Perceptual Measurements, Distances and Metrics

Perception is often viewed as a process that transforms physical variables, external to an observer, into internal psychological variables. Such a process can be modeled by a function coined perceptual scale. The perceptual scale can be deduced from psychophysical measurements that consist in comparing the relative differences between stimuli (i.e. difference scaling experiments). However, this approach is often overlooked by the modeling and experimentation communities. Here, we demonstrate the value of measuring the perceptual scale of classical (spatial frequency, orientation) and less classical physical variables (interpolation between textures) by embedding it in recent probabilistic modeling of perception. First, we show that the assumption that an observer has an internal representation of univariate parameters such as spatial frequency or orientation while stimuli are high-dimensional does not lead to contradictory predictions when following the theoretical framework. Second, we show that the measured perceptual scale corresponds to the transduction function hypothesized in this framework. In particular, we demonstrate that it is related to the Fisher information of the generative model that underlies perception and we test the predictions given by the generative model of different stimuli in a set a of difference scaling experiments. Our main conclusion is that the perceptual scale is mostly driven by the stimulus power spectrum. Finally, we propose that this measure of perceptual scale is a way to push further the notion of perceptual distances by estimating the perceptual geometry of images i.e. the path between images instead of simply the distance between those.Comment: 15 pages, 6 figures, 5 appendi

Organisation of audio-visual three-dimensional space

Le terme stéréopsie renvoie à la sensation de profondeur qui est perçue lorsqu une scène est vue de manière binoculaire. Le système visuel s appuie sur les disparités horizontales entre les images projetées sur les yeux gauche et droit pour calculer une carte des différentes profondeurs présentes dans la scène visuelle. Il est communément admis que le système stéréoscopique est encapsulé et fortement contraint par les connexions neuronales qui s étendent des aires visuelles primaires (V1/V2) aux aires intégratives des voies dorsales et ventrales (V3, cortex temporal inférieur, MT). A travers quatre projets expérimentaux, nous avons étudié comment le système visuel utilise la disparité binoculaire pour calculer la profondeur des objets. Nous avons montré que le traitement de la disparité binoculaire peut être fortement influencé par d autres sources d information telles que l occlusion binoculaire ou le son. Plus précisément, nos résultats expérimentaux suggèrent que : (1) La stéréo de da Vinci est résolue par un mécanisme qui intègre des processus de stéréo classiques (double fusion), des contraintes géométriques (les objets monoculaires sont nécessairement cachés à un œil, par conséquent ils sont situés derrière le plan de l objet caché) et des connaissances à priori (une préférence pour les faibles disparités). (2) Le traitement du mouvement en profondeur peut être influencé par une information auditive : un son temporellement corrélé avec une cible définie par le mouvement stéréo peut améliorer significativement la recherche visuelle. Les détecteurs de mouvement stéréo sont optimalement adaptés pour détecter le mouvement 3D mais peu adaptés pour traiter le mouvement 2D. (3) Grouper la disparité binoculaire avec un signal auditif dans une dimension orthogonale (hauteur tonale) peut améliorer l acuité stéréo d approximativement 30%Stereopsis refers the perception of depth that arises when a scene is viewed binocularly. The visual system relies on the horizontal disparities between the images from the left and right eyes to compute a map of the different depth values present in the scene. It is usually thought that the stereoscopic system is encapsulated and highly constrained by the wiring of neurons from the primary visual areas (V1/V2) to higher integrative areas in the ventral and dorsal streams (V3, inferior temporal cortex, MT). Throughout four distinct experimental projects, we investigated how the visual system makes use of binocular disparity to compute the depth of objects. In summary, we show that the processing of binocular disparity can be substantially influenced by other types of information such as binocular occlusion or sound. In more details, our experimental results suggest that: (1) da Vinci stereopsis is solved by a mechanism that integrates classic stereoscopic processes (double fusion), geometrical constraints (monocular objects are necessarily hidden to one eye, therefore they are located behind the plane of the occluder) and prior information (a preference for small disparities). (2) The processing of motion-in-depth can be influenced by auditory information: a sound that is temporally correlated with a stereomotion defined target can substantially improve visual search. Stereomotion detectors are optimally suited to track 3D motion but poorly suited to process 2D motion. (3) Grouping binocular disparity with an orthogonal auditory signal (pitch) can increase stereoacuity by approximately 30%PARIS5-Bibliotheque electronique (751069902) / SudocSudocFranceF

Attractive and repulsive visual aftereffects depend on stimulus contrast

Visual perception has been described as a dynamic process where incoming visual information is combined with what has been seen before to form the current percept. Such a process can result in multiple visual aftereffects that can be attractive toward or repulsive away from past visual stimulation. A lot of research has been conducted on what functional role the mechanisms that produce these aftereffects may play. However, there is a lack of understanding of the role of stimulus uncertainty on these aftereffects. In this study, we investigate how the contrast of a stimulus affects the serial aftereffects it induces and how the stimulus itself is affected by these effects depending on its contrast. We presented human observers with a series of Gabor patches and monitored how the perceived orientation of stimuli changed over time with the systematic manipulation of orientation and contrast of presented stimuli. We hypothesized that repulsive serial effects would be stronger for the judgment of high-contrast than low-contrast stimuli, but the other way around for attractive serial effects. Our experimental findings confirm such a strong interaction between contrast and sign of aftereffects. We present a Bayesian model observer that can explain this interaction based on two principles, the dynamic changes of orientation-tuned channels in short timescales and the slow integration of prior information over long timescales. Our findings have strong implications for our understanding of orientation perception and can inspire further work on the identification of its neural mechanisms

Measuring uncertainty in human visual segmentation

Segmenting visual stimuli into distinct groups of features and visual objects is central to visual function. Classical psychophysical methods have helped uncover many rules of human perceptual segmentation, and recent progress in machine learning has produced successful algorithms. Yet, the computational logic of human segmentation remains unclear, partially because we lack well-controlled paradigms to measure perceptual segmentation maps and compare models quantitatively. Here we propose a new, integrated approach: given an image, we measure multiple pixel-based same--different judgments and perform model--based reconstruction of the underlying segmentation map. The reconstruction is robust to several experimental manipulations and captures the variability of individual participants. We demonstrate the validity of the approach on human segmentation of natural images and composite textures. We show that image uncertainty affects measured human variability, and it influences how participants weigh different visual features. Because any putative segmentation algorithm can be inserted to perform the reconstruction, our paradigm affords quantitative tests of theories of perception as well as new benchmarks for segmentation algorithms.Comment: 27 pages, 9 figures, 4 appendix, 3 figures in appendi

Comparison of perceptual and motor latencies via anticipatory and reactive response times.

To compare the timing of perceptual and motor decisions, distinct tasks have been designed, all of which have yielded systematic differences between these two moments. These observations have been taken as evidence of a sensorimotor dissociation. Inasmuch as the distinction between perceptual and motor decision moments is conceptually warranted, this conclusion remains debatable, since the observed differences may reflect the dissimilarity between the stimulations/tasks used to assess them. Here, we minimize such dissimilarities by comparing response time (RT) and anticipatory RT (ART), an alternative technique with which to infer the relative perceptual decision moments. Observers pressed a key either in synchrony with the third of a sequence of three stimuli appearing at a constant pace (ART) or in response to the onset of this third stimulus presented at a random interval after the second (RT). Hence, the two stimulation sequences were virtually identical. Both the mean and the variance of RT were affected by stimulus intensity about 1.5 times more than were the mean and the variance of ART. Within the framework of two simple integration-to-bound models, these findings are compatible with the hypothesis that perceptual and motor decisions operate on the same internal signal but are based on distinct criteria, with the perceptual criterion lower than the motor one

Confidence at the limits of human nested cognition

Metacognition is the ability to weigh the quality of our own cognition, such as the confidence that our perceptual decisions are correct. Here we ask whether metacognitive performance can itself be evaluated or else metacognition is the ultimate reflective human faculty. Building upon a classic visual perception task, we show that human observers are able to produce nested, above-chance judgements on the quality of their decisions at least up to the fourth order (i.e. meta-meta-meta-cognition). A computational model can account for this nested cognitive ability if evidence has a high-resolution representation, and if there are two kinds of noise, including recursive evidence degradation. The existence of fourth-order sensitivity suggests that the neural mechanisms responsible for second-order metacognition can be flexibly generalized to evaluate any cognitive process, including metacognitive evaluations themselves. We define the theoretical and practical limits of nested cognition and discuss how this approach paves the way for a better understanding of human self-regulation

The prediction of visual stimuli influences auditory loudness discrimination

The brain combines information from different senses to improve performance on perceptual tasks. For instance, auditory processing is enhanced by the mere fact that a visual input is processed simultaneously. However, the sensory processing of one modality is itself subject to diverse influences. Namely, perceptual processing depends on the degree to which a stimulus is predicted. The present study investigated the extent to which the influence of one processing pathway on another pathway depends on whether or not the stimulation in this pathway is predicted. We used an action–effect paradigm to vary the match between incoming and predicted visual stimulation. Participants triggered a bimodal stimulus composed of a Gabor and a tone. The Gabor was either congruent or incongruent compared to an action–effect association that participants learned in an acquisition phase.We tested the influence of action–effect congruency on the loudness perception of the tone. We observed that an incongruent–task-irrelevant Gabor stimulus increases participant’s sensitivity to loudness discrimination. An identical result was obtained for a second condition in which the visual stimulus was predicted by a cue instead of an action. Our results suggest that prediction error is a driving factor of the crossmodal interplay between vision and audition

DynTex: A real-time generative model of dynamic naturalistic luminance textures

The visual systems of animals work in diverse and constantly changing environments where organism survival requires effective senses. To study the hierarchical brain networks that perform visual information processing, vision scientists require suitable tools, and Motion Clouds (MCs)—a dense mixture of drifting Gabor textons—serve as a versatile solution. Here, we present an open toolbox intended for the bespoke use of MC functions and objects within modeling or experimental psychophysics contexts, including easy integration within Psychtoolbox or PsychoPy environments. The toolbox includes output visualization via a Graphic User Interface. Visualizations of parameter changes in real time give users an intuitive feel for adjustments to texture features like orientation, spatiotemporal frequencies, bandwidth, and speed. Vector calculus tools serve the frame-by-frame autoregressive generation of fully controlled stimuli, and use of the GPU allows this to be done in real time for typical stimulus array sizes. We give illustrative examples of experimental use to highlight the potential with both simple and composite stimuli. The toolbox is developed for, and by, researchers interested in psychophysics, visual neurophysiology, and mathematical and computational models. We argue the case that in all these fields, MCs can bridge the gap between well- parameterized synthetic stimuli like dots or gratings and more complex and less controlled natural videos