Neuroscience of Consciousness

Previous studies suggest that visual mental imagery (VMI) acts as a weaker form of top-down visual perception (VP), with the two becoming more similar as VMI vividness increases. However, this relationship remains ill-defined, and it is unclear precisely how much weaker VMI is relative to VP. Here, we introduce an original probabilistic deep learning approach to quantify vividness at the neural level. Thirty-four participants either imagined or perceived stimuli presented at varying levels of vividness and provided trial-by-trial, picture-based vividness ratings. EEG activity recorded during VP was used to train a convolutional neural network (EEGNet) to predict perceived vividness from eight posterior electrodes located around early visual areas. A leave-one-subject-out cross-validation procedure showed that the model generalised across participants with above-chance accuracy during VP. On VP trials, predictions tracked vividness labels, with reliable interpolation to new vivid labels not included during training. Applied to VMI trials, mean expected VMI vividness remained substantially lower than expected vividness for seen stimuli but slightly higher than baseline, supporting a barely rather than quasi depictive imagery. For 91% of participants, mean expected VMI vividness was also lower than, yet scaled with, mean reported VMI vividness. This framework provides a principled way to quantify and compare VMI and VP on a shared neural-behavioural scale, with implications for studying individual differences and aphantasia.

AO_SCPLOWBSTRACTC_SCPLOWSpontaneous thoughts constitute most of everyday inner experience, yet long-standing methodological challenges obscure a thorough exploration of their content and neurophysiological underpinnings. Traditional approaches relying on thought probes impose strict constraints on phenomenological reports, whereas online verbal reports disrupt the natural flow of experience while interfering neural signals with motor artifacts. Here, we designed and tested an alternative approach to assess the neural basis of spontaneous thoughts combining delayed verbal retrospective free reports (RFR) with automated phenomenological ratings generated by large language models (LLMs). Twenty-two participants performed an eyes-closed free-thinking task, providing reports that were evaluated along ten phenomenological dimensions by four state-of-the-art LLMs and a panel of human raters. Machine-learning models (ML) were then trained to decode LLM-derived ratings from EEG spectral, complexity, and connectivity features. Our analyses showed that inter-rater agreement among LLMs exceeded that of human raters whereas ML models achieved above-chance accuracy for the prediction of emotional valence. These findings provide support for the use of LLMs for a scalable phenomenological annotation of spontaneous thoughts and suggest that their affective dimensions can be decoded from concurrent EEG activity.

Flow, as defined by Mihalyi Csikszentmihalyi (1975), is a holistic sensation experienced when individuals are fully immersed in an activity, resulting in a mental state characterized by a diminished sense of self and altered perception of time. To investigate the global neural dynamics underlying flow, we employed EEG microstate analysis to capture the spatial and temporal properties of dominant transient global brain states (Lehmann et al., 1998). In a study involving 43 participants playing the video game Thumper for 25 minutes, we extracted three four-minute EEG segments from each session corresponding to reported experiences of flow, boredom, and frustration, as determined by self-reports and performance metrics. Across conditions, six distinct microstate topographies (A-F) accounted for most of the global variance. Given that reduced self-referential processing is a key feature of flow, we hypothesized that flow would modulate the properties of microstates C and E, which have been associated with brain regions resembling the default mode network (DMN). Compared to boredom and frustration, the flow condition showed significantly decreased global explained variance, mean duration, time coverage, and occurrence frequency of microstate E, as well as reduced mean duration and time coverage of microstate C. These findings suggest that microstates associated with self-referential processing are shorter and less frequent during flow than during boredom and frustration. This supports the notion that the flow experience modulates global brain dynamics, particularly within the DMN. Furthermore, our results align with previous research reporting reduced DMN activity during meditative and psychedelic states, reinforcing the idea of diminished self-awareness in such conditions.

Can we rescue a percept that would otherwise be processed non-consciously? While pre-stimulus alerting is known to facilitate conscious access, the effects of retro-cues remain ambiguous due to methodological confounds in existing literature. Specifically, most studies finding retro-cue benefits have relied on spatial features (such as lateralized targets or cues) which confound alerting with spatial selection. Our design addresses this gap by employing central visual targets and non-lateralized auditory cues, thereby isolating the temporal boost of phasic alerting from spatial orienting. Across four experiments, participants reported the presence and orientation of a central Gabor patch presented at near-threshold ([~]50% detection) or higher visibility ([~]75% detection) levels. An auditory alerting tone was presented prior, simultaneously or after the Gabor, at various short and long stimulus onset asynchronies, with both short and long temporal ranges. Results consistently showed that pre-stimulus and simultaneous cues significantly enhanced conscious perception, increasing both seen rates and (in some experiments) perceptual sensitivity. Crucially, the effectiveness of retro-cues strictly depended on stimulus visibility. While retro-cues provided no benefit under near-threshold conditions, an alerting cue presented 200 ms after target offset significantly increased the proportion of seen targets when target visibility was higher. This suggests that a sufficiently robust sensory trace can be retrospectively rescued or promoted into awareness by a late alerting boost, and that pure alerting retro-cues are able to modulate conscious perception even when no spatial features are involved. These findings demonstrate a decoupling of stimulus onset from the timing of conscious access, providing a behavioural platform to arbitrate between competing models of consciousness such as the Global Neuronal Workspace Theory and the phenomenal/access distinction of consciousness.

Virtual Reality (VR) applications depend on eliciting spatial presence, the subjective experience of being physically located within a virtual environment. Although individual differences have long been theorised to contribute to this experience, their role in highly immersive VR systems remains contested. The present study investigated whether trait absorption predicts spatial presence and whether this relationship is mediated by attention allocation. Seventy participants (44 female, 26 male; M age = 22.90, SD = 4.88) completed a 6-minute VR session using a Meta Quest 3 Head-Mounted Display and validated self-report measures of trait absorption (Tellegen Absorption Scale), attention allocation, and spatial presence (MEC-Spatial Presence Questionnaire). Path analysis confirmed a significant, complete mediation pathway: trait absorption positively predicted attention allocation ({beta} = 0.27, p = .013), which in turn strongly predicted spatial presence ({beta} = 0.54, p < .001). The direct path from absorption to spatial presence was non-significant ({beta} = 0.11, p = .325), indicating complete mediation. The indirect effect was significant ({beta} = 0.15; 95% BCa CI [0.025, 0.291]). The model explained a sizeable 33.8% of the variance in spatial presence (Cohens f{superscript 2} = 0.51). Post-hoc dose-response analysis revealed that trait absorption acts as a cognitive amplifier: the strength of the attention-presence relationship tripled from low-absorption ({beta} = 0.33, R{superscript 2} = .15) to high-absorption individuals ({beta} = 1.00, R{superscript 2} = .56). These findings demonstrate that individual differences remain important in highly immersive VR by modulating the effectiveness of attentional focus, offering promising directions for tailoring VR interventions.

Aesthetic experiences in everyday life unfold under continuously changing visual input. Although these experiences clearly depend on the observer and context, they are partly explained by the visual features of the input. Here, we investigated how well a combination of visual features predicts dynamic aesthetic experiences during naturalistic and artistic movie watching. In two experiments, participants continuously rated the aesthetic appeal of either the nature documentary Home or the animated art-style movie Loving Vincent. We modeled moment-to-moment ratings using image-computable visual features extracted from each movie frame, including visual fluency, color and motion statistics, and symmetry. Linear models trained on these features reliably predicted aesthetic ratings for new movie parts, both within and across observers, pointing to shared perceptual influences on aesthetic experiences. Model comparisons showed that visual fluency and color-related features were most informative for predicting aesthetic experience in both movies. Critically, models trained on one movie could reliably predict aesthetic appeal ratings in the other movie, despite the movies remarkably different content and styles. Color features were most informative for cross-movie prediction. We conclude that visual features shape dynamic and naturalistic aesthetic experiences, and that the mapping of visual features onto aesthetic appeal is stable across observers and different movie content.

Human experience unfolds continuously, yet it is remembered and understood as a sequence of discrete events. How the brain segments this stream of experience, particularly under naturalistic conditions, remains poorly understood. Here we investigate the neural dynamics associated with event boundaries during active navigation through architectural transitions. Using mobile electroencephalography combined with virtual reality, we analyzed data from participants freely walking between rooms and repeatedly crossing doorways. Time-frequency analysis of source-localized neural activity revealed a robust increase in theta-band power (4-8 Hz) over temporo-occipital and parietal regions approximately 300-450 ms after passing through a doorway. This effect was consistent across participants and independent component clusters, indicating a reliable neural signature of architectural transitions. We interpret this theta response within frameworks of event segmentation and Bayesian inference, suggesting that doorways trigger a transient reconfiguration of distributed neural networks when ongoing predictions can no longer be maintained and a new event model must be inferred. By preserving the natural coupling between perception, movement, and environmental structure, our findings demonstrate that architecture provides meaningful boundaries that shape brain dynamics and the organization of experience. More broadly, this work highlights the power of naturalistic experimentation and positions architectural space as an active medium for investigating how the brain structures events.

Realism and naturalness remain unresolved questions in vision science. This study investigates whether the physical gamut correlates with realism judgements. We conducted psychophysical experiments where observers judged the realism of natural scenes with target regions manipulated across the CIE 1931 color space. Results initially showed a moderate-to-strong correlation between judgements and a theoretical physical gamut derived from optimal colors. Further analysis revealed that the most detrimental points were in the saturated green region of the CIE 1931 xy chromaticity diagram; removing them yielded a very strong correlation. To explain this discrepancy, we modeled a real-world physical gamut based on USGS and ECOSTRESS spectral libraries. The analysis revealed that the detrimental green chromaticities might be non-existent in the real-world. Since physical gamut theory posits that the visual system constructs internal references through empirical observation of the world, the absence of these colors in nature might be a plausible explanation to the theoretical models failure. Ultimately, the real-world gamut exhibited an even stronger correlation with judgements, supporting our hypothesis while suggesting that the theoretical model may not be the optimal approximation of the actual physical gamut. These findings contribute to discussions on perceptual realism and offer a framework for enhancing rendering technologies.

Numerous studies have demonstrated rapid (< 100 ms) visuo-cortical differentiation of threat-associated faces. This may be due to low-spatial frequency (LSF) visual information originating from magnocellular pathways. Yet it remains unclear whether potentially magnocellular fear signals extend beyond evolutionarily prepared emotional faces and whether they are subject to short-term neuroplasticity. If so, spatial frequency characteristics should modulate processing of faces with newly acquired threat-relevance. Furthermore, it is unknown whether sub-bands of the visual spectrum are associated with autonomic arousal. Using a differential fear-conditioning paradigm, this study tested whether early visual attentional capture, indicated by the P1 event-related potential component, prioritizes LSF information of threat-associated faces with neutral expressions. Additionally, it was tested whether such effects would be paralleled by threat differentiation in the skin conductance response (SCR). For contingency aware participants, stimulus ratings confirmed successful fear conditioning and participants showed a selective left-hemispheric enhancement of the P1 in response to LSF threat-faces. By contrast, CS differentiation in the SCR was not modulated by spatial frequencies but by stimulus duration, with longer CS presentations resulting in larger SCR to threat compared to neutral faces. For contingency unaware participants, trial-by-trial amplitudes of P1 and SCR were positively correlated. Data support the notion that magnocellular-cortical pathways adapt quickly to novel threat-associations and facilitate rapid threat retrieval even for perceptually neutral faces. However, at least in the short term, these signals do not necessarily associate with anticipatory arousal in SCR. Impact statementOur electroencephalography (EEG) study provides evidence for distinct contributions of subcortical signals during early visual perception of fear-conditioned faces (P1 event-related potential) but not autonomic arousal (skin conductance response). Instead, skin conductance responses reflected conscious anticipatory arousal irrespective of the visual pathway. Together, these results reveal parallel but dissociable mechanisms of fear perception that are differentially sensitive to visual properties of threat-associated faces.

Color is a prominent feature of visual experience, yet humans can recognize objects easily and accurately from grayscale images. We examined whether color becomes more useful when spatial information is degraded due to blurring. Participants viewed naturalistic scenes in color or grayscale, and reported whether a named target object was present across a range of blur levels that simulated optical defocus from 0-8 diopters. With unblurred images, performance did not differ between color and grayscale conditions, but as blur increased, recognition accuracy declined. Color provided a modest but reliable advantage at higher levels of blur, suggesting that color becomes increasingly useful when optical quality is degraded. We hypothesize that the evolutionary shift towards trichromacy may have been partially driven by the need to compensate for optical degradation due to aging and/or accumulated light exposure.

A critical aspect of human cognition is the ability to use our knowledge about the laws of physics to make predictions about physical events. Whether this ability is based on abstract processes or is grounded in our body-environment interactions remains an open debate. We used physical reasoning under altered gravity as a model system to show that humans real-time embodied experience modifies their high-level physical reasoning. Specifically, we tested participants in computerised reasoning games, while disrupting their gravitational signalling using Galvanic Vestibular Stimulation (GVS). Participants failed more and had suboptimal strategies under the GVS condition compared to no-GVS in games requiring reasoning about terrestrial gravity. However, the effects of GVS were reduced when the games included reasoning about altered gravity. Our findings demonstrate how the physical experience of the body shifts high-level cognitive skill as reasoning, suggesting that humans mental representation of the world is grounded in adaptable physical mechanisms.

Sense of agency (SoA), the experience of controlling ones actions and their consequences, is crucial for self-representation and adaptive goal-directed behavior. Classic comparator models explain SoA as the match between predicted and actual sensorimotor outcomes, whereas inference-based and Bayesian accounts emphasize cue integration and probabilistic weighting. Besides the influence of action-outcome contingencies on SoA, the feedback effect of perceived SoA on cognitive processing is also crucial for cognitive performance. Much of todays cognitive work is performed through interaction with devices that are not entirely reliable or are prone to operator error. Against this background, it is of particular interest whether the impact of an expectancy violation differs depending on whether the outcome is attributed to a malfunctioning system or to ones own mistake. To investigate this, the present EEG study deploys manipulated performance feedback in a color-discrimination task, while EEG was recorded. Thirty-five participants performed in this task with periods of veridical feedback, periods with feedback simulating an increased error rate, and periods of feedback suggesting malfunctioning response buttons. Behavioral performance was decomposed using the EZ-diffusion model, and time-frequency EEG analyses focused on event-related alpha, beta, and theta oscillations. The participants responded significantly slower in the self-attribution of errors condition compared to neutral feedback, and also significantly slower in the system-attribution of errors condition compared to self-attribution of errors. Decomposing behavior using drift-diffusion modeling indicates that a general decrease of response times with manipulated feedback can be attributed to decreased drift rates, whereas the difference between the self and system error conditions are reflected in the non-decision time. In the EEG, the manipulated feedback was reflected in attenuated decreases of occipital alpha and sensorimotor beta power during the cue-target interval. Furthermore, system-versus self-attributed errors elicited stronger feedback-locked midfrontal theta responses. Our findings suggest a functional dissociation within the agency inference process, where perceived controllability regulates preparatory investment of cognitive resources, while the attribution of action-outcome discrepancies seem to modulate sensory processes or motor-execution.

Humanity has always admired and created artwork, but the neurocognitive mechanisms behind artistic experience are still elusive. Professional artists and their intimate relationship with their artworks provide a unique opportunity to study the nature of art experience due to their expertise in both art making and art appreciation. During two fMRI tasks, professional artists (N=20) made aesthetic judgments on their own and other artists paintings (aesthetic appreciation task); they also mentally reconstructed the moments when they conceived their artworks or, as a control condition, when they visited now-familiar places for the first time (reconstruction by imagery task). During art appreciation of their own (as compared to other artists) paintings, participants showed stronger recruitment of bilateral posterior parietal cortices, the left lateral occipitotemporal cortex, and the dorso-central sector of the right insula, that is, action-related brain regions also involved in encoding the emotional components of movements. The reconstruction of their own artistic creation (as compared to episodic memory retrieval) involved the left fronto-parietal network associated with motor cognition. Altogether, these results suggest that the mental representations of the actions involved in creating art are integral to the overall artistic experience of painters, supporting an embodied view of the artists experience of art.

Is there a geometry of time in the human mind? A canonical measure of time in psychology is duration, a time interval quantifiable as a magnitude. Durations have been proposed to be arranged along a mental timeline: a unidimensional, linear, and spatialised representation of time. Here, we asked whether such a mental timeline is sufficient to account for the experience of duration. To address this, we tested the same participants in two experiments: a behavioural similarity judgment task, in which participants rated the similarity of duration pairs, and an electroencephalography (EEG) experiment in which they detected oddball durations in a sequence. Behavioural and EEG data were used to construct representational dissimilarity matrices, whose geometry was compared against theoretical models of duration organisation. Our results reveal that most variance in behavioural similarity judgements is explained by three latent dimensions, interpretable as: magnitude (monotonic ordering of durations), contextual encoding (distance to the geometric mean of the duration set), and a periodic component. These three dimensions are jointly consistent with a latent generalised helical model, which provided excellent fit to the behavioural data. Individual helical model parameters further correlated with endogenous neural oscillations measured during rest, suggesting that an individuals duration space is partially constrained by intrinsic dynamics. The neural geometry was also found to be dynamic, unfolding in two successive stages: a strong logarithmic encoding of durations peaking around 150 ms after duration offset, followed by a spring-like geometry starting around 300 ms after offset. Together, these findings describe multidimensional psychological and neural geometries of duration space, and characterise their relationship.

ObjectiveMagnetophosphenes are visual percepts induced by extremely low-frequency magnetic fields (ELF-MF; <300 Hz), yet their EEG correlates remain poorly characterized and are not reliably captured by classical low-frequency markers. We tested whether magnetophosphene perception is associated with broadband high-frequency EEG changes rather than focal oscillatory effects. ApproachEEG was recorded in N=13 healthy volunteers during 20 Hz sinusoidal magnetic-field exposure delivered using transcranial alternating magnetic stimulation (tAMS) in a global-head configuration. Three conditions were analyzed: no exposure (0 mT), subthreshold (5 mT), and suprathreshold (50 mT). Gamma-band activity (30-80 Hz) was quantified using complementary spectral approaches, including aperiodic-adjusted measures. Main resultsPerception reports sharply dissociated the three conditions, with frequent perception at 50 mT only. Suprathreshold stimulation was associated with spatially distributed increases in gamma-band activity over frontal and occipital electrodes. These effects persisted after aperiodic correction using two independent parameterization methods and did not exhibit a consistent narrowband peak, indicating broadband high-frequency changes. SignificanceMagnetophosphene perception is not reliably captured by focal low-frequency EEG markers but is instead associated with distributed broadband high-frequency activity. These findings challenge standard assumptions derived from classical visual paradigms and suggest that perception under magnetic stimulation reflects large-scale, state-dependent neural dynamics.

Visual perception of symbolic numerals is essential for everyday tasks; however, the neural and perceptual mechanisms underlying this ability remain unclear. Partially occluded digital numerals can elicit bistable perception, and adaptation to symbolic numerals alters the perception of these ambiguous stimuli. We aimed to examine how symbolic numeral adaptation is related to hierarchical visual processing by testing its interocular and interhemifield transfer. Experiment 1 tested interocular transfer by presenting the test stimulus to either the same or opposite eye as the adaptation stimulus. Experiment 2 assessed interhemifield transfer by presenting the test stimulus to either the same or opposite hemifield as the adaptation stimulus. Experiment 3 examined the interhemifield transfer of adaptation confined to the upper parts of digital numerals. Our results showed that adaptation to digital numerals induced shifted perceptual interpretations that transferred across eyes. In addition, we found that adaptation to digital numerals induced a relatively small but statistically significant interhemifield transfer. In contrast, adaptation restricted to the upper parts of digital numerals showed no significant interhemifield transfer. These findings suggest that the perceptual interpretation of symbolic numerals involves visual processing stages that integrate information across the eyes and hemifields.

The sensory content and temporal structure of stimuli have been shown to consistently bias duration perception. Temporal intervals filled with continuous sensory input ("filled intervals"), are often perceived as lasting longer than intervals marked only by their onset and offset ("empty intervals"). Despite this robust behavioral finding, it remains unclear whether filled and empty intervals rely on similar or distinct neural mechanisms and, more generally, how sensory format shapes the neural processing of millisecond time. To address this question, we asked twenty-one healthy participants to reproduce visual durations across different stimulus configurations while high-density scalp EEG was recorded. Behavioral results revealed differences in performance across stimulus configurations. Event-related potentials (ERPs) recorded at occipito-parietal and fronto-central electrodes between 0.1 and 0.4 s after duration offset were modulated in amplitude by both stimulus duration and format. These modulations scaled with the sensory load of the stimulus and its duration, suggesting a common underlying mechanism. A Representational Similarity Analysis (RSA) of the ERP data showed that perceived time was represented more strongly than physical time particularly at occipito-parietal electrodes, but only within the 0.2-0.3 s post-offset window, where stimulus format exerted a pronounced effect on the ERP signal. These findings highlight the role of sensory processing in shaping duration perception and its neural coding, and reveal an early neural signature of perceived time in occipito-parietal electrodes. 1 Significance statementOur perception of subsecond durations is distorted by the sensory content of stimuli. Here, we investigated how stimulus configuration shapes the neural correlates of visual duration perception. Specifically, we asked whether temporal intervals filled with continuous sensory input are processed differently from those lacking such content. We found that, between 0.2 and 0.3 s after interval offset, ERP amplitudes were modulated by stimulus content, and in this same temporal window the EEG signal reflected the perceptual bias. These findings support the view that duration processing and perception are deeply rooted in sensory processing.

As avatars become more commonplace, understanding how the brain processes emotional expressions in virtual faces is critical. We compared behavioral and neural responses to real and virtual faces expressing seven emotions (anger, disgust, fear, joy, sadness, surprise, neutral). In Experiment 1 (n=61), participants rated the similarity between paired faces. Expressions conveying the same emotion were rated as highly similar across face types, whereas mismatched emotions yielded substantially lower similarity ratings, indicating perceived emotional meaning was preserved despite differences in face realism. In Experiment 2 (n=91), functional near-infrared spectroscopy was used to measure brain activity while participants viewed the same stimuli. General-linear-model analyses revealed greater activation limited to visual areas for 1) virtual faces and 2) surprise and neutral expressions. Functional connectivity analyses, however, revealed network level differences between face type and emotion across the brain. Real faces elicited stronger connectivity patterns across frontal, central-temporal, and parietal regions, whereas high-arousal emotions (fear, anger, and joy) were associated with broader network engagement than other expressions. Our results suggest face-type processing occur in early visual areas, and despite perceptual similarity, different emotions on real and virtual faces are associated with distinct patterns of network level connectivity across the brain.

Meditation has been associated with improvements in attention, emotional regulation, and mental well-being, motivating increasing interest in objective methods for assessing meditative states. In this study, we investigate whether EEG-based machine learning can reliably distinguish between multiple meditation styles and mind-wandering states. EEG data were recorded from experienced meditators performing three meditation styles, Shamatha, Vipassana, and Metta, together with an eyes-closed mind-wandering condition. EEG signals were preprocessed to remove artifacts, and features were extracted from frequency, time-frequency, and time domains. Classification was evaluated using both intra-subject and inter-subject strategies with multiple machine learning classifiers. Results demonstrate high intra-subject classification accuracy across meditation-versus-mind-wandering and meditation-style comparisons, indicating strongly discriminative subject-specific neural signatures. In contrast, inter-subject performance decreased substantially, particularly for distinguishing meditation styles, suggesting considerable inter-individual variability in meditation-related EEG patterns. Furthermore, temporal analysis revealed that classification performance increase over time, indicating that the neural distinctions between meditation states become increasingly pronounced over time. Additionally, t-SNE visualization showed clear within-subject clustering but increased overlap across subjects, explaining the reduced inter-subject generalization. Overall, these findings highlight the potential of EEG-based machine learning for personalized assessment and monitoring of meditative states while emphasizing the challenges of developing subject-independent meditation classification systems.

Each individual person looks at natural scenes in their own unique way, resulting in a distinct perceptual experience of the world. However, little is known about why such differences in gaze emerge. Here, we test the hypothesis that idiosyncrasies in gaze behavior are predicted by inter-subject variations in internal models--expectations about how scenes typically look. In two experiments, we first characterized participants personal internal models by asking them to draw typical bathroom and kitchen scenes. Individual differences in these drawings were quantified using an objective deep learning pipeline and, in turn, related to individual differences in gaze behavior. In Experiment 1, where participants freely viewed a set of kitchen and bathroom photographs, inter-subject similarities in internal models did not predict inter-subject similarities in gaze. In Experiment 2, we encouraged strategic exploration through gaze-contingent viewing and a memory task. Here, inter-subject similarities in internal models predicted similarities in fixation frequency and the sequence in which different object categories were inspected. These findings suggest that the influence of internal models on visual exploration is stronger under increased sensory uncertainty and when expectation-guided sampling of the environment is encouraged. Together, our results provide new insights into how individual expectations shape gaze behavior and help explain why people differ in how they explore the visual world.