening to a partner's question, identifying facial expressions) and not when communicating social information (i.e., when speaking). Furthermore, higher extraversion levels consistently led to a shorter amount of time gazing towards the eyes, whereas higher anxiety levels led to slight modulations of gaze only when participants were listening to questions. Face-to-face conversation with virtual agents can provide a more naturalistic framework for the assessment of online socio-emotional interaction in older adults, which is not easily observable in classical offline paradigms. This study provides novel and important insights into the specific circumstances in which older adults may experience difficulties in social interactions.

Personality Sensing

Personality detection is an important task in psychology, as different personality traits are linked to different behaviours and real-life outcomes. Traditionally it involves filling out lengthy questionnaires, which is time-consuming, and may also be unreliable if respondents do not fully understand the questions or are not willing to honestly answer them. In this article, we propose a framework for objective personality detection that leverages humans’ physiological responses to external stimuli. We exemplify and evaluate the framework in a case study, where we expose subjects to affective image and video stimuli, and capture their physiological responses using non-invasive commercial-grade eye-tracking and skin conductivity sensors. These responses are then processed and used to build a machine learning classifier capable of accurately predicting a wide range of personality traits. We investigate and discuss the performance of various machine learning methods, the most and least accurately predicted traits, and also assess the importance of the different stimuli, features, and physiological signals. Our work demonstrates that personality traits can be accurately detected, suggesting the applicability of the proposed framework for robust personality detection and use by psychology practitioners and researchers, as well as designers of personalised interactive systems.

Chinese college students' ability to recognize facial expressions based on their meaning-in-life profiles: An eye-tracking study

OBJECTIVE

People can be categorized into one of four meaning-in-life profiles: High Presence High Search (HPHS), High Presence Low Search (HPLS), Low Presence High Search (LPHS), and Low Presence Low Search (LPLS).The main goal of this study is to provide a theoretical explanation for why Chinese people with different meaning-in-life profiles have different mental health levels than Western people, based on their emotional-cognitive-processing ability.

METHOD

We adopted eye-movement analysis and recognition-judgment experimental paradigm concerning absolute-recognition judgment and relative-recognition judgment in our study. Moreover, we applied a multifactor and multilevel mixed-experimental design. We selected 118 participants for the experiments from the 788 Chinese college students who responded.

RESULTS

Our results showed that HPHS individuals preferred positive-emotion pictures, LPLS individuals preferred negative-emotion pictures, HPLS individuals preferred positive- and neutral-emotion pictures, and LPHS individuals preferred neutral-emotion pictures. Moreover, HPHS individuals were better at accurately processing facial expression from pictures, while LPLS individuals lacked such ability. The fine-processing ability of HPLS and LPHS individuals was lower than that of HPHS yet higher than that of LPLS individuals. Moreover, the features of HPLS individuals were closer to HPHS, while those of LPHS individuals were closer to LPLS.

CONCLUSIONS

Our findings support the hypothesis that meaning-in-life profiles have different immediate processing abilities and preferences regarding facial expression recognition and different emotional-cognitive-processing ability.

Global visual salience of competing stimuli

Current computational models of visual salience accurately predict the distribution of fixations on isolated visual stimuli. It is not known, however, whether the global salience of a stimulus, that is, its effectiveness in the competition for attention with other stimuli, is a function of the local salience or an independent measure. Further, do task and familiarity with the competing images influence eye movements? Here, we investigated the direction of the first saccade to characterize and analyze the global visual salience of competing stimuli. Participants freely observed pairs of images while eye movements were recorded. The pairs balanced the combinations of new and already seen images, as well as task and task-free trials. Then, we trained a logistic regression model that accurately predicted the location-left or right image-of the first fixation for each stimulus pair, accounting too for the influence of task, familiarity, and lateral bias. The coefficients of the model provided a reliable measure of global salience, which we contrasted with two distinct local salience models, GBVS and Deep Gaze. The lack of correlation of the behavioral data with the former and the small correlation with the latter indicate that global salience cannot be explained by the feature-driven local salience of images. Further, the influence of task and familiarity was rather small, and we reproduced the previously reported left-sided bias. Summarized, we showed that natural stimuli have an intrinsic global salience related to the human initial gaze direction, independent of the local salience and little influenced by task and familiarity.

Presence, Mixed Reality, and Risk-Taking Behavior: A Study in Safety Interventions

Immersive environments have been successfully applied to a broad range of safety training in high-risk domains. However, very little research has used these systems to evaluate the risk-taking behavior of construction workers. In this study, we investigated the feasibility and usefulness of providing passive haptics in a mixed-reality environment to capture the risk-taking behavior of workers, identify at-risk workers, and propose injury-prevention interventions to counteract excessive risk-taking and risk-compensatory behavior. Within a mixed-reality environment in a CAVE-like display system, our subjects installed shingles on a (physical) sloped roof of a (virtual) two-story residential building on a morning in a suburban area. Through this controlled, within-subject experimental design, we exposed each subject to three experimental conditions by manipulating the level of safety intervention. Workers' subjective reports, physiological signals, psychophysical responses, and reactionary behaviors were then considered as promising measures of Presence. The results showed that our mixed-reality environment was a suitable platform for triggering behavioral changes under different experimental conditions and for evaluating the risk perception and risk-taking behavior of workers in a risk-free setting. These results demonstrated the value of immersive technology to investigate natural human factors.

Oculomotor Control in Amputee Soccer Players

The authors investigated the dynamics of saccadic parameters during a stationary oculomotor target task in amputee soccer players (n = 16), able-bodied soccer players (n = 16), and nonathletic control subjects (n = 16). Eye movements during the visual-search tasks were recorded binocularly using a mobile eye-tracking system, and the gaze parameters were analyzed (fixation duration, saccade duration, saccade amplitude, saccade average acceleration, saccade peak deceleration, saccade average velocity, and ocular mobility index). The average saccade acceleration in the amputee soccer players was significantly lower than in the able-bodied players (p = .021). Other saccade characteristics in disabled athletes were comparable to those of the able-bodied groups. Moreover, the able-bodied soccer players presented faster saccadic parameters than nonathletes in terms of saccade acceleration (p = .002), deceleration (p = .015), and velocity (p = .009). The modification of oculomotor functions may result from extensive practice and participation in ball games. The authors' hypothesis that oculomotor functions in amputee soccer players may be impaired was not fully confirmed.

The Dynamics of Attention Shifts Among Concurrent Speech in a Naturalistic Multi-speaker Virtual Environment

Focusing attention on one speaker on the background of other irrelevant speech can be a challenging feat. A longstanding question in attention research is whether and how frequently individuals shift their attention towards task-irrelevant speech, arguably leading to occasional detection of words in a so-called unattended message. However, this has been difficult to gauge empirically, particularly when participants attend to continuous natural speech, due to the lack of appropriate metrics for detecting shifts in internal attention. Here we introduce a new experimental platform for studying the dynamic deployment of attention among concurrent speakers, utilizing a unique combination of Virtual Reality (VR) and Eye-Tracking technology. We created a Virtual Café in which participants sit across from and attend to the narrative of a target speaker. We manipulated the number and location of distractor speakers by placing additional characters throughout the Virtual Café. By monitoring participant's eye-gaze dynamics, we studied the patterns of overt attention-shifts among concurrent speakers as well as the consequences of these shifts on speech comprehension. Our results reveal important individual differences in the gaze-pattern displayed during selective attention to speech. While some participants stayed fixated on a target speaker throughout the entire experiment, approximately 30% of participants frequently shifted their gaze toward distractor speakers or other locations in the environment, regardless of the severity of audiovisual distraction. Critically, preforming frequent gaze-shifts negatively impacted the comprehension of target speech, and participants made more mistakes when looking away from the target speaker. We also found that gaze-shifts occurred primarily during gaps in the acoustic input, suggesting that momentary reductions in acoustic masking prompt attention-shifts between competing speakers, in line with "glimpsing" theories of processing speech in noise. These results open a new window into understanding the dynamics of attention as they wax and wane over time, and the different listening patterns employed for dealing with the influx of sensory input in multisensory environments. Moreover, the novel approach developed here for tracking the locus of momentary attention in a naturalistic virtual-reality environment holds high promise for extending the study of human behavior and cognition and bridging the gap between the laboratory and real-life.

Components of the Triarchic Model of Psychopathy and the Five-Factor Model Domains Share Largely Overlapping Nomological Networks

The triarchic model of psychopathy is a recently developed model of psychopathy that identifies three primary domains: Boldness, Meanness, and Disinhibition. These traits overlap substantially with general and pathological five-factor model of personality (Boldness = low Neuroticism + high Extraversion; Meanness = low Agreeableness; Disinhibition = low Conscientiousness). In the current study (total N = 1,266), we compare domains from the triarchic model of psychopathy and five-factor model in relation to self- and informant-report of external criteria (e.g., pathological traits, antisocial behavior), and quantified their absolute similarity using a profile-matching approach. The corresponding traits from these models show large interrelations and very similar convergent and divergent relations, suggesting that unaltered traits from one can be considered excellent representations of the other. Results are discussed in terms of the benefits of using a unifying trait-based model to study psychopathy, as well as personality disorders more broadly.

Correlations between holistic processing, Autism quotient, extraversion, and experience and the own-gender bias in face recognition

The variability in the own-gender bias (OGB) in face-recognition is thought to be based on experience and the engagement of expert face processing mechanisms for own-gender faces. Experience is also associated with personality characteristics such as extraversion and Autism, yet the effects of these variables on the own-gender bias has not been explored. We ran a face recognition study exploring the relationships between own-gender experience, holistic processing (measured using the face-inversion effect, composite face effect, and the parts-and-wholes test), personality characteristics (extraversion and Autism Quotient) and the OGB. Findings did not support a mediational account where experience increases holistic processing and this increases the OGB. Rather, there was a direct relationship between extraversion and Autism Quotient and the OGB. We interpret this as personality characteristics having an effect on the motivation to process own-gender faces more deeply than opposite-gender faces.

Ruminative minds, wandering minds: Effects of rumination and mind wandering on lexical associations, pitch imitation and eye behaviour

This study demonstrates that rumination is reflected in two behavioural signals that both play an important role in face-to-face interactions and provides evidence for the negative impact of rumination on social cognition. Sixty-one students were randomly assigned either to a condition in which rumination was induced or to a control condition. Their task was to play a speech-based word association game with an Embodied Conversational Agent during which their word associations, pitch imitation and eye movements were measured. Two questionnaires assessed their ruminative tendencies and mind wandering thoughts, respectively. Rumination predicted differences in task-related mind wandering, polarity of lexical associations, pitch imitation, and blinks while mind wandering predicted differences in saccades. This outcome may show that rumination has a negative impact on certain aspects of social interactions.

Eye Movements During Everyday Behavior Predict Personality Traits

Besides allowing us to perceive our surroundings, eye movements are also a window into our mind and a rich source of information on who we are, how we feel, and what we do. Here we show that eye movements during an everyday task predict aspects of our personality. We tracked eye movements of 42 participants while they ran an errand on a university campus and subsequently assessed their personality traits using well-established questionnaires. Using a state-of-the-art machine learning method and a rich set of features encoding different eye movement characteristics, we were able to reliably predict four of the Big Five personality traits (neuroticism, extraversion, agreeableness, conscientiousness) as well as perceptual curiosity only from eye movements. Further analysis revealed new relations between previously neglected eye movement characteristics and personality. Our findings demonstrate a considerable influence of personality on everyday eye movement control, thereby complementing earlier studies in laboratory settings. Improving automatic recognition and interpretation of human social signals is an important endeavor, enabling innovative design of human–computer systems capable of sensing spontaneous natural user behavior to facilitate efficient interaction and personalization.

Neuroticism, schizotypy, and scale anchors influence eye movement behaviour in the visual exploration of abstract art: An exploratory study

The same piece of artwork can attract both admiration and rejection from different people. One potential explanation for this effect is individual differences in perceptual biases, which influence the way in which we see different aspects of the same image. We explored the relationship between individual differences (i.e., personality) and eye movements for examinations of abstract art. Images were presented for 5000ms, after which participants judged aesthetic appeal and perceived value using visual analogue scales. Scale anchor labels (Looks Good/Looks Bad; $0/$5000) were counterbalanced between participants such that positive labels were on the left half of the time and on the right half of the time. Overall, more fixations occurred to the right and upper visual fields. Neuroticism significantly predicted the proportion of fixations to the left, whereas cognitive disorganisation negatively predicted the proportion of fixations to upper space. Participants found images more aesthetically pleasing and more valuable when positive anchors were on the left. Findings demonstrate that personality traits influence fixation patterns. Further, the positioning of positive anchor labels on the left leads to higher ratings of visual stimuli.

Eye-Tracking Evidence of a Maintenance Bias in Social Anxiety

Background: The mechanisms and triggers of the attentional bias in social anxiety are not yet fully determined, and the modulating role of personality traits is being increasingly acknowledged. Aims: Our main purpose was to test whether social anxiety is associated with mechanisms of hypervigilance, avoidance (static biases), vigilance-avoidance or the maintenance of attention (dynamic biases). Our secondary goal was to explore the role of personality structure in shaping the attention bias. Method: Participants with high vs low social anxiety and different personality structures viewed pairs of faces (free-viewing eye-tracking task) representing different emotions (anger, happiness and neutrality). Their eye movements were registered and analysed for both whole-trial (static) and time-dependent (dynamic) measures. Results: Comparisons between participants with high and low social anxiety levels did not yield evidence of differences in eye-tracking measures for the whole trial (latency of first fixation, first fixation direction, total dwell time), but the two groups differed in the time course of overt attention during the trial (dwell time across three successive time segments): participants with high social anxiety were slower in disengaging their attention from happy faces. Similar results were obtained using a full-sample, regression-based analysis. Conclusion: Our results speak in favour of a maintenance bias in social anxiety. Preliminary results indicated that personality structure may not affect the maintenance (dynamic) bias of socially anxious individuals, although depressive personality structures may favour manifestations of a (static) hypervigilance bias.

Exploration and Exploitation in Natural Viewing Behavior

Many eye-tracking studies investigate visual behavior with a focus on image features and the semantic content of a scene. A wealth of results on these aspects is available, and our understanding of the decision process where to look has reached a mature stage. However, the temporal aspect, whether to stay and further scrutinize a region (exploitation) or to move on and explore image regions that were yet not in the focus of attention (exploration) is less well understood. Here, we investigate the trade-off between these two processes across stimuli with varying properties and sizes. In a free viewing task, we examined gaze parameters in humans, involving the central tendency, entropy, saccadic amplitudes, number of fixations and duration of fixations. The results revealed that the central tendency and entropy scaled with stimulus size. The mean saccadic amplitudes showed a linear increase that originated from an interaction between the distribution of saccades and the spatial bias. Further, larger images led to spatially more extensive sampling as indicated by a higher number of fixations at the expense of reduced fixation durations. These results demonstrate a profound shift from exploitation to exploration as an adaptation of main gaze parameters with increasing image size.

Rapid Communication: Personality and attention: Levels of neuroticism and extraversion can predict attentional performance during a change detection task

The present study demonstrates that levels of extraversion and neuroticism can predict attentional performance during a change detection task. After completing a change detection task built on the flicker paradigm, participants were assessed for personality traits using the Revised Eysenck Personality Questionnaire (EPQ–R). Multiple regression analyses revealed that higher levels of extraversion predict increased change detection accuracies, while higher levels of neuroticism predict decreased change detection accuracies. In addition, neurotic individuals exhibited decreased sensitivity A′ and increased fixation dwell times. Hierarchical regression analyses further revealed that eye movement measures mediate the relationship between neuroticism and change detection accuracies. Based on the current results, we propose that neuroticism is associated with decreased attentional control over the visual field, presumably due to decreased attentional disengagement. Extraversion can predict increased attentional performance, but the effect is smaller than the relationship between neuroticism and attention.

What Guides Visual Overt Attention under Natural Conditions? Past and Future Research

In the last decade, overt attention under natural conditions became a prominent topic in neuroscientific and psychological research. In this context, one central question is “what guides the direction of gaze on complex visual scenes?” In the present review recent research on bottom-up influences on overt attention is presented first. Against this background, strengths and limitations of the bottom-up approach are discussed and future directions in this field are outlined. In addition to that, the current scope on top-down factors in visual attention is enlarged by discussing the impact of emotions and motivational tendencies on viewing behavior. Overall, this review highlights how behavioral and neurophysiological research on overt attention can benefit from a broader scope on influential factors in visual attention.