The Warped Geometry of Visual Space Near a Line Assessed Using a Hyperacuity Displacement Task

Badcock & Westheimer (Spatial Vision, 1(1), 3-11, 1985) showed that a thin vertical line induces nearby zones of attraction and repulsion; this study extends those results by more closely examining the horizontal and vertical extents of the repulsion zone and by using an illusory contour to induce repulsion. The experimental paradigm measures perceived hyperacute displacements of a thin vertical line 10' tall. Halfway through the stimulus, the bright target line was shifted and a lower contrast flanking line added. Conditions equivalent to Badcock & Westheimer replicate their results. Repulsion is observed horizontally from separations of 5' to at least 30' and becomes minimal at 50'. Repulsion also decreases with increasing vertical separation. Another experiment shows that symmetry is not required for repulsion when the flanking line is split into two vertically separated fragments; one fragment alone causes the same amount of repulsion as both fragments together. Finally, it is shown that a flanking contour formed by the grating illusion causes repulsion of the target line in the same manner as a target line defined by luminance.British Petroleum (89A-1204); Defense Advanced Research Projects Agency (90-0083); Air Force Office of Scientific Research (90-0175

Effects of biased feedback on learning and deciding in a vernier discrimination task

AbstractWe investigate the influence of biased feedback on decision and learning processes in a vernier discrimination task. Subjects adjust their decision criteria and hence their responses according to biased external feedback. However, they do not use learning processes to encode incorrectly classified stimuli. As soon as correct feedback is restored observers regain their original performance indicating an involvement of internal criteria. If the external feedback is switched off instead of being corrected, the rebound is less vigorous. The findings contradict predictions of supervised neural network models

Estimation of the parameters of a boundary contour system using psychophysical hyperacuity experiments

Dissertation (Ph.D.)--Boston UniversityVisual hyperacuity enables observers to make accurate judgments of the relative positions of stimuli when the differences are smaller than the size of a single cone in the fovea. Because hyperacuity can serve as a gauge for precisely measuring characteristics of the visual system, it can provide stringent tests for models of the visual system. A variant of the Boundary Contour System (BCS) model is here used to clarify previously unexplained psychophysical hyperacuity results involving contrast polarity, stimulus separation, and sinusoidal masking gratings. Two-dot alignment thresholds were studied by Levi & Waugh (1996) by varying the gap between the dots, with same and opposite contrast polarity with respect to the background, and also with and without band-limited sinusoidal grating masks of different orientations. They found that when the gap between the dots is small (6 arcmin), different patterns of misalignment thresholds are obtained for the same and different contrast polarity conditions. However, when the gap is large (24 arcmin), the same pattern of thresholds was obtained irrespective of contrast polarity. The simulations presented here replicate these findings, producing the same pattern of results when varying the gap between the dots, with same and opposite contrast polarity with respect to the background, and also with and without sinusoidal grating masks of different orientations. The vision model used (BCS) is able to produce these patterns because of its inherent processing using contrast insensitivity, spatial and oriented competition, and long-range completion layers. A novel aspect of the model is the use of sampled field processing, which simplifies the model's equations. Modified Hebbian learning and a neural decision module are proposed as mechanisms that link the vision model's outputs to a decision criterion. All model parts have plausible neurobiological correlates. In addition, psychophysical hyperacuity experiments served to map the limits of inhibitory spatial interactions. The results show that inhibition occurs even when only half of the split flanking line of Badcock & Westheimer (1985b) is used, suggesting that subthreshold activity in units representing the line extends beyond the end of the line. Furthermore, strong inhibition was observed with a flanking illusory line grating

The relationship of alignment hyperacuity to stereopsis

Human ability to monocularly detect spatial misalignment is functionally more precise than predicted by the diameter of one foveal cone. The spatial thresholds for vernier alignment are approximately 8 to 13 arc seconds of visual angle, which is more sensitive than expected. Although threshold stereopsis (another hyperacuity) seems to be approximately double alignment hyperacuity values, studies have not conclusively shown a definite relationship to ex1st. Additionally, these measurements have not been widely tested in clinical settings. This study examines the correlation between threshold stereoacuity and the monocular alignment hyperacuity measures. Twenty six subjects were evaluated measuring threshold stereopsis with the Mentor BVAT II Visual Acuity Tester and monocular alignment hyperacuity with software designed at Pacific University College of Optometry. This study supports a relationship of sum of one standard deviation of hyperacuity data distributed for each eye with stereopsis. However, the relationship is not statistically significant, most likely due to the lack of testing precision and variability in individual performance, specifically in binocular function and appreciation of stereopsis. Increased knowledge in the areas of monocular alignment hyperacuity and threshold stereopsis may aid optometric practitioners to better understand how these two factors play a role in such clinical conditions as unexplained asthenopia, amblyopia, strabismus and stereoacuity potential. However, clinical testing of an individual patient would not seem appropriate with this testing paradigm

Electrical stimulation of visual cortex can immediately improve spatial vision

Published in final edited form as:Curr Biol. 2016 July 25; 26(14): 1867–1872. doi:10.1016/j.cub.2016.05.019.SUMMARY We can improve human vision by correcting the optics of our lenses [1, 2, 3]. However, after the eye transduces the light, visual cortex has its own limitations that are challenging to correct [4]. Overcoming these limitations has typically involved innovative training regimes that improve vision across many days [5, 6]. In the present study, we wanted to determine whether it is possible to immediately improve the precision of spatial vision with noninvasive direct-current stimulation. Previous work suggested that visual processing could be modulated with such stimulation [7, 8, 9]. However, the short duration and variability of such effects made it seem unlikely that spatial vision could be improved for more than several minutes [7, 10]. Here we show that visual acuity in the parafoveal belt can be immediately improved by delivering noninvasive direct current to visual cortex. Twenty minutes of anodal stimulation improved subjects’ vernier acuity by approximately 15% and increased the amplitude of the earliest visually evoked potentials in lockstep with the behavioral effects. When we reversed the orientation of the electric field, we impaired resolution and reduced the amplitude of visually evoked potentials. Next, we found that anodal stimulation improved acuity enough to be measurable with the relatively coarse Snellen test and that subjects with the poorest acuity benefited the most from stimulation. Finally, we found that stimulation-induced acuity improvements were accompanied by changes in contrast sensitivity at high spatial frequencies.This work was supported by grants from the NIH (R01-EY019882, R01-EY025275, P30-EY08126, T32-EY007135, F31-MH102042). We thank the reviewers and Randolph Blake for helpful comments. We thank Kevin Dieter for technical assistance in designing the psychophysical procedure for experiment 5. Subjects gave informed written consent to procedures approved by the Vanderbilt University Institutional Review Board and were compensated at a rate of $10/hr for their time. (R01-EY019882 - NIH; R01-EY025275 - NIH; P30-EY08126 - NIH; T32-EY007135 - NIH; F31-MH102042 - NIH)Accepted manuscrip

Assessing the detailed time course of perceptual sensitivity change in perceptual learning.

The learning curve in perceptual learning is typically sampled in blocks of trials, which could result in imprecise and possibly biased estimates, especially when learning is rapid. Recently, Zhao, Lesmes, and Lu (2017, 2019) developed a Bayesian adaptive quick Change Detection (qCD) method to accurately, precisely, and efficiently assess the time course of perceptual sensitivity change. In this study, we implemented and tested the qCD method in assessing the learning curve in a four-alternative forced-choice global motion direction identification task in both simulations and a psychophysical experiment. The stimulus intensity in each trial was determined by the qCD, staircase or random stimulus selection (RSS) methods. Simulations showed that the accuracy (bias) and precision (standard deviation or confidence bounds) of the estimated learning curves from the qCD were much better than those obtained by the staircase and RSS method; this is true for both trial-by-trial and post hoc segment-by-segment qCD analyses. In the psychophysical experiment, the average half widths of the 68.2% credible interval of the estimated thresholds from the trial-by-trial and post hoc segment-by-segment qCD analyses were both quite small. Additionally, the overall estimates from the qCD and staircase methods matched extremely well in this task where the behavioral rate of learning is relatively slow. Our results suggest that the qCD method can precisely and accurately assess the trial-by-trial time course of perceptual learning

The Role of Non-Linearities in Visual Perception studied with a Computational Model of the Vertebrate Retina

Processing of visual stimuli in the vertebrate retina is complex and diverse. The retinal output to the higher centres of the nervous system, mediated by ganglion cells, consists of several different channels. Neurons in these channels can have very distinct response properties, which originate in different retinal pathways. In this work, the retinal origins and possible functional implications of the segregation of visual pathways will be investigated with a detailed, biologically realistic computational model of the retina. This investigation will focus on the two main retino-cortical pathways in the mammalian retina, the parvocellular and magnocellular systems, which are crucial for conscious visual perception. These pathways differ in two important aspects. The parvocellular system has a high spatial, but low temporal resolution. Conversely, the magnocellular system has a high temporal fidelity, spatial sampling however is less dense than for parvocellular cells. Additionally, the responses of magnocellular ganglion cells can show pronounced nonlinearities, while the parvocellular system is essentially linear. The origin of magnocellular nonlinearities is unknown and will be investigated in the first part of this work. As their main source, the results suggest specific properties of the photoreceptor response and a specialised amacrine cell circuit in the inner retina. The results further show that their effect combines in a multiplicative way. The model is then used to examine the influence of nonlinearities on the responses of ganglion cells in the presence of involuntary fixational eye movements. Two different stimulus conditions will be considered: visual hyperacuity and motion induced illusions. In both cases, it is possible to directly compare properties of the ganglion cell population response with psychophysical data, which allows for an analysis of the influence of different components of the retinal circuitry. The simulation results suggest an important role for nonlinearities in the magnocellular stream for visual perception in both cases. First, it will be shown how nonlinearities, triggered by fixational eye movements, can strongly enhance the spatial precision of magnocellular ganglion cells. As a result, their performance in a hyperacuity task can be equal to or even surpass that of the parvocellular system. Second, the simulations imply that the origin of some of the illusory percepts elicited by fixational eye movements could be traced back to the nonlinear properties of magnocellular ganglion cells. As these activity patterns strongly differ from those in the parvocellular system, it appears that the magnocellular system can strongly dominate visual perception in certain conditions. Taken together, the results of this theoretical study suggest that retinal nonlinearities may be important for and strongly influence visual perception. The model makes several experimentally verifiable predictions to further test and quantify these findings. Furthermore, models investigating higher visual processing stages may benefit from this work, which could provide the basis to produce realistic afferent input

High resolution, high capacity, spatial specificity in perceptual learning.

Research of perceptual learning has received significant interest due to findings that training on perceptual tasks can yield learning effects that are specific to the stimulus features of that task. However, recent studies have demonstrated that while training a single stimulus at a single location can yield a high-degree of stimulus specificity, training multiple features, or at multiple locations can reveal a broad transfer of learning to untrained features or stimulus locations. We devised a high resolution, high capacity, perceptual learning procedure with the goal of testing whether spatial specificity can be found in cases where observers are highly trained to discriminate stimuli in many different locations in the visual field. We found a surprising degree of location specific learning, where performance was significantly better when target stimuli were presented at 1 of the 24 trained locations compared to when they were placed in 1 of the 12 untrained locations. This result is particularly impressive given that untrained locations were within a couple degrees of visual angle of those that were trained. Given the large number of trained locations, the fact that the trained and untrained locations were interspersed, and the high-degree of spatial precision of the learning, we suggest that these results are difficult to account for using attention or decision strategies and instead suggest that learning may have taken place for each location separately in retinotopically organized visual cortex

Perceptual learning in visual hyperacuity: A reweighting model

AbstractImprovements of visual hyperacuity are a key focus in research of perceptual learning. Of particular interest has been the specificity of visual hyperacuity learning to the particular features of the trained stimuli as well as disruption of learning that occurs in some cases when different stimulus features are trained together. The implications of these phenomena on the underlying learning mechanisms are still open to debate; however, there is a marked absence of computational models that explore these phenomena in a unified way. Here we implement a computational learning model based on reweighting and extend it to enable direct comparison, by means of simulations, with a variety of existing psychophysical data. We find that this very simple model can account for a diversity of findings, such as disruption of learning of one task by practice on a similar task, as well as transfer of learning across both tasks and stimulus configurations under certain conditions. These simulations help explain existing results in the literature as well as provide important insights and predictions regarding the reliability of different hyperacuity tasks and stimuli. Our simulations also shed light on the model’s limitations, for example in accounting for temporal aspects of training procedures or dependency of learning with contextual stimuli, which will need to be addressed by future research