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We measure the performance of five subjects in a 2-AFC slant-discrimination task for differently textured planes. As textures we used uniform lattices, randomly displaced lattices, circles (polka dots), Voronoi tessellations, plaids, 1/f noise, “coherent ” noise and a leopard skin-like texture. Our results show: (1) Improving performance with larger slants for all textures, (2) and some cases of “non-symmetrical ” performance around a particular orientation. (3) For orientations sufficiently slanted, the different textures do not elicit major differences in performance, (4) while for orientations closer to the vertical plane there are marked differences among them. (5) These differences allow a rank-order of textures to be formed according to their “helpfulness” – that is, how easy the discrimination task is when a particular texture is mapped on the plane. Polka dots tend to allow the best slant discrimination performance, noise patterns the worst. Two additional experiments were conducted to test the generality of the obtained rank-order. First, the tilt of the planes was rotated by ninety degrees. Second, the task was changed to a slant report task via probe adjustment. The results of both control experiments confirmed the texture rank-order previously obtained. We then test a number of spatial-frequency-based slant-from-texture models and discuss their shortcomings in explaining our rank-order. Finally, we comment on the importance of these results for depth perception research in general, and in particular the implications our results have for studies of cue combination (sensor fusion) using texture as one of the cues involved.- 2 – 1

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The pedestal or dipper effect is the large improvement in the detectability of a sinusoidal grating observed when it is added to a masking or pedestal grating of the same spatial frequency, orientation, and phase. We measured the pedestal effect in both broadband and notched noiseVnoise from which a 1.5-octave band centered on the signal frequency had been removed. Although the pedestal effect persists in broadband noise, it almost disappears in the notched noise. Furthermore, the pedestal effect is substantial when either high- or low-pass masking noise is used. We conclude that the pedestal effect in the absence of notched noise results principally from the use of information derived from channels with peak sensitivities at spatial frequencies different from that of the signal and the pedestal. We speculate that the spatial-frequency components of the notched noise above and below the spatial frequency of the signal and the pedestal prevent ‘‘off-frequency looking,’’ that is, prevent the use of information about changes in contrast carried in channels tuned to spatial frequencies that are very much different from that of the signal and the pedestal. Thus, the pedestal or dipper effect measured without notched noise appears not to be a characteristic of individual spatial-frequency-tuned channels.

INTRODUCTION There has been much recent interest in looking at the time taken to process various visual-stimulus attributes, such as colour, form and motion. It is commonly accepted that different visual attributes are processed relatively independently in separate parts of the brain (Zeki 1978; Livingstone & Hubel 1988). These different attributes may have different processing latencies. Nevertheless, we are rarely aware of such asynchronies. How can these observations be reconciled? Does the brain compensate for differences in processing time, such that a unified percept is recovered that mirrors the synchrony of real-world events? Research by Moutoussis & Zeki (1997) suggested that colour reaches our awareness faster than motion. When objects are repeatedly and rapidly changing colour (between red and green) and switching motion direction with the same frequency, then colour changes must occur ca. 80 ms after motion changes for them to be perceived as synchronous. In the framework

Eight paid volunteers who were unaware of the experimental hypotheses and the two authors participated in the experiments. Two participants did not complete observations for the paint condition, so there were only eight participants for this condition. All participants had normal or corrected to normal acuity and normal color vision as assessed by an Ishihara color-blindness test. Stimuli were presented on a computer-controlled calibrated RGB monitor with 14-bit resolution per channel and a refresh rate of 75 Hz. Participants viewed the stimuli monocularly through a small square aperture. Their head position was stabilized with a chin rest placed 86 cm from the monitor. Background patterns were simulated perspective projection images of checkerboards (see Figure 1). We generated the shadowed checkerboard by simulating a 60 % decrease in the illumination of the shadowed region. The penumbra was created with a Gaussian

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This dissertation attempts to shed new light on the mechanisms used by human subjects to extract features from visual stimuli and for their subsequent classification. A methodology combining human psychophysics and machine learning is introduced, where feature extractors are modeled using methods from unsupervised machine learning whereas supervised machine learning is considered for classification. We consider a gender classification task using stimuli drawn from the Max Planck Institute face database. Once a feature extractor is chosen and the corresponding data representation is computed, the resulting feature vector is classified using a separating hyperplane (SH) between the classes. The behavioral responses of humans to one stimulus, in our study the gender estimate and its corresponding reaction time and confidence rating, are compared and correlated to the distance of the feature vector of this stimulus to the SH. It is successfully demonstrated that machine learning can be used as a novel method to “look into the human

Abstract——The stiffness of the environment with which we come in contact is the local derivative of a force field. The boundary of an elastic field is a singular region where local stiffness is ill-defined. We found that subjects interacting with delayed force fields tend to underestimate stiffness if they do not move across the boundary. In contrast, they tend to overestimate stiffness when they move across the elastic field boundary. We propose a unifying computational model of stiffness perception based on an active process that combines the concurrent operations of a force and of a position-control system.

Running title: Interaural time differences in electric hearing Abbreviated Title: Interaural time differences in electric hearing Accepted This study examined the sensitivity of four CI listeners to ITD in different portions of four-pulse sequences in lateralization discrimination. ITD was present either in all the pulses (referred to as condition Wave), the two middle pulses (Ongoing), the first pulse (Onset), the last pulse (Offset), or both the first and last pulse (Gating). All ITD conditions were tested at different pulse rates (100, 200, 400, and 800 pulses per second, pps). Also, five normal hearing (NH) subjects were tested, listening to an acoustic simulation of CI stimulation. All CI and NH listeners were sensitive in condition Gating at all pulse rates for which they showed sensitivity in condition Wave. The sensitivity in condition Onset increased with the pulse rate for three CI listeners as well as for all NH listeners. The performance in condition Ongoing varied over the subjects. One CI listener showed sensitivity up to 800 pps, two up to 400 pps, and one at 100 pps only. The group of NH listeners showed sensitivity up to 200 pps. The result that CI listeners detect ITD from the middle pulses of short trains indicates the relevance of fine timing of stimulation pulses in lateralization and therefore in CI stimulation strategies. PACS numbers: 43.66.Pn, 43.66.Ts 2 I.