Biology subjects

Burge, J.

Publications and source records attributed to Burge, J..

At least 19 recordsLinked to original sources

bioRxiv2025

Monovision-induced motion illusions in presbyopic and non-presbyopic populations

Monovision is a common correction for presbyopia that focuses one eye at far distances and the other at near distances, resulting in an interocular difference in blur between the eyes. Because blur increases the speed of visual processing by a few milliseconds, these optical conditions can induce dramatic misperceptions of the distances and 3D directions of moving objects. To date, however, the illusion has been demonstrated in only non-presbyopic individuals. We analyze the prevalence of both the processing speed differences and the visibility of the resulting illusions in the presbyopic and general populations.17 presbyopes (54.4{+/-}5.9years) and 36 non-presbyopes (22.2{+/-}5.0years) participated. The proportions of these participant populations approximately match their proportions in the general population. Two strips of horizontally moving bars were presented on an autostereoscopic display with interocular blur and light-level differences. The task was to report which strip appeared closer in depth. Blur- and light-level differences caused illusions that are respectively known as the reverse and classic Pulfrich effects. Interocular delay and an illusion visibility index--the ratio of interocular delay and the detection threshold--were obtained from each participant for both blur and light-level differences between the eyes. Blur- and light-level differences cause highly significant changes in processing speed at the individual and group levels. (The two populations were statistically indistinguishable in their susceptibility to stimulus-induced processing speed differences.) The reverse and classic Pulfrich effects occurred in 94% and in 96%, respectively, of the general participant population. The visibility index showed that the processing speed discrepancy exceeded the detection threshold in a smaller number of participants--30% and 43%, respectively. Interocular differences in optical blur reliably cause interocular differences in processing speed across presbyopic and non-presbyopic populations, although they create visible (suprathreshold) illusions in only a subset of participants. However, this subset included individuals with processing delays that were many times larger than the detection threshold. These latter participants are likely to be afflicted by large, highly visible illusions in real-world conditions. Methods for reducing or eliminating these illusions are discussed.+

neuroscience↗

bioRxiv2024

Feature-specific divisive normalization improves natural image encoding for depth perception

Vision science and visual neuroscience seek to understand how stimulus and sensor properties limit the precision with which behaviorally-relevant latent variables are encoded and decoded. In the primate visual system, binocular disparity--the canonical cue for stereo-depth perception--is initially encoded by a set of binocular receptive fields with a range of spatial frequency preferences. Here, with a stereo-image database having ground-truth disparity information at each pixel, we examine how response normalization and receptive field properties determine the fidelity with which binocular disparity is encoded in natural scenes. We quantify encoding fidelity by computing the Fisher information carried by the normalized receptive field responses. Several findings emerge from an analysis of the response statistics. First, broadband (or feature-unspecific) normalization yields Laplace-distributed receptive field responses, and narrowband (or feature-specific) normalization yields Gaussian-distributed receptive field responses. Second, the Fisher information in narrowband-normalized responses is larger than in broadband-normalized responses by a scale factor that grows with population size. Third, the most useful spatial frequency decreases with stimulus size and the range of spatial frequencies that is useful for encoding a given disparity decreases with disparity magnitude, consistent with neurophysiological findings. Fourth, the predicted patterns of psychophysical performance, and absolute detection threshold, match human performance with natural and artificial stimuli. The current computational efforts establish a new functional role for response normalization, and bring us closer to understanding the principles that should govern the design of neural systems that support perception in natural scenes.

neuroscience↗

bioRxiv2024

Optimal motion-in-depth estimation with natural stimuli

Estimating the motion of objects in depth is important for behavior, and is strongly supported by binocular visual cues. To understand both how the brain should estimate motion in depth and how natural constraints shape and limit performance, we develop image-computable ideal observer models from naturalistic binocular video clips of two 3D motion tasks. The observers spatio-temporally filter the videos, and non-linearly decode 3D motion from the filter responses. The optimal filters and decoder are dictated by the task-relevant natural image statistics, and are specific to each task. Multiple findings emerge. First, two distinct filter types are spontaneously learned for each task. For 3D speed estimation, filters emerge for processing either changing disparities over time (CDOT) or interocular velocity differences (IOVD), cues used by humans. For 3D direction estimation, filters emerge for discriminating either left-right or towards-away motion. Second, the filter responses, conditioned on the latent variable, are well-described as jointly Gaussian, and the covariance of the filter responses carries the information about the task-relevant latent variable. Quadratic combination is thus necessary for optimal decoding, which can be implemented by biologically plausible neural computations. Finally, the ideal observer yields non-obvious-and in some cases counter-intuitive-patterns of performance like those exhibited by humans. Important characteristics of human 3D motion processing and estimation may therefore result from optimal information processing in the early visual system. Significance statementHumans and other animals extract and process features of natural images that are useful for estimating motion-in-depth, an ability that is crucial for successful interaction with the environment. But the enormous diversity of natural visual inputs that are consistent with a given 3D motion-natural stimulus variability-presents a challenging computational problem. The neural populations that support the estimation of motion-in-depth are under active investigation. Here, we study how to optimally estimate local 3D motion with naturalistic stimulus variability. We show that the optimal computations are biologically plausible, and that they reproduce sometimes counterintuitive performance patterns independently reported in the human psychophysical literature. Novel testable hypotheses for future neurophysiological and psychophysical research are discussed.

neuroscience↗

bioRxiv2024

Temporal dynamics of human color processing measured using a continuous tracking task

We characterized the temporal dynamics of color processing using a continuous tracking paradigm by estimating temporal impulse response functions associated with tracking chromatic Gabor patches. We measured how the lag of these functions changes as a function of chromatic direction and contrast for stimuli in the LS cone contrast plane. In the same set of subjects, we also measured detection thresholds for stimuli with matched spatial, temporal, and chromatic properties. We created a model of tracking and detection performance to test if a common representation of chromatic contrast accounts for both measures. The model summarizes the effect of chromatic contrast over different chromatic directions through elliptical isoresponse contours, the shapes of which are contrast independent. The fitted elliptical isoresponse contours have essentially the same orientation in the detection and tracking tasks. For the tracking task, however, there is a striking reduction in sensitivity to signals originating in the S cones. The results are consistent with common chromatic mechanisms mediating performance on the two tasks, but with task-dependent relative weighting of signals from L and S cones.

neuroscience↗

bioRxiv2024

Sources of uncertainty in human stereo-depth perception in natural images and scenes

2Stimulus variability--a form of nuisance variability--is a primary source of perceptual uncertainty in every-day natural tasks. How do different properties of natural images and scenes contribute to this uncertainty? Using binocular disparity as a model system, we report a systematic investigation of how various forms of natural stimulus variability impact performance in a stereo-depth discrimination task. With stimuli sampled from a stereo-image database of real-world scenes having pixel-by-pixel ground-truth distance data, three human observers completed two closely related double-pass psychophysical experiments. In the two experiments, each human observer responded twice to ten thousand unique trials, in which twenty thousand unique stimuli were presented. New analytical methods reveal, from this data, the specific and nearly dissociable effects of two distinct sources of natural stimulus variability--variation in luminance-contrast patterns and variation in local-depth structure--on discrimination performance, as well as the relative importance of stimulus-driven-variability and internal-noise in determining performance limits. Between-observer analyses show that both stimulus-driven sources of uncertainty are responsible for a large proportion of total variance, have strikingly similar effects on different people, and--surprisingly--make stimulus-by-stimulus responses more predictable (not less). The consistency across observers raises the intriguing prospect that image-computable models can make reasonably accurate performance predictions in natural viewing. Overall, the findings provide a rich picture of stimulus factors that contribute to human perceptual performance in natural scenes. The approach should have broad application to other animal models and other sensory-perceptual tasks with natural or naturalistic stimuli. 1 SignificanceLinking properties of the external world, and of sensory stimuli, to how neurons and animals respond has proven an important approach to understanding how the brain works. Much is known about how nervous systems respond to simple stimuli. Less is known about how systems respond during real-world viewing. Using data from two human stereo-depth discrimination experiments, we develop a new approach that reveals how distinct features of natural scenes and images contribute to perceptual performance. Results show that stimulus-by-stimulus variation has highly consistent effects on different people. The approach should have broad application to other animal models and other sensory-perceptual tasks.

neuroscience↗

bioRxiv2023

Eccentricity strongly modulates visual processing delays

The temporal dynamics of visual information processing varies with the stimulus being processed and with the retinal location that initiates the processing. Here, we present psychophysical data with sub-millisecond precision showing that increasing eccentricity decreases the delay with which stimuli are processed. We show that, even within the central +/-6{o} of the visual field, processing delays change by a factor of up to three times. A simple model, grounded in retinal physiology, provides a good account of the data. The relative delays are on the order of only milliseconds. But if later processing leaves the delays unresolved, they can cause dramatic misperceptions of motion and 3D layout. We discuss the implications for how the human visual system solves the temporal binding problem across eccentricity. The results highlight the severe computational challenge of obtaining accurate, temporally-unified percepts of the environment with spatiotemporally-staggered processing across the visual field.

neuroscience↗

bioRxiv2023

The impact of overall light-level on the reverse Pulfrich effect

The Pulfrich Effect is an illusion characterized by the misperception of the depth and 3D direction of moving objects. Interocular luminance differences cause the Classic Pulfrich effect; the darker image is processed more slowly. Interocular blur differences cause the Reverse Pulfrich effect; the blurrier image is processed more quickly. A common correction for presbyopia--monovision--intentionally induces the optical conditions that cause the Reverse Pulfrich Effect. The effect sizes, and the fact that tens of millions of people wear these corrections every day, raise concerns about public safety. However, although the impact of overall light-level (e.g., nighttime vs. daytime) on the Classic Pulfrich effect has been well-characterized, its impact on the Reverse Pulfrich effect is unknown. Here, using a custom binocular 4f tunable lens optical system that allows the decoupling of retinal illuminance and retinal blur, we report how the Classic and Reverse Pulfrich effects scale with overall light-level. Both effects increase logarithmically with decreases in light-level. These results motivate a characterization of how light level interacts with other optical factors (e.g., higher-order aberrations) that are likely to impact the Reverse Pulfrich effect, and hence the perceptual consequences of monovision corrections. Commercial disclosureV. Rodriguez Lopez: None; B. Chin: None; J. Burge: None.

neuroscience↗

bioRxiv2022

Perceptual consequences of interocular imbalances in the duration of temporal integration

Temporal differences in visual information processing between the eyes can cause dramatic misperceptions of motion and depth. Processing delays between the eyes cause the Pulfrich effect: oscillating targets in the frontal plane are misperceived as moving along near-elliptical motion trajectories in depth (Pulfrich, 1922). Here, we explain a previously reported but poorly understood variant: the anomalous Pulfrich effect. When this variant is perceived, the illusory motion trajectory appears oriented left- or right-side back in depth, rather than aligned with the true direction of motion. Our data indicate that this perceived misalignment is due to interocular differences in neural temporal integration periods, as opposed to interocular differences in delay. For oscillating motion, differences in the duration of temporal integration dampen the effective motion amplitude in one eye relative to the other. In a dynamic analog of the Geometric effect in stereo-surface-orientation perception (Ogle, 1950), the different motion amplitudes cause the perceived misorientation of the motion trajectories. Forced-choice psychophysical experiments, conducted with either different spatial frequencies and/or different onscreen motion damping in the two eyes, show that the perceived misorientation in depth is associated with the eye having greater motion damping. A target-tracking experiment provided more direct evidence that the anomalous Pulfrich effect is caused by interocular differences in temporal integration and delay. These findings highlight the computational hurdles posed to the visual system by temporal differences in sensory processing. Future work will explore how the visual system overcomes these challenges to achieve accurate perception.

neuroscience↗

bioRxiv2021

Equivalent noise characterization of human lightness constancy

A goal of visual perception is to provide stable representations of task-relevant scene properties (e.g. object reflectance) despite variation in task-irrelevant scene properties (e.g. illumination, reflectance of other nearby objects). To study such stability in the context of the perceptual representation of lightness, we introduce a threshold-based psychophysical paradigm. We measure how thresholds for discriminating the achromatic reflectance of a target object (task-relevant property) in rendered naturalistic scenes are impacted by variation in the reflectance functions of background objects (task-irrelevant property), using a two-alternative forced-choice paradigm in which the reflectance of the background objects is randomized across the two intervals of each trial. We control the amount of background reflectance variation by manipulating a statistical model of naturally-occurring surface reflectances. For low background object reflectance variation, discrimination thresholds were nearly constant, indicating that observers internal noise determines threshold in this regime. As background object reflectance variation increases, its effects start to dominate performance. A model based on signal detection theory allows us to express the effects of task-irrelevant variation in terms of the equivalent noise, that is relative to the intrinsic precision of the task-relevant perceptual representation. The results indicate that although naturally-occurring background object reflectance variation does intrude on the perceptual representation of target object lightness, the effect is modest - within a factor of two of the equivalent noise level set by internal noise.

neuroscience↗

bioRxiv2021

Stereo Slant Discrimination of Planar 3D Surfaces: Standard vs. Planar Cross-Correlation

Binocular stereo cues are important for discriminating 3D surface orientation, especially at near distances. We devised a single-interval task where observers discriminated the slant of a densely textured planar test surface relative to a textured planar surround reference surface. Although surfaces were rendered with correct perspective, the stimuli were designed so that the binocular cues dominated performance. Slant discrimination performance was measured as a function of the reference slant and the level of uncorrelated white noise added to the test-plane images in the left and right eye. We compared human performance with an approximate ideal observer (planar cross correlation, PCC) and two sub-ideal observers. The PCC observer uses the image in one eye and back projection to predict the test image in the other eye for all possible slants, tilts, and distances. The estimated slant, tilt, and distance are determined by the prediction that most closely matches the measured image in the other eye. The first sub-ideal observer (local PCC, LPCC) applies planar cross correlation over local neighborhoods and then pools estimates across the test plane. The second sub-optimal observer (standard cross correlation, SCC), uses only positional disparity information. We find that the ideal observer (PCC) and the first sub-ideal observer (LPCC) outperform the second sub-ideal observer (SCC), demonstrating the benefits of structural disparities. We also find that all three model observers can account for human performance, if two free parameters are included: a fixed small level of internal estimation noise, and a fixed overall efficiency scalar on slant discriminability. PrecisWe measured human stereo slant discrimination thresholds for accurately-rendered textured surfaces designed so that performance is dominated by binocular-disparity cues. We compared human performance with an approximate ideal observer and two sub-ideal observers.

animal behavior and cognition↗

bioRxiv2020

Target tracking reveals the time course of visual processing with millisecond-scale precision

Image differences between the eyes can cause interocular discrepancies in the speed of visual processing. Millisecond-scale differences in visual processing speed can cause dramatic misperceptions of the depth and 3D direction of moving objects. Here, we develop a monocular and binocular continuous target-tracking psychophysics paradigm that can quantify such tiny differences in visual processing speed. Human observers continuously tracked a target undergoing Brownian motion with a range of luminance levels in each eye. Suitable analyses recover the time-course of the visuomotor response in each condition, the dependence of visual processing speed on luminance level, and the temporal evolution of processing differences between the eyes. Importantly, using a direct within-observer comparison, we show that continuous target-tracking and traditional forced-choice psychophysical methods provide estimates of interocular delays that agree on average to within a fraction of a millisecond. Thus, visual processing delays are preserved in the movement dynamics of the hand. Finally, we show analytically, and partially confirm experimentally, that differences between the temporal impulse response functions in the two eyes predicts how lateral target motion causes misperceptions of motion-in-depth and associated tracking responses. Because continuous target-tracking can accurately recover millisecond-scale differences in visual processing speed and has multiple advantages over traditional psychophysics, it should facilitate the study of temporal processing in the future.

neuroscience↗

bioRxiv2020

Contact lenses can cause the reverse Pulfrich effect and anti-Pulfrich monovision corrections can eliminate it

Interocular differences in image blur can cause dramatic misperceptions of the distance and three-dimensional direction of moving objects. This new illusion--the reverse Pulfrich effect--is caused by the optical conditions induced by monovision, a common correction for presbyopia. Fortunately, anti-Pulfrich monovision corrections, in which the blurring lens is slightly darkened, can eliminate the illusion for a wide range of viewing conditions. However, the reverse Pulfrich effect and the efficacy of anti-Pulfrich corrections have previously been demonstrated only with trial lenses. This situation should be addressed, for both clinical and scientific reasons. First, monovision is most commonly prescribed with contact lenses. It is important to replicate these effects in the most common monovision delivery system. Second, trial lenses of different powers, unlike contacts, cause large magnification differences between the eyes. To confidently attribute the reverse Pulfrich effect to differences in optical blur between the eyes, and to ensure that the reported effect sizes are reliable, one must control for magnification. Here, in a within observer study with five separate experiments, we demonstrate i) that contact lenses induce reverse Pulfrich effects that are indistinguishable from those induced by trial lenses, ii) that overall magnification differences do not cause or impact the Pulfrich effect, and iii) that anti-Pulfrich corrections (i.e. darkening the blurring lens) are equally effective when induced by contact lenses and by trial lenses.

neuroscience↗

bioRxiv2020

Natural image statistics at depth edges modulate perceptual stability

Binocular fusion relies on matching points in the two eyes that correspond to the same physical feature in the world. However, not all world features are binocularly visible. In particular, at depth edges parts of a scene are often visible to only one eye (so-called half occlusions). Accurate detection of these monocularly visible regions is likely to be important for stable visual perception. If monocular regions are not detected as such, the visual system may attempt to binocularly fuse non-corresponding points, which can result in unstable percepts. We investigated the hypothesis that the visual system capitalizes upon statistical regularities associated with depth edges in natural scenes to aid binocular fusion and facilitate perceptual stability. By sampling from a large set of stereoscopic natural image patches, we found evidence that monocularly visible regions near depth edges in natural scenes tend to have features more visually similar to the adjacent binocularly visible background region than to the adjacent binocularly visible foreground. The generality of these results was supported by a parametric study of three-dimensional (3D) viewing geometry in simulated environments. In two perceptual experiments, we examined if this statistical regularity may be leveraged by the visual system. The results show that perception tended to be more stable when the visual properties of the depth edge were statistically more likely. Exploiting regularities in natural environments may allow the visual system to facilitate fusion and perceptual stability of natural scenes when both binocular and monocular regions are visible. PrecisWe report an analysis of natural scenes and two perceptual studies aimed at understanding how the visual statistics of depth edges impact perceptual stability. Our results suggest that the visual system exploits natural scene regularities to aid binocular fusion and facilitate perceptual stability.

neuroscience↗

bioRxiv2019

Natural scene statistics predict how humans pool information across space in the estimation of surface tilt

Visual systems estimate the three-dimensional (3D) structure of scenes from information in two-dimensional (2D) retinal images. Visual systems use multiple sources of information to improve the accuracy of these estimates, including statistical knowledge of the probable spatial arrangements of natural scenes. Here, we examine how 3D surface tilts are spatially related in real-world scenes, and show that humans pool information across space when estimating surface tilt in accordance with these spatial relationships. We develop a hierarchical model of surface tilt estimation that is grounded in the statistics of tilt in natural scenes and images. The model computes a global tilt estimate by pooling local tilt estimates within an adaptive spatial neighborhood. The spatial neighborhood in which local estimates are pooled changes according to the value of the local estimate at a target location. The hierarchical model provides more accurate estimates of groundtruth tilt in natural scenes and provides a better account of human performance than the local model. Taken together, the results imply that the human visual system pools information about surface tilt across space in accordance with natural scene statistics.

neuroscience↗

bioRxiv2019

Comprehensive characterisation of cell-free tumour DNA in plasma and urine of patients with renal tumours

Cell-free tumour-derived DNA (ctDNA) allows non-invasive monitoring of cancers but its utility in renal cell cancer (RCC) has not been established. Here, untargeted and targeted sequencing methods, applied to two independent cohorts of renal tumour patients (n=90), were used to determine ctDNA content in plasma and urine. Our data revealed lower plasma ctDNA levels in RCC relative to other cancers, with untargeted detection of [~]33%. A sensitive personalised approach, applied to plasma and urine from select patients improved detection to [~]50%, including in patients with early-stage and even benign lesions.\n\nA machine-learning based model predicted detection, potentially offering a means of triaging samples for personalised analysis. In addition, with limited data we observed that plasma, and for the first time, urine ctDNA may better represent tumour heterogeneity than tissue biopsy. Furthermore, longitudinal sampling of >200 plasma samples revealed that ctDNA can track disease course. Additional datasets will be required to validate these findings.\n\nOverall, our data highlight RCC as a ctDNA-low malignancy, but indicate potential clinical utility provided improvement in detection approaches.\n\nOne sentence summaryComplementary sequencing methods show that cell-free tumour DNA levels are low in renal cancer though, via various strategies, may still be informative.

cancer biology↗

bioRxiv2019

Predicting the partition of behavioral variability in speed perception with naturalistic stimuli

A core goal of visual neuroscience is to predict human perceptual performance from natural signals. Performance in any natural task can be impacted by at least three sources of uncertainty: stimulus variability, internal noise, and sub-optimal computations. Determining the relative importance of these factors has been a focus of interest for decades, but most successes have been achieved with simple tasks and simple stimuli. Drawing quantitative links directly from natural signals to perceptual performance has proven a substantial challenge. Here, we develop an image-computable (pixels in, estimates out) Bayesian ideal observer that makes optimal use of the statistics relating image movies to speed. The optimal computations bear striking resemblance to descriptive models proposed to account for neural activity in area MT. We develop a model based on the ideal, stimulate it with naturalistic signals, predict the behavioral signatures of each performance-limiting factor, and test the predictions in an interlocking series of speed discrimination experiments. The critical experiment collects human responses to repeated presentations of each unique image movie. The model, highly constrained by the earlier experiments, tightly predicts human response consistency without free parameters. This result implies that human observers use near-optimal computations to estimate speed, and that human performance is near-exclusively limited by natural stimulus variability and internal noise. The results demonstrate that human performance can be predicted from a task-specific statistical analysis of naturalistic stimuli, show that image-computable ideal observer analysis can be generalized from simple to natural stimuli, and encourage similar analyses in other domains.

neuroscience↗

bioRxiv2019

Monovision and the misperception of motion

Monovision corrections are a common treatment for presbyopia. Each eye is fit with a lens that sharply focuses light from a different distance, causing the image in one eye to be blurrier than the other. Millions of people in the United States and Europe have monovision corrections, but little is known about how differential blur affects motion perception. We investigated by measuring the Pulfrich effect, a stereo-motion phenomenon first reported nearly 100 years ago. When a moving target is viewed with unequal retinal illuminance or contrast in the two eyes, the target appears to be closer or further in depth than it actually is, depending on its frontoparallel direction. The effect occurs because the image with lower illuminance or contrast is processed more slowly. The mismatch in processing speed causes a neural disparity, which results in the illusory motion in depth. What happens with differential blur? Remarkably, differential blur causes a reverse Pulfrich effect, an apparent paradox. Blur reduces contrast and should therefore cause processing delays. But the reverse Pulfrich effect implies that the blurry image is processed more quickly. The paradox is resolved by recognizing that: i) blur reduces the contrast of high-frequency image components more than low-frequency image components, and ii) high spatial frequencies are processed more slowly than low spatial frequencies, all else equal. Thus, this new illusion--the reverse Pulfrich effect--can be explained by known properties of the early visual system. A quantitative analysis shows that the associated misperceptions are large enough to impact public safety.

neuroscience↗

bioRxiv2018

Model neuron response statistics to natural images

To model the responses of neurons in the early visual system, at least three basic components are required: a receptive field, a normalization term, and a specification of encoding noise. Here, we examine how the receptive field, the normalization factor, and the encoding noise impact the model neuron responses to natural images and the signal-to-noise ratio for natural image discrimination. We show that when these components are modeled appropriately, the model neuron responses to natural stimuli are Gaussian distributed, scale-invariant, and very nearly maximize the signal-to-noise ratio for stimulus discrimination. We discuss the statistical models of natural stimuli that can account for these response statistics, and we show how some commonly used modeling practices may distort these results. Finally, we show that normalization can equalize important properties of neural response across different stimulus types. Specifically, narrowband (stimulus- and feature-specific) normalization causes model neurons to yield Gaussian-distributed responses to natural stimuli, 1/f noise stimuli, and white noise stimuli. The current work makes recommendations for best practices and it lays a foundation, grounded in the response statistics to natural stimuli, upon which principled models of more complex visual tasks can be built.

neuroscience↗