Peter John Bex

The paper examines mesoscale developmental rivalry in human extrastriate visual cortex by comparing fMRI data from individuals with and without amblyopia, finding that compromised modules are usurped by intact ones.

This study investigates how empathy relates to the structural representation of facial affect by comparing face prototypes generated by participants with different empathy levels.

This study uses a genetic-algorithm face synthesis task to show that depression severity affects the cognitive process of facial affect representation, with At Risk participants showing faster convergence on embarrassment and greater instability in anger representations.

This paper uses AI-generated facial expressions to explore emotion perception, revealing a four-cluster structure and autistic trait associations.

This study uses a novel combination of continuous psychophysical methods and machine learning to analyze perceptual transitions during binocular rivalry, revealing individual variability and new insights into neural processing.

This paper introduces AIM Color Detection and Discrimination, a psychophysical tool for color vision assessment that uses adaptive stimuli and machine learning to classify and quantify color vision deficiency.

The paper uses genetic algorithms to show that context modulates individual differences in facial emotion representations, with some emotions more affected than others.

This study investigates how central vision loss alters internal emotion representations using a genetic algorithm paradigm and three-dimensional face models, finding significant group differences in emotion expression.

The paper evaluates the repeatability and behavioral relationships of vision tests using AIM and FInD paradigms on a tablet-based tool, finding bias-free results for most tests and clustering of CSF, form, and motion outcomes.

This study finds reduced scene-selective activity in the posterior intraparietal gyrus (PIGS) in amblyopic adults compared to controls, while other scene-processing areas remain unaffected.

This study uses high-resolution fMRI to show that strabismus and anisometropia affect ocular dominance responses differently in the human visual cortex.

This study shows that visual attention operates in real-world coordinates, with high precision and minimal disruption during eye movements.

This study shows that large depth differences between targets and flankers increase crowding, contradicting previous findings with small depth differences.

This study introduces AIM-VA, a vision assessment method, and compares its ability to detect defocus and astigmatism with ETDRS, finding greater sensitivity to astigmatism and comparable repeatability.

The paper uses high-resolution fMRI to show two interdigitated channels in human extrastriate cortex for motion and stereopsis processing, consistent across stimuli and with strong intra-channel connectivity.

This study investigates how head tilt affects stereoacuity using different stimuli, finding that stereoacuity remains stable with sparse stimuli but decreases with noise stimuli.

The paper tests the hypothesis that target detection in natural images is inversely related to spatial similarity with the background, finding that high similarity increases detectability due to phase alignment.

The paper models how the human visual system processes binocular disparity across spatial scales and the visual field, showing foveal sensitivity to fine disparities and peripheral sensitivity to coarse disparities, with an optimal integration of information.

This study investigates whether voluntary attention modulates perceptual lightness filling-in using a modified Kanizsa illusory triangle.

This study shows that motor signals improve gaze tracking accuracy in both horizontal and depth directions, even with simulated visual impairments.

This study investigates visual crowding by analyzing positional uncertainty, source confusion, and featural averaging through a hybrid adjustment method and modeling.