Filling-in and suppression of visual perception from context: a Bayesian account of perceptual biases by contextual influences

Isolating objective and subjective filling-in using the drift diffusion model

Spatial context is known to influence the behavioral sensitivity (d') and the decision criterion (c) when detecting low-contrast targets. Of interest here is the effect on the decision criterion. Polat and Sagi (2007) demonstrated that, for a Gabor target positioned between two similar co-aligned high-contrast flankers, the observers' reports of seeing the target (Hit and False Alarm) decreased with increasing target-flanker distance. This effect was more pronounced when the distance was randomized within testing blocks compared to when it was fixed. According to signal detection theory (SDT), the latter result suggests that the decision criterion is adjusted to a specific distance-dependent combination of signal (S) and noise (N) when the S and N statistics are fixed, but not when they vary across trials. However, SDT cannot differentiate between changes in the decision bias (the criterion shift) and changes introduced by variations in S and N (the signal and noise shift). To circumvent this limitation of SDT, we analyzed the reaction time (RT) data within the framework of the drift diffusion model (DDM). We performed an RT analysis of the target-flanker interactions using data from Polat and Sagi (2007) and Zomet et al. (2008; 2016). The analysis revealed a stronger dependence on flankers for faster RTs and a weaker dependence for slower RTs. The results can be explained by DDM, where an evidence accumulation process depends on the flankers via a change in the rate of the evidence (signal and noise shift) and on observers' prior knowledge via a change in the starting point (criterion shift), leading to RT-independent and RT-dependent effects, respectively. The RT-independent distance-dependent response bias is attributed to the observers' inability to learn multiple internal distributions required to accommodate the distance-dependent effects of the flankers on both the signal and noise.

Testing the effect of display organization in the collinear search impairment

Previous studies established that a salient collinear structure impairs local visual search. A display organization hypothesis states that the vertical grouping of elemental bars in the search display may selectively increase the salience of the local target in the background than that in the collinear distractor, leading to the collinear search impairment. Three displays were designed to test this hypothesis. A classical search display was adopted as a baseline. A diagonal search display was created with tilted bars, making perceptual organization diagonal and should reduce collinear search impairment. An illusory search display was designed by using abutting line illusion to emphasize the vertical grouping direction, which should increase collinear search impairment. A manipulation check was conducted with an online survey to understand the perceptual organization of the three displays. Results showed that the probability to perceive the stimuli grouping in the vertical direction was strongest in the illusory display and the least in the diagonal display. Nevertheless, the collinear search impairment did not vary with these manipulations, argue against the display organization hypothesis. We speculate that the search impairment might associate with the perceptual organization of the collinear distractor per se, rather than the perceptual organization of the background.

Inference via sparse coding in a hierarchical vision model

Sparse coding has been incorporated in models of the visual cortex for its computational advantages and connection to biology. But how the level of sparsity contributes to performance on visual tasks is not well understood. In this work, sparse coding has been integrated into an existing hierarchical V2 model (Hosoya & Hyvärinen, 2015), but replacing its independent component analysis (ICA) with an explicit sparse coding in which the degree of sparsity can be controlled. After training, the sparse coding basis functions with a higher degree of sparsity resembled qualitatively different structures, such as curves and corners. The contributions of the models were assessed with image classification tasks, specifically tasks associated with mid-level vision including figure–ground classification, texture classification, and angle prediction between two line stimuli. In addition, the models were assessed in comparison with a texture sensitivity measure that has been reported in V2 (Freeman et al., 2013) and a deleted-region inference task. The results from the experiments show that although sparse coding performed worse than ICA at classifying images, only sparse coding was able to better match the texture sensitivity level of V2 and infer deleted image regions, both by increasing the degree of sparsity in sparse coding. Greater degrees of sparsity allowed for inference over larger deleted image regions. The mechanism that allows for this inference capability in sparse coding is described in this article.

Contrast-reversed binocular dot-pairs in random-dot stereograms for depth perception in central visual field: Probing the dynamics of feedforward-feedback processes in visual inference

In a random-dot stereogram (RDS), the spatial disparities between the interocularly corresponding black and white random dots determine the depths of object surfaces. If a black dot in one monocular image corresponds to a white dot in the other, disparity-tuned neurons in primary visual cortex (V1) respond as if their preferred disparities become non-preferred and vice versa, reversing the disparity sign reported to higher visual areas. Reversed depth is perceptible in the peripheral but not the central visual field. This study demonstrates that, in central vision, adding contrast-reversed dots to a noisy RDS (containing the normal contrast-matched dots) can augment or degrade depth perception. Augmentation occurs when the reversed depth signals are congruent with the normal depth signals to report the same disparity sign, and occurs regardless of the viewing duration. Degradation occurs when the reversed and normal depth signals are incongruent with each other and when the RDS is viewed briefly. These phenomena reflect the Feedforward-Feedback-Verify-and-reWeight (FFVW) process for visual inference in central vision, and are consistent with the central-peripheral dichotomy that central vision has a stronger top-down feedback from higher to lower brain areas to disambiguate noisy and ambiguous inputs from V1. When a RDS is viewed too briefly for feedback, augmentation and degradation work by adding the reversed depth signals from contrast-reversed dots to the feedforward, normal, depth signals. With a sufficiently long viewing duration, the feedback vetoes incongruent reversed depth signals and amends or completes the imperfect, but congruent, reversed depth signals by analysis-by-synthesis computation.

Collinear masking effect in visual search is independent of perceptual salience

Searching for a target in a salient region should be easier than looking for one in a nonsalient region. However, we previously discovered a contradictory phenomenon in which a local target in a salient structure was more difficult to find than one in the background. The salient structure was constructed of orientation singletons aligned to each other to form a collinear structure. In the present study, we undertake to determine whether such a masking effect was a result of salience competition between a global structure and the local target. In the first 3 experiments, we increased the salience value of the local target with the hope of adding to its competitive advantage and eventually eliminating the masking effect; nevertheless, the masking effect persisted. In an additional 2 experiments, we reduced salience of the global collinear structure by altering the orientation of the background bars and the masking effect still emerged. Our salience manipulations were validated by a controlled condition in which the global structure was grouped noncollinearly. In this case, local target salience increase (e.g., onset) or global distractor salience reduction (e.g., randomized flanking orientations) effectively removed the facilitation effect of the noncollinear structure. Our data suggest that salience competition is unlikely to explain the collinear masking effect, and other mechanisms such as contour integration, border formation, or the crowding effect may be prospective candidates for further investigation.

The perceptual saliency of fearful eyes and smiles: A signal detection study

Facial features differ in the amount of expressive information they convey. Specifically, eyes are argued to be essential for fear recognition, while smiles are crucial for recognising happy expressions. In three experiments, we tested whether expression modulates the perceptual saliency of diagnostic facial features and whether the feature's saliency depends on the face configuration. Participants were presented with masked facial features or noise at perceptual conscious threshold. The task was to indicate whether eyes (experiments 1-3A) or a mouth (experiment 3B) was present. The expression of the face and its configuration (i.e. spatial arrangement of the features) were manipulated. Experiment 1 compared fearful with neutral expressions, experiments 2 and 3 compared fearful versus happy expressions. The detection accuracy data was analysed using Signal Detection Theory (SDT), to examine the effects of expression and configuration on perceptual precision (d') and response bias (c), separately. Across all three experiments, fearful eyes were detected better (higher d') than neutral and happy eyes. Eyes were more precisely detected than mouths, whereas smiles were detected better than fearful mouths. The configuration of the features had no consistent effects across the experiments on the ability to detect expressive features. But facial configuration affected consistently the response bias. Participants used a more liberal criterion for detecting the eyes in canonical configuration and fearful expression. Finally, the power in low spatial frequency of a feature predicted its discriminability index. The results suggest that expressive features are perceptually more salient with a higher d' due to changes at the low-level visual properties, with emotions and configuration affecting perception through top-down processes, as reflected by the response bias.

Dichotomy in perceptual learning of interval timing: calibration of mean accuracy and precision differ in specificity and time course

Our brain is inexorably confronted with a dynamic environment in which it has to fine-tune spatiotemporal representations of incoming sensory stimuli and commit to a decision accordingly. Among those representations needing constant calibration is interval timing, which plays a pivotal role in various cognitive and motor tasks. To investigate how perceived time interval is adjusted by experience, we conducted a human psychophysical experiment using an implicit interval-timing task in which observers responded to an invisible bar drifting at a constant speed. We tracked daily changes in distributions of response times for a range of physical time intervals over multiple days of training with two major types of timing performance, mean accuracy and precision. We found a decoupled dynamics of mean accuracy and precision in terms of their time course and specificity of perceptual learning. Mean accuracy showed feedback-driven instantaneous calibration evidenced by a partial transfer around the time interval trained with feedback, while timing precision exhibited a long-term slow improvement with no evident specificity. We found that a Bayesian observer model, in which a subjective time interval is determined jointly by a prior and likelihood function for timing, captures the dissociative temporal dynamics of the two types of timing measures simultaneously. Finally, the model suggested that the width of the prior, not the likelihoods, gradually shrinks over sessions, substantiating the important role of prior knowledge in perceptual learning of interval timing.

On the rules of integration of crowded orientation signals

Crowding is related to an integration of feature signals over an inappropriately large area in the visual periphery. The rules of this integration are still not well understood. This study attempts to understand how the orientation signals from the target and flankers are combined. A target Gabor, together with 2, 4, or 6 flanking Gabors, was briefly presented in a peripheral location (4° eccentricity). The observer's task was to identify the orientation of the target (eight-alternative forced-choice). Performance was found to be nonmonotonically dependent on the target-flanker orientation difference (a drop at intermediate differences). For small target-flanker differences, a strong assimilation bias was observed. An effect of the number of flankers was found for heterogeneous flankers only. It appears that different rules of integration are used, dependent on some salient aspects (target pop-out, homogeneity-heterogeneity) of the stimulus pattern. The strategy of combining simple rules may be explained by the goal of the visual system to encode potentially important aspects of a stimulus with limited processing resources and using statistical regularities of the natural visual environment.

Methods for segmentation and interpretation of electron tomographic reconstructions

Electron tomography has become a powerful tool for revealing the molecular architecture of biological cells and tissues. In principle, electron tomography can provide high-resolution mapping of entire proteomes. The achievable resolution (3-8 nm) is capable of bridging the gap between live-cell imaging and atomic resolution structures. However, the relevant information is not readily accessible from the data and needs to be identified, extracted, and processed before it can be used. Because electron tomography imaging and image acquisition technologies have enjoyed major advances in the last few years and continue to increase data throughput, the need for approaches that allow automatic and objective interpretation of electron tomograms becomes more and more urgent. This chapter provides an overview of the state of the art in this field and attempts to identify the major bottlenecks that prevent approaches for interpreting electron tomography data to develop their full potential.

Perceptual organization in the tilt illusion

The tilt illusion is a paradigmatic example of contextual influences on perception. We analyze it in terms of a neural population model for the perceptual organization of visual orientation. In turn, this is based on a well-found treatment of natural scene statistics, known as the Gaussian Scale Mixture model. This model is closely related to divisive gain control in neural processing and has been extensively applied in the image processing and statistical learning communities; however, its implications for contextual effects in biological vision have not been studied. In our model, oriented neural units associated with surround tilt stimuli participate in divisively normalizing the activities of the units representing a center stimulus, thereby changing their tuning curves. We show that through standard population decoding, these changes lead to the forms of repulsion and attraction observed in the tilt illusion. The issues in our model readily generalize to other visual attributes and contextual phenomena, and should lead to more rigorous treatments of contextual effects based on natural scene statistics.