Peripheral vision and crowding in mental maze-solving.

Solving a maze effectively relies on both perception and cognition. Studying maze-solving behavior contributes to our knowledge about these important processes. Through psychophysical experiments and modeling simulations, we examine the role of peripheral vision, specifically visual crowding in the periphery, in mental maze-solving. Experiment 1 measured gaze patterns while varying maze complexity, revealing a direct relationship between visual complexity and maze-solving efficiency. Simulations of the maze-solving task using a peripheral vision model confirmed the observed crowding effects while making an intriguing prediction that saccades provide a conservative measure of how far ahead observers can perceive the path. Experiment 2 confirms that observers can judge whether a point lies on the path at considerably greater distances than their average saccade. Taken together, our findings demonstrate that peripheral vision plays a key role in mental maze-solving.

An Automated Visual Psychophysics Method to Measure Visual Function in Swine Preclinical Animal Model.

Purpose: The aim of this study was to develop and validate a test to assess visual function in pigs using the visual psychophysics contrast sensitivity function. Methods: We utilized a touchscreen along with a pellet reward dispenser to train three Göttingen pigs on a visual psychophysics test and determined their contrast sensitivity function. Images with different contrast resolutions were used as visual stimuli and presented against a control image in a two-choice test. Following animals' acclimatization and the first phase of training, the system was arranged such that animals could self-run multiple consecutive trials without human intervention. Results: All animals were trained within a week and remembered the task with 1 day of reinforcement when tested 1 month after the last visual assessment. All trained animals performed well during the trial with minimal screen side bias, especially at contrast threshold above 40%. Conclusions: Göttingen pigs are trainable for a visual psychophysics test and able to self-run the trial without human intervention. Translational Relevance: Contrast sensitivity is one of the key parameters to assess visual function in humans. The possibility of measuring the same parameters in a large animal model allows for a better translation and understanding of drug safety and efficacy in preclinical ophthalmology.

Are ipRGCs involved in human color vision? Hints from physiology, psychophysics, and natural image statistics.

Human photoreceptors consist of cones, rods, and melanopsin-expressing intrinsically photosensitive retinal ganglion cells (ipRGCs). First studied in circadian regulation and pupillary control, ipRGCs project to a variety of brain centers suggesting a broader involvement beyond non-visual functions. IpRGC responses are stable, long-lasting, and with a particular codification of photoreceptor signals. In comparison with the transient and adaptive nature of cone and rod signals, ipRGCs' signaling might provide an ecological advantage to different attributes of color vision. Previous studies have indicated melanopsin's influence on visual responses yet its contribution to color perception in humans remains debated. We summarized evidence and hypotheses (from physiology, psychophysics, and natural image statistics) about direct and indirect involvement of ipRGCs in human color vision, by first briefly assessing the current knowledge about the role of melanopsin and ipRGCs in vision and codification of spectral signals. We then approached the question about melanopsin activation eliciting a color percept, discussing studies using the silent substitution method. Finally, we explore various avenues through which ipRGCs might impact color perception indirectly, such as through involvement in peripheral color matching, post-receptoral pathways, color constancy, long-term chromatic adaptation, and chromatic induction. While there is consensus about the role of ipRGCs in brightness perception, confirming its direct contribution to human color perception requires further investigation. We proposed potential approaches for future research, emphasizing the need for empirical validation and methodological thoroughness to elucidate the exact role of ipRGCs in human color vision.

Motion-Acuity Test for Visual Field Acuity Measurement with Motion-Defined Shapes.

The standard visual acuity measurements rely on stationary stimuli, either letters (Snellen charts), vertical lines (vernier acuity) or grating charts, processed by those regions of the visual system most sensitive to the stationary stimulation, receiving visual input from the central part of the visual field. Here, an acuity measurement is proposed based on discrimination of simple shapes, that are defined by motion of the dots in the random dot kinematograms (RDK) processed by visual regions sensitive to motion stimulation and receiving input also from the peripheral visual field. In the motion-acuity test, participants are asked to distinguish between a circle and an ellipse, with matching surfaces, built from RDKs, and separated from the background RDK either by coherence, direction, or velocity of dots. The acuity measurement is based on ellipse detection, which with every correct response becomes more circular until reaching the acuity threshold. The motion-acuity test can be presented in negative contrast (black dots on white background) or in positive contrast (white dots on black background). The motion defined shapes are located centrally within 8 visual degrees and are surrounded by RDK background. To test the influence of visual peripheries on centrally measured acuity, a mechanical narrowing of the visual field to 10 degrees is proposed, using opaque goggles with centrally located holes. This easy and replicable narrowing system is suitable for MRI protocols, allowing further investigations of the functions of the peripheral visual input. Here, a simple measurement of shape and motion perception simultaneously is proposed. This straightforward test assesses vision impairments depending on the central and peripheral visual field inputs. The proposed motion-acuity test advances the capability of standard tests to reveal spare or even strengthened vision functions in patients with injured visual system, that until now remained undetected.

The psychophysics of home plate umpire calls.

We analyze the visual perception task that home plate umpires (N = 121) perform calling balls and strikes (N = 3,001,019) in baseball games, focusing on the topics of perceptual learning and bias in decision-making. In the context of perceptual learning, our results show that monitoring, training, and feedback improve skill over time. In addition, we document two other aspects of umpires' improvement that are revealing with respect to the nature of their perceptual expertise. First, we show that biases in umpires' decision-making persist even as their overall accuracy improves. This suggests that bias and accuracy are orthogonal and that reduction of bias in decision-making requires interventions aimed specifically at this goal. Second, we measure a distinct difference in the rate of skill improvement between older and younger umpires. Younger umpires improve more quickly, suggesting that the decision task umpires engage in becomes routinized over time.

Over- and underweighting of extreme values in decisions from sequential samples.

People routinely make decisions based on samples of numerical values. A common conclusion from the literature in psychophysics and behavioral economics is that observers subjectively compress magnitudes, such that extreme values have less sway over people's decisions than prescribed by a normative model (underweighting). However, recent studies have reported evidence for anti-compression, that is, the relative overweighting of extreme values. Here, we investigate potential reasons for this discrepancy in findings and propose that it might reflect adaptive responses to different task requirements. We performed a large-scale study (n = 586) of sequential numerical integration, manipulating (a) the task requirement (averaging a single stream or comparing two interleaved streams of numbers), (b) the distribution of sample values (uniform or Gaussian), and (c) their range (1-9 or 100-900). The data showed compression of subjective values in the averaging task, but anticompression in the comparison task. This pattern held for both distribution types and for both ranges. In model simulations, we show that either compression or anticompression can be beneficial for noisy observers, depending on the sample-level processing demands imposed by the task. This suggests that the empirically observed patterns of over- and underweighting might reflect adaptive responses. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Mission impossible? Spatial context relearning following a target relocation event depends on cue predictiveness.

Visual search for a target is faster when the spatial layout of distractors is repeatedly encountered, illustrating that statistical learning of contextual invariances facilitates attentional guidance (contextual cueing; Chun & Jiang, 1998, Cognitive Psychology, 36, 28-71). While contextual learning is usually relatively efficient, relocating the target to an unexpected location (within an otherwise unchanged search layout) typically abolishes contextual cueing and the benefits deriving from invariant contexts recover only slowly with extensive training (Zellin et al., 2014, Psychonomic Bulletin & Review, 21(4), 1073-1079). However, a recent study by Peterson et al. (2022, Attention, Perception, & Psychophysics, 84(2), 474-489) in fact reported rather strong adaptation of spatial contextual memories following target position changes, thus contrasting with prior work. Peterson et al. argued that previous studies may have been underpowered to detect a reliable recovery of contextual cueing after the change. However, their experiments also used a specific display design that frequently presented the targets at the same locations, which might reduce the predictability of the contextual cues thereby facilitating its flexible relearning (irrespective of statistical power). The current study was a (high-powered) replication of Peterson et al., taking into account both statistical power and target overlap in context-memory adaptation. We found reliable contextual cueing for the initial target location irrespective of whether the targets shared their location across multiple displays, or not. However, contextual adaptation following a target relocation event occurred only when target locations were shared. This suggests that cue predictability modulates contextual adaptation, over and above a possible (yet negligible) influence of statistical power.

Responding, fast and slow: Visual detection and localization performance is unaffected by retrieval.

According to action control theories, responding to a stimulus leads to the binding of the response and stimulus features into an event file. Repeating any component of the latter retrieves previous information, affecting ongoing performance. Based on years of attentional orienting research, recent boundaries of such binding theories have been proposed as binding effects are fully absent in visual detection (e.g., Schöpper et al., 2020, Attention, Perception, & Psychophysics, 82(4), 2085-2097) and localization (e.g., Schöpper & Frings, 2022; Visual Cognition, 30(10), 641-658) performance. While this can be attributed to specific task demands, the possibility remains that retrieval of previous event files is hampered in such tasks due to overall fast responding. In the current study we instructed participants to signal the detection (Experiment 1) and location (Experiment 2) of dots orthogonally repeating or changing their nonspatial identity and location. Crucially, the dots were either hard or easy to perceive. As expected, making targets hard to perceive drastically slowed down detection and localization response speed. Importantly, binding effects were absent irrespective of perceptibility. In contrast, discriminating the nonspatial identity of targets (Experiment 3) showed strong binding effects. These results highlight the impact of task-dependence for binding approaches in action control.

Examining Increment thresholds as a function of pedestal contrast under hypothetical parvo- and magnocellular-biased conditions.

Theoretically, the pulsed- and steady-pedestal paradigms are thought to track contrast-increment thresholds (ΔC) as a function of pedestal contrast (C) for the parvocellular (P) and magnocellular (M) systems, respectively, yielding linear ΔC versus C functions for the pulsed- and nonlinear functions for the steady-pedestal paradigm. A recent study utilizing these paradigms to isolate the P and M systems reported no evidence of the M system being suppressed by red light, contrary to previous physiological and psychophysical findings. Curious as to why this may have occurred, we examined how ΔC varies with C for the P and M systems using the pulsed- and steady-pedestal paradigms and stimuli biased towards the P or M systems based on their sensitivity to spatial frequency (SF) and color. We found no effect of color and little influence of SF. To explain this lack of color effects, we used a quantitative model of ΔC (as it changes with C) to obtain Csat and contrast-gain values. The contrast-gain values (i) contradicted the hypothesis that the steady-pedestal paradigm tracks the M-system response, and (ii) our obtained Csat values indicated strongly that both pulsed- and steady-pedestal paradigms track primarily the P-system response.

Psychophysics may be the game-changer for deep neural networks (DNNs) to imitate the human vision.

Psychologically faithful deep neural networks (DNNs) could be constructed by training with psychophysics data. Moreover, conventional DNNs are mostly monocular vision based, whereas the human brain relies mainly on binocular vision. DNNs developed as smaller vision agent networks associated with fundamental and less intelligent visual activities, can be combined to simulate more intelligent visual activities done by the biological brain.

The psychophysics of human three-dimensional active visuospatial problem-solving.

Our understanding of how visual systems detect, analyze and interpret visual stimuli has advanced greatly. However, the visual systems of all animals do much more; they enable visual behaviours. How well the visual system performs while interacting with the visual environment and how vision is used in the real world is far from fully understood, especially in humans. It has been suggested that comparison is the most primitive of psychophysical tasks. Thus, as a probe into these active visual behaviours, we use a same-different task: Are two physical 3D objects visually the same? This task is a fundamental cognitive ability. We pose this question to human subjects who are free to move about and examine two real objects in a physical 3D space. The experimental design is such that all behaviours are directed to viewpoint change. Without any training, our participants achieved a mean accuracy of 93.82%. No learning effect was observed on accuracy after many trials, but some effect was seen for response time, number of fixations and extent of head movement. Our probe task, even though easily executed at high-performance levels, uncovered a surprising variety of complex strategies for viewpoint control, suggesting that solutions were developed dynamically and deployed in a seemingly directed hypothesize-and-test manner tailored to the specific task. Subjects need not acquire task-specific knowledge; instead, they formulate effective solutions right from the outset, and as they engage in a series of attempts, those solutions progressively refine, becoming more efficient without compromising accuracy.

Introspective inference counteracts perceptual distortion.

Introspective agents can recognize the extent to which their internal perceptual experiences deviate from the actual states of the external world. This ability, also known as insight, is critically required for reality testing and is impaired in psychosis, yet little is known about its cognitive underpinnings. We develop a Bayesian modeling framework and a psychophysics paradigm to quantitatively characterize this type of insight while people experience a motion after-effect illusion. People can incorporate knowledge about the illusion into their decisions when judging the actual direction of a motion stimulus, compensating for the illusion (and often overcompensating). Furthermore, confidence, reaction-time, and pupil-dilation data all show signatures consistent with inferential adjustments in the Bayesian insight model. Our results suggest that people can question the veracity of what they see by making insightful inferences that incorporate introspective knowledge about internal distortions.

Motion direction is represented as a bimodal probability distribution in the human visual cortex.

Humans infer motion direction from noisy sensory signals. We hypothesize that to make these inferences more precise, the visual system computes motion direction not only from velocity but also spatial orientation signals - a 'streak' created by moving objects. We implement this hypothesis in a Bayesian model, which quantifies knowledge with probability distributions, and test its predictions using psychophysics and fMRI. Using a probabilistic pattern-based analysis, we decode probability distributions of motion direction from trial-by-trial activity in the human visual cortex. Corroborating the predictions, the decoded distributions have a bimodal shape, with peaks that predict the direction and magnitude of behavioral errors. Interestingly, we observe similar bimodality in the distribution of the observers' behavioral responses across trials. Together, these results suggest that observers use spatial orientation signals when estimating motion direction. More broadly, our findings indicate that the cortical representation of low-level visual features, such as motion direction, can reflect a combination of several qualitatively distinct signals.

Poster Session: Achromatic increments and decrements are different: the relationship between scaling and discrimination.

A basic problem in psychophysics is to relate the internal representation of a stimulus to its physical intensity. In this study, we measured perceptual scales for achromatic contrast with Maximum Likelihood Difference Scaling (MLDS), using squares against a mid-grey background. Observers compared two stimulus pairs and chose the more different pair. All four squares were either achromatic increments (A+), or achromatic decrements (A-). The MLDS result was then compared with 2AFC achromatic pedestal discrimination, with pedestals and tests that were all combinations of A+ and A-. The main result is not novel: A+ and A- obey different rules. A Naka-Rushton saturating function describes the A+ MLDS result well, and the derivative of that function is proportional to the A+ pedestal discrimination for some (but not all) observers. A- MLDS and discrimination results are more complicated and are reminiscent of the classic findings of Whittle (1986, 1992). The sensitivity of A- is a cubic polynomial function of pedestal contrast. These findings will be compared with a similar study of S-cone contrast (reported at VSS 2022), which found a different type of asymmetry between S+ and S-. Presumably these increment/decrement asymmetries are due to underlying differences between ON and OFF neural pathways. One implication is that using stimuli that include both contrast signs, such as gratings and flicker, may obscure important asymmetries in the processing of contrast.

Poster Session: A unifying framework for perceptual decision-making.

Perceptual decision making (PDM) has been studied using two approaches. Threshold measurement is predominant used in psychophysics, while reaction times (RT) with associated models have been used to estimate components of PDM (i.e., drift rate). To test if these two approaches reflect overlapping mechanisms, we conducted 3 experiments: a motion, a static orientation, and a dynamic orientation task. DT is the shortest stimulus presentation time sufficient to make accurate perceptual decisions. RTs and choices were fitted by a drift diffusion model (DDM). We expected a close relationship between DTs and drift rates, allowing us to accurately predict DTs from RT. In the motion task, we found a close relation between the empirical DTs and the DTs predicted by the DDM. Surprisingly, in the static task, there was little correlation between the two; DTs, improved monotonically with higher contrast, but drift rates saturated at 6%. We hypothesize that this mismatch is due to the information being available immediately in the static task, without needing to accumulate new evidence. Thus, we developed a novel dynamic orientation task that mimics the dynamic nature of the motion task and found a similar relation between DTs and drift rates. In summary, we show a close link between DTs and drift rate for the two dynamic tasks. This result supports the conceptualization of drift rate as a proxy for perceptual sensitivity but only for task where new information becomes available over time.

The psychophysics of bouncing: Perceptual constraints, physical constraints, animacy, and phenomenal causality.

In the present study we broadly explored the perception of physical and animated motion in bouncing-like scenarios through four experiments. In the first experiment, participants were asked to categorize bouncing-like displays as physical bounce, animated motion, or other. Several parameters of the animations were manipulated, that is, the simulated coefficient of restitution, the value of simulated gravitational acceleration, the motion pattern (uniform acceleration/deceleration or constant speed) and the number of bouncing cycles. In the second experiment, a variable delay at the moment of the collision between the bouncing object and the bouncing surface was introduced. Main results show that, although observers appear to have realistic representations of physical constraints like energy conservation and gravitational acceleration/deceleration, the amount of visual information available in the scene has a strong modulation effect on the extent to which they rely on these representations. A coefficient of restitution >1 was a crucial cue to animacy in displays showing three bouncing cycles, but not in displays showing one bouncing cycle. Additionally, bouncing impressions appear to be driven by perceptual constraints that are unrelated to the physical realism of the scene, like preference for simulated gravitational attraction smaller than g and perceived temporal contiguity between the different phases of bouncing. In the third experiment, the visible opaque bouncing surface was removed from the scene, and the results showed that this did not have any substantial effect on the resulting impressions of physical bounce or animated motion, suggesting that the visual system can fill-in the scene with the missing element. The fourth experiment explored visual impressions of causality in bouncing scenarios. At odds with claims of current causal perception theories, results indicate that a passive object can be perceived as the direct cause of the motion behavior of an active object.

A model of colour appearance based on efficient coding of natural images.

An object's colour, brightness and pattern are all influenced by its surroundings, and a number of visual phenomena and "illusions" have been discovered that highlight these often dramatic effects. Explanations for these phenomena range from low-level neural mechanisms to high-level processes that incorporate contextual information or prior knowledge. Importantly, few of these phenomena can currently be accounted for in quantitative models of colour appearance. Here we ask to what extent colour appearance is predicted by a model based on the principle of coding efficiency. The model assumes that the image is encoded by noisy spatio-chromatic filters at one octave separations, which are either circularly symmetrical or oriented. Each spatial band's lower threshold is set by the contrast sensitivity function, and the dynamic range of the band is a fixed multiple of this threshold, above which the response saturates. Filter outputs are then reweighted to give equal power in each channel for natural images. We demonstrate that the model fits human behavioural performance in psychophysics experiments, and also primate retinal ganglion responses. Next, we systematically test the model's ability to qualitatively predict over 50 brightness and colour phenomena, with almost complete success. This implies that much of colour appearance is potentially attributable to simple mechanisms evolved for efficient coding of natural images, and is a well-founded basis for modelling the vision of humans and other animals.

Contrast sensitivity function in deep networks.

The contrast sensitivity function (CSF) is a fundamental signature of the visual system that has been measured extensively in several species. It is defined by the visibility threshold for sinusoidal gratings at all spatial frequencies. Here, we investigated the CSF in deep neural networks using the same 2AFC contrast detection paradigm as in human psychophysics. We examined 240 networks pretrained on several tasks. To obtain their corresponding CSFs, we trained a linear classifier on top of the extracted features from frozen pretrained networks. The linear classifier is exclusively trained on a contrast discrimination task with natural images. It has to find which of the two input images has higher contrast. The network's CSF is measured by detecting which one of two images contains a sinusoidal grating of varying orientation and spatial frequency. Our results demonstrate characteristics of the human CSF are manifested in deep networks both in the luminance channel (a band-limited inverted U-shaped function) and in the chromatic channels (two low-pass functions of similar properties). The exact shape of the networks' CSF appears to be task-dependent. The human CSF is better captured by networks trained on low-level visual tasks such as image-denoising or autoencoding. However, human-like CSF also emerges in mid- and high-level tasks such as edge detection and object recognition. Our analysis shows that human-like CSF appears in all architectures but at different depths of processing, some at early layers, while others in intermediate and final layers. Overall, these results suggest that (i) deep networks model the human CSF faithfully, making them suitable candidates for applications of image quality and compression, (ii) efficient/purposeful processing of the natural world drives the CSF shape, and (iii) visual representation from all levels of visual hierarchy contribute to the tuning curve of the CSF, in turn implying a function which we intuitively think of as modulated by low-level visual features may arise as a consequence of pooling from a larger set of neurons at all levels of the visual system.

Interaction between spatial perception and temporal perception enables preservation of cause-effect relationship: Visual psychophysics and neuronal dynamics.

INTRODUCTION: Visual perception of moving objects is integral to our day-to-day life, integrating visual spatial and temporal perception. Most research studies have focused on finding the brain regions activated during motion perception. However, an empirically validated general mathematical model is required to understand the modulation of the motion perception. Here, we develop a mathematical formulation of the modulation of the perception of a moving object due to a change in speed, under the formulation of the invariance of causality. METHODS: We formulated the perception of a moving object as the coordinate transformation from a retinotopic space onto perceptual space and derived a quantitative relationship between spatiotemporal coordinates. To validate our model, we undertook the analysis of two experiments: (i) the perceived length of the moving arc, and (ii) the perceived time while observing moving stimuli. We performed a magnetic resonance imaging (MRI) tractography investigation of subjects to demarcate the anatomical correlation of the modulation of the perception of moving objects. RESULTS: Our theoretical model shows that the interaction between visual-spatial and temporal perception, during the perception of moving object is described by coupled linear equations; and experimental observations validate our model. We observed that cerebral area V5 may be an anatomical correlate for this interaction. The physiological basis of interaction is shown by a Lotka-Volterra system delineating interplay between acetylcholine and dopamine neurotransmitters, whose concentrations vary periodically with the orthogonal phase shift between them, occurring at the axodendritic synapse of complex cells at area V5. CONCLUSION: Under the invariance of causality in the representation of events in retinotopic space and perceptual space, the speed modulates the perception of a moving object. This modulation may be due to variations of the tuning properties of complex cells at area V5 due to the dynamic interaction between acetylcholine and dopamine. Our analysis is the first significant study, to our knowledge, that establishes a mathematical linkage between motion perception and causality invariance.