Biology subjects

Bex, P. J.

Publications and source records attributed to Bex, P. J..

17 recordsLinked to original sources

bioRxiv2026

Empathy and the Structural Representation of Facial Affect: Evidence from a Genetic-Algorithm Face Synthesis Task

Empathy has been linked to facial emotion recognition, but whether empathy is associated with the structural representation of facial affect (how observers position different affects relative to one another in face-shape space) remains largely unexplored. 53 adults completed a genetic-algorithm face task that generated prototypes for 13 affects using the Basel Face Model, and completed the 60-item Empathy Quotient (EQ). The genetic-algorithm task produced structurally distinct prototypes for all 13 affects (all paired tests p < .001 Bonferroni-corrected; Cohens dz 1.74-3.13), confirming that participants generated reliable, affect-specific face representations. A 13 x 13 between-affect distance matrix was then compared between higher-EQ (n = 30) and lower-EQ (n = 23) groups. 1 pair survived full correction across all 156 off-diagonal cells: Amusement x Contempt (Cohens d = -1.31), with higher-empathy participants representing these two affects as structurally closer to each other. Both amusement and contempt are social-evaluative affects that share overlapping facial action components, and this convergence may reflect heightened sensitivity to shared expressive structure among higher-empathy observers. In exploratory analyses, permutation testing and continuous-EQ correlations pointed to a broader pattern centered on social-evaluative affects (Amusement, Awe, Contempt, Fear, Happiness, Pride, Sadness, Interest). Individual differences in empathy appear most prominently associated with how social-evaluative affects are structurally positioned in face-shape space, suggesting that empathy modulates not just emotion recognition accuracy but the representational geometry of facial affect itself.

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bioRxiv2026

Depression Severity Modulates the Cognitive Process of Facial Affect Representation: Evidence from a Genetic-Algorithm Face Synthesis Task

Depression is associated with biased facial emotion processing, yet existing paradigms measure only the recognition of pre-selected stimuli, conflating the process of forming an internal representation with its endpoint product. Here, we used a genetic-algorithm (GA) face synthesis task to disentangle these components. Fifty-seven undergraduates (40 Low Risk, 17 At Risk by Beck Depression Inventory-II) iteratively evolved photorealistic 3D faces to match their internal representations of 13 emotions across seven generations in a 199-dimensional face shape space. We extracted five evolutionary metrics capturing how participants constructed their representations (convergence speed, velocity, stability, range) and the structure they ultimately produced (peak intensity). At Risk participants converged on embarrassment representations significantly faster than Low Risk participants (d = 0.88, p = .001, FDR-corrected, permutation-validated), reaching their template in roughly half the number of generations. Anger representations showed greater evolutionary instability in the At Risk group (d = -0.75, p = .029, permutation-validated). Critically, endpoint face intensities did not differ between groups for any emotion. These results suggest that depression severity is associated with rigid self-conscious emotion schemas and unstable anger representations during face generation, reflecting altered cognitive processes rather than distorted perceptual products. The findings extend cognitive schema theory to the domain of facial affect representation and highlight self-conscious emotions as an underexplored locus of depression-related perceptual bias.

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bioRxiv2026

Beyond forced choice: hyper-realistic AI faces reveal a four-cluster perceptual geometry of emotion

Forced-choice paradigms in facial emotion perception research require observers to commit to a single label and discard any simultaneous activation of related categories that participants might otherwise express. We introduce a multi-select rating paradigm in which 112 participants rated each of 52 facial-expression stimuli on 13 emotion categories using continuous 0-to-10 sliders, alongside a separate authenticity slider. Stimuli were generated using OpenAIs DALL-E 3 from an orthogonal four-factor design (emotion, race, gender, age), allowing demographic balance and compositional uniformity more readily than photograph-based stimulus sets permit. Linear mixed-effects models with participant random intercepts and logistic regression with cluster-robust standard errors were applied to 5,824 trials. Perceived authenticity reliably predicted agreement between the participants top-rated category and the AI-prompted target emotion (odds ratio 1.03 per +1 unit, p < .001), and a principal-components analysis of the 13-emotion rating matrix recovered three interpretable dimensions accounting for over half of trial-level variance, with the first two corresponding to the canonical valence and arousal axes. Hierarchical clustering exposed a tight cluster of self-conscious negative emotions (sadness, embarrassment, shame) that does not align with the canonical basic-versus-complex emotion distinction. Collapsing the participants top-rated emotion to its cluster raised the trial-level prompt-agreement rate from 43.1% to 86.9% ({Delta} = +43.8 percentage points), indicating that participants most common departures from the prompted target fell within rather than across clusters. Among Autism-Spectrum Quotient subscales, the Social-Skill subscale showed a robust interaction with contempt-target faces (p < .001), with higher Social-Skill scores predicting elevated contempt ratings of approximately 1.2 points on the 0-to-10 scale. Two further secondary patterns emerged in the AQ-subscale-by-emotion grid, including an opposing-direction effect of Imagination and Attention-to-Detail subscales on awe ratings. We acknowledge that some of the recovered structure may partly reflect statistical regularities of the AI-generation pipeline rather than human perceptual geometry alone, and we discuss this caveat at length below. Multi-select rating with hyper-realistic AI-generated stimuli produces a richer perceptual probe than the forced-choice paradigms that have dominated this literature, and reveals subscale-level autistic-trait associations that AQ-total analyses obscure.

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bioRxiv2025

The Contextual Affects of Facial Expression

Affect recognition and communication are critical for everyday social interaction. Traditional emotion research has often assumed that facial expressions reliably reflect internal emotional states and conform to a set of universal expressions. However, emerging evidence suggests that facial expressions are highly individualized and influenced by context. Recent work using genetic algorithms (GAs) has revealed profound individual differences in internal representations of emotion, but these studies have not examined how contextual information modulates such representations. To investigate the joint effects of context and individual differences, we used GAs to enable 12 participants to generate personalized facial expressions matching their subjective interpretation of affect within written contextual scenarios. Standardized scenarios drawn from Howard Schatzs Actors Acting were independently rated across 13 primary emotions. In the MAX condition, each primary emotion was paired with a scenario maximizing a secondary emotion; in the MIN condition, the secondary emotion was minimized; in the WORD condition, participants selected faces based on emotion words alone. Faces were generated within the 199-dimensional shape coefficient space of the Basel Face Database across 6 generations per trial. We found a significant main effect of condition on selection rate (p < .001), with participants selecting more faces under contextual conditions than under WORD. Critically, context differentially modulated specific emotions: Embarrassment, Surprise, and Disgust showed large context effects (all p < .001), whereas Sadness, Awe, and Anger did not. Cosine distance analysis confirmed that face clusters were emotion-specific (d = -7.88) and that their separation varied with context. The GA showed robust convergence across generations (d = 0.61). Strong individual differences were observed (2 = .229), with low inter-participant agreement (mean r = .06). These results support constructionist models of emotion by demonstrating that facial expression representations are context-dependent, with context selectively modulating certain emotions more than others.

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bioRxiv2025

The Affects of Central Vision Loss on Emotion Perception

Central vision loss (CVL) from age-related macular degeneration (AMD) profoundly impacts daily life. While much research focuses on visual discrimination and reading, understanding how CVL affects emotional perception remains unexplored. We adapted the genetic-algorithm face paradigm introduced by Carlisi et al. (2021) and extended by Binetti et al. (2022), combining it with a three-dimensional morphable face model, to investigate how healthy young, healthy older, and CVL-affected individuals internally represent facial emotions. Participants evolved faces they perceived to best express 13 distinct emotions (or 4 for the older healthy group). Using a three-cohort design, we separated age effects from CVL-specific effects. Results revealed four significant group differences: Awe Convergence (H = 10.97, p = 0.001), Shame Intensity (H = 10.04, p = 0.005), Interest Range (H = 6.35, p = 0.016), and Interest Stability (H = 4.86, p = 0.026). Additionally, cosine similarity analysis in 199-dimensional face space showed cohorts use fundamentally different facial feature configurations (mean cosine {approx}0.006 for YNG vs CVL), suggesting CVL may reorganize emotion representations rather than simply scaling them. These preliminary findings raise questions about whether all emotions require uniform amplification in CVL and point toward the potential value of selective rehabilitation over broad caricaturing approaches.

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bioRxiv2025

Investigating the repeatability and behavioral relationships of acuity, contrast sensitivity, form, and motion perception measurements using a novel tablet-based vision test tool

Visual function tests are important in basic and clinical vision research but are typically limited to very few aspects of human vision, coarse diagnostic resolution, and require an administrator. Recently, the generalizable, response-adaptive, self-administered Angular Indication Measurement (AIM) and Foraging Interactive D-prime (FInD) methods were developed to assess vision across different visual functions. The AIM and FInD paradigms show a range of visual stimuli per display (4x4 stimuli) spanning {+/-}2{sigma} around an adaptively estimated perceptual threshold across multiple displays. Here, we investigated the repeatability and behavioral relationships of the AIM and FInD paradigms for near visual acuity, contrast sensitivity function (CSF), form, and motion coherence threshold measurements using a novel tablet-based vision test tool. 31 healthy participants were recruited and completed two repetitions of each experiment in random order. Bland-Altman analyses were performed to calculate the Coefficient of Repeatability (precision) and Mean Bias (accuracy). Linear regressions and hierarchical cluster analysis were used to investigate the relationship between outcome parameters. Results show that AIM Form coherence and FInD Form horizontal coherence showed significant retest bias; all other tests were bias-free. Cluster analysis revealed overall clustering of CSF, form and motion outcomes. We further show significant correlations within CSF and between motion coherence outcomes but few significant correlations between form coherence outcomes. AIM and FInD near vision tests are generalizable across multiple visual functions and are precise and reliable. Most functions tested were bias-free. CSF, form, and motion outcomes clustered together, and CSF and motion outcomes correlated with one another. The combination of a generalizable, response-adaptive, and self-administered approach may be a suitable set of tests for basic science and clinical use cases.

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bioRxiv2024

Novel color vision assessment tool: AIM Color Detection and Discrimination

Color vision assessment is essential in clinical practice, yet different tests exhibit distinct strengths and limitations. Here we apply a psychophysical paradigm, Angular Indication Measurement (AIM) for color detection and discrimination. AIM is designed to address some of the shortcomings of existing tests, such as prolonged testing time, limited accuracy and sensitivity, and the necessity for clinician oversight. AIM presents adaptively generated charts, each a NxM (here 4x4) grid of stimuli, and participants are instructed to indicate either the orientation of the gap in a cone-isolating Landolt C optotype or the orientation of the edge between two colors in an equiluminant color space. The contrasts or color differences of the stimuli are adaptively selected for each chart based on performance of prior AIM charts. In a group of 23 color-normal and 15 people with color vision deficiency (CVD), we validate AIM color against Hardy-Rand-Rittler (HRR), Farnsworth-Munsell 100 hue test (FM100), and anomaloscope color matching diagnosis and use machine learning techniques to classify the type and severity of CVD. The results show that AIM has classification accuracies comparable to that of the anomaloscope, and while HRR and FM100 are less accurate than AIM and an anomaloscope, HRR is very rapid. We conclude that AIM is a computer-based, self-administered, response-adaptive and rapid tool with high test-retest repeatability that has the potential to be suitable for both clinical and research applications.

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bioRxiv2024

Which perceptual categories do observers experience during multistable perception?

Multistable perceptual phenomena provide insights into the minds dynamic states within a stable external environment and the neural underpinnings of these consciousness changes are often studied with binocular rivalry. Conventional methods to study binocular rivalry suffer from biases and assumptions that limit their ability to describe the continuous nature of this perceptual transitions and to discover what kind of percept was perceived across time. In this study, we propose a novel way to avoid those shortcomings by combining a continuous psychophysical method that estimates introspection during binocular rivalry with machine learning clustering and transition probability analysis. This combination of techniques reveals individual variability and complexity of perceptual experience in 28 normally sighted participants. Also, the analysis of transition probabilities between perceptual categories, i.e., exclusive and different kinds of mixed percepts, suggest that interocular perceptual competition, triggered by low-level stimuli, involves conflict between monocular and binocular neural processing sites rather than mutual inhibition of monocular sites. Layman abstractWhen our brain receives ambiguous information about the world, it changes its interpretation between different alternatives and thereby provides insight into how the mind works. Scientists often use a technique called binocular rivalry, where each eye sees a different image, to provoke an ambiguous visual world that is perceived as ongoing competition among interpretations of the two eyes inputs. Traditional methods for studying binocular rivalry struggle to describe the continuous nature of this fluctuation and to estimate the range of different perceived experiences. We have created a new approach in which participants reproduce their ongoing perceptual experiences combined machine learning analyses of these states. We found that individuals visual experience is more varied and complex than previously thought. Our results suggest that when our eyes see conflicting images, the brains effort to make sense of what is seen involves syntheses among both monocular and binocular brain areas, not just competition between monocular areas.

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bioRxiv2023

A computational account of real-world attentional allocation based on visual gain fields

Coordination of goal-directed behaviour depends on the brains ability to recover the locations of relevant objects in the world. In humans, the visual system encodes the spatial organisation of sensory inputs, but neurons in early visual areas map objects according to their retinal positions, rather than where they are in the world. How the brain computes world-referenced spatial information across eye movements has been widely researched and debated. Here we tested whether shifts of covert attention are sufficiently precise in space and time to track an objects real-world location across eye movements. We found that observers attentional selectivity is remarkably precise, and is barely perturbed by the execution of saccades. Inspired by recent neurophysiological discoveries, we developed an observer model that rapidly estimates the real-world locations of objects and allocates attention within this reference frame. The model recapitulates the human data and provides a parsimonious explanation for previously reported phenomena in which observers allocate attention to task-irrelevant locations across eye movements. Our findings reveal that visual attention operates in real-world coordinates, which can be computed rapidly at the earliest stages of cortical processing.

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bioRxiv2023

AIM (Angular Indication Measurement) paradigm: Adaptive, self-administered, and generalizable vision assessment used to measure visual acuity

This proof-of-concept study introduces Angular Indication Measurement and applies it to VA (AIM-VA). First, we compared the ability of AIM-VA and ETDRS to detect defocus and astigmatic blur in 22 normally-sighted adults. Spherical and cylindrical lenses ({+/-}0.00D, +0.25D, +0.50D, +0.75D, +1.00D, +2.00D and +0.50D, +1.00D, +2.00D each at 0{degrees}, 90{degrees}, 135{degrees}, respectively) in the dominant eye induced blur. Second, we compared repeatability over two tests of AIM-VA and ETDRS. A 2-way-ANOVA showed a main effect for defocus-blur and test with no interaction. A 3-way-ANOVA for the astigmatism experiment revealed main effects for test type, blur, and direction and with no interactions. Planned multiple comparisons showed AIM had greater astigmatic-induced VA loss than ETDRS. Bland-Altman plots showed small bias and no systematic learning effect for either test type and improved repeatability with >2 adaptive steps for AIM-VA. AIM-VAs ability to detect defocus was comparable with that of an ETDRS letter chart and showed greater sensitivity to astigmatic blur, and AIM-VAs repeatability is comparable with ETDRS when using 2 or more adaptive steps. AIMs self-administered orientation judgment approach is generalizable to interrogate other visual functions, e.g., contrast, color, motion, stereo-vision.

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bioRxiv2022

Effect of depth on crowding investigated with a multi-depth plane display

Crowding occurs when the presence of nearby features causes highly visible objects to become unrecognizable. Although crowding has implications for many everyday tasks and the tremendous amounts of research reflect its importance, surprisingly little is known about how depth affects crowding. Most available studies show that stereoscopic disparity reduces crowding, indicating that crowding may be relatively unimportant in three-dimensional environments. However, most previous studies tested only small stereoscopic differences in depth in which disparity, defocus blur, and accommodation are inconsistent with the real world. Using a novel multi-depth plane display, this study investigated how large (0.54 - 2.25 diopters), real differences in target-flanker depth, representative of those experienced between many objects in the real world, affect crowding. Our findings show that large differences in target-flanker depth increased crowding in the majority of observers, contrary to previous work showing reduced crowding in the presence of small depth differences. Furthermore, when the target was at fixation depth, crowding was generally more pronounced when the flankers were behind the target as opposed to in front of it. However, when the flankers were at fixation depth, crowding was generally more pronounced when the target was behind the flankers. These findings suggest that crowding from clutter outside the limits of binocular fusion can still have a significant impact on object recognition and visual perception in the peripheral field.

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bioRxiv2022

Stimulus-dependent depth constancy during head tilt

Stereopsis is traditionally measured with noise-based stereo tests while the observer views the test in primary gaze. We investigated the effect of stimulus sparseness and axial variations of interocular disparity induced via head rotations. First, we measured stereoacuity using a 4-Alternative-Forced-Choice (4-AFC) task with three uncrossed and one crossed disparity bandpass-filtered circles on a passive-3-D-monitor. Ten binocularly-normal adults fixated a central cross and clicked on the circle withcrossed disparity for forty trials/condition. Observers adopted head tilts of 0{degrees} or {+/-}20{degrees} pitch, roll, or yaw, enforced with an innertial measurement unit and fixation enforced with an eye tracker. Next, we measured stereoacuity in 8 adults while either the head (H), monitor (M), or both (B) were tilted 0{degrees}, {+/-}22.5{degrees}, or {+/-}45{degrees} roll in random order (eighty trials/condition) using a 4-AFC task and random-dot stimuli. Head tilts did not signifcantly alter stereoacuity using narrow-band stimuli(p>0.05), despite that IPDs and the axis of disparity were differentially affected by the tilts. However, for random dot stimuli, stereoacuity decreased with increasing orientation difference between the head and monitor (H and M: p<0.05; B: p>0.05]. Head tilt decreases IPD and rotates the axis of interocular disparity, however, these manipulations affect stereoacuity when measured with noise stimuli but not with sparse stimuli. The results are consistent with a vestibular input to stereoscopic disparity processing that can be detected by sparse stimuli but is masked by dense stimuli. The results have implications for natural vision and for clinical screening in patients with abnormal head posture. Significance statementDepth perception is a critical feature of human vision and it is thought that the ability to perceive stereoscopic depth is bound to an essentially eye-fixed, horizontal disparity of each image that rapidly deteriorates away from that limited horizontal axis. In a set of head tilt experiments, we varied the orientations of stereoscopic images and demonstrate that stereoacuity remains constant when deploying sparse narrow-band stimuli, and only worsens when using fine-detailed noise stimuli that mask off-axis disparities. These results shine new light upon the debate of neuroplasticity of stereo vision. Moreover, the results are consequential for diagnosis and treatment in people with atypical head- and eye alignment, such as for patients with torticollis or strabismus.

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bioRxiv2021

Spatial structure, phase, and the contrast of natural images

The sensitivity of the human visual system is thought to be shaped by environmental statistics. A major endeavour in vision science, therefore, is to uncover the image statistics that predict perceptual and cognitive function. When searching for targets in natural images, for example, it has recently been proposed that target detection is inversely related to the spatial similarity of the target to its local background. We tested this hypothesis by measuring observers sensitivity to targets that were blended with natural image backgrounds. Targets were designed to have a spatial structure that was either similar or dissimilar to the background. Contrary to masking from similarity, we found that observers were most sensitive to targets that were most similar to their backgrounds. We hypothesised that a coincidence of phase-alignment between target and background results in a local contrast signal that facilitates detection when target-background similarity is high. We confirmed this prediction in a second experiment. Indeed, we show that, by solely manipulating the phase of a target relative to its background, the target can be rendered easily visible or undetectable. Our study thus reveals that, in addition to its structural similarity, the phase of the target relative to the background must be considered when predicting detection sensitivity in natural images.

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bioRxiv2019

Near-optimal combination of disparity across a log-polar scaled visual field

The human visual system is foveated: we can see fine spatial details in central vision, whereas resolution is poor in our peripheral visual field, and this loss of resolution follows an approximately logarithmic decrease. Additionally, our brain organizes visual input in polar coordinates. Therefore, the image projection occurring between retina and primary visual cortex can be mathematically described by the log-polar transform. Here, we test and model how this space-variant visual processing affects how we process binocular disparity, a key component of human depth perception. We observe that the fovea preferentially processes disparities at fine spatial scales, whereas the visual periphery is tuned for coarse spatial scales, in line with the naturally occurring distributions of depths and disparities in the real-world. We further show that the visual field integrates disparity information across the visual field, in a near-optimal fashion. We develop a foveated, log-polar model that mimics the processing of depth information in primary visual cortex and that can process disparity directly in the cortical domain representation. This model takes real images as input and recreates the observed topography of disparity sensitivity in man. Our findings support the notion that our foveated, binocular visual system has been moulded by the statistics of our visual environment.\n\nAuthor summaryWe investigate how humans perceive depth from binocular disparity at different spatial scales and across different regions of the visual field. We show that small changes in disparity-defined depth are detected best in central vision, whereas peripheral vision best captures the coarser structure of the environment. We also demonstrate that depth information extracted from different regions of the visual field is combined into a unified depth percept. We then construct an image-computable model of disparity processing that takes into account how our brain organizes the visual input at our retinae. The model operates directly in cortical image space, and neatly accounts for human depth perception across the visual field.

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bioRxiv2017

Three-Dimensional Binocular Eye-Hand Coordination in Normal Vision and with Simulated Visual Impairment

Sensorimotor coupling in healthy humans is demonstrated by the higher accuracy of visually tracking intrinsically-rather than extrinsically-generated hand movements in the fronto-parallel plane. It is unknown whether this coupling also facilitates vergence eye movements for tracking objects in depth, or can overcome symmetric or asymmetric binocular visual impairments. Human observers were therefore asked to track with their gaze a target moving horizontally or in depth. The movement of the target was either directly controlled by the observer's hand or followed hand movements executed by the observer in a previous trial. Visual impairments were simulated by blurring stimuli independently in each eye. Accuracy was higher for self-generated movements in all conditions, demonstrating that motor signals are employed by the oculomotor system to improve the accuracy of vergence as well as horizontal eye movements. Asymmetric monocular blur affected horizontal tracking less than symmetric binocular blur, but impaired tracking in depth as much as binocular blur. There was a critical blur level up to which pursuit and vergence eye movements maintained tracking accuracy independent of blur level. Hand-eye coordination may therefore help compensate for functional deficits associated with eye disease and may be employed to augment visual impairment rehabilitation.

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bioRxiv2017

Selective attention modulates surface filling-in

The visual system is required to compute objects from partial image structure so that figures can be segmented from their backgrounds. Although early clinical, behavioral, and modeling data suggested that such computations are performed pre-attentively, recent neurophysiological evidence suggests that surface filling-in is influenced by attention. In the present study we developed a variant of the classical Kanizsa illusory triangle to investigate whether voluntary attention modulates perceptual filling-in. Our figure consists of \"pacmen\" positioned at the tips of an illusory 6-point star and alternating in polarity such that two illusory triangles are implied to compete with one another within the figure. On each trial, observers were cued to attend to only one triangle, and then compared its lightness with a matching texture-defined triangle. We found that perceived lightness of the illusory shape depended on the polarity of pacmen framing the attended triangle, although the magnitude of this effect was weaker than when all inducers were of the same polarity. Our findings thus reveal that voluntary attention can influence lightness filling-in, and provide important data linking neurophysiological effects to phenomenology.

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bioRxiv2016

Visual crowding is a combination of an increase of positional uncertainty, source confusion, and featural averaging

Although we perceive a richly detailed visual world, our ability to identify 1 individual objects is severely limited in clutter, particularly in peripheral vision. Models of such crowding have generally been driven by the phenomenological misidentifications of crowded targets: using stimuli that do not easily combine to form a unique symbol (e.g. letters or objects), observers typically confuse the source of objects and report either the target or a distractor, but when continuous features are used (e.g. orientated gratings or line positions) observers report a feature somewhere between the target and distractor. To reconcile these accounts, we develop a hybrid method of adjustment that allows detailed analysis of these multiple error categories. Observers reported the orientation of a target, under several distractor conditions, by adjusting an identical foveal target. We apply new modelling to quantify whether perceptual reports show evidence of positional uncertainty, source confusion, and featural averaging on a trial-by-trial basis. Our results show that observers make a large proportion of source-confusion errors. However, our study also reveals the distribution of perceptual reports that underlie performance in this crowding task more generally: aggregate errors cannot be neatly labelled because they are heterogeneous and their structure depends on target-distractor distance.

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