Time constancy in human perception

Estimated time contracts or dilates depending on many visual-stimulation attributes (size, speed, etc.). Here we show that when such attributes are jointly modulated so as to respect the rules of perspective, their effect on the perceived duration of moving objects depends on the presence of contextual information about viewing distance.We show that perceived duration contracts and dilates with changes in the retinal input associated with increasing distance from the observer only when the moving objects are presented in the absence of information about the viewing distance. When this information (in the form of linear perspective cues) is present, the time-contraction/dilation effect is eliminated and time constancy is preserved. This is the first demonstration of a perceptual time constancy, analogous to size constancy but in the time domain. It points to a normalization of time computation operated by the visual brain when stimulated within a quasi- ecological environment

A morphometric study of the human mandible in the Indian population for sex determination

Sex determination from bones is important in forensic investigations for establishing identity in cases of mutilated bodies. Many morphometric criteria have been laid down for various bones for sex determination in previous studies. The present study aimed at setting up some parameters of the mandible as indicators of sex in the Indian population. The length of body of the mandible, angle of the mandible and minimum ramus breadth were considered as chief parameters for sex determination from dried bones obtained from the Departments of Anatomy in two medical colleges of Punjab and Chandigarh. There was a statistically significant difference found in the diagonal length, horizontal length and minimum ramus breadth with their mean values 79.77 ± 4.68 mm, 71.99 ± 4.54 mm and 30.93 ± 2.56 mm in adult males, respectively and 73.83 ± 4.84 mm, 68.62 ± 4.78 mm and 29.57 ± 2.86 mm in adult females, respectively, whereas no significant difference was found in the mandibular angle of males and females. The parameters used for the present study gave an overall 60% accuracy in determining the sex of the mandible

Summary statistics for size over space and time

A number of studies have investigated how the visual system extracts the average feature-value of an ensemble of simultaneously or sequentially delivered stimuli. In this study we model these two processes within the unitary framework of linear systems theory. The specific feature value used in this investigation is size, which we define as the logarithm of a circle's diameter. Within each ensemble, sizes were drawn from a normal distribution. Average size discrimination was measured using ensembles of one and eight circles. These circles were presented simultaneously (display times: 13–427 ms), one at a time, or eight at a time (temporal-frequencies: 1.2–38 Hz). Thresholds for eight-item ensembles were lower than thresholds for one-item ensembles. Thresholds decreased by a factor of 1.3 for a 3,200% increase in display time, and decreased by the same factor for a 3,200% decrease in temporal frequency. Modeling and simulations show that the data are consistent with one readout of three to four items every 210 ms

Inverse modeling of cloud-aerosol interactions – Part 1: Detailed response surface analysis

This is the final version of the article. Available from EGU via the DOI in this record.New methodologies are required to probe the sensitivity of parameters describing cloud droplet activation. This paper presents an inverse modeling-based method for exploring cloud-aerosol interactions via response surfaces. The objective function, containing the difference between the measured and model predicted cloud droplet size distribution is studied in a two-dimensional framework, and presented for pseudo-adiabatic cloud parcel model parameters that are pair-wise selected. From this response surface analysis it is shown that the susceptibility of cloud droplet size distribution to variations in different aerosol physiochemical parameters is highly dependent on the aerosol environment and meteorological conditions. In general the cloud droplet size distribution is most susceptible to changes in the updraft velocity. A shift towards an increase in the importance of chemistry for the cloud nucleating ability of particles is shown to exist somewhere between marine average and rural continental aerosol regimes. We also use these response surfaces to explore the feasibility of inverse modeling to determine cloud-aerosol interactions. It is shown that the "cloud-aerosol" inverse problem is particularly difficult to solve due to significant parameter interaction, presence of multiple regions of attraction, numerous local optima, and considerable parameter insensitivity. The identifiability of the model parameters will be dependent on the choice of the objective function. Sensitivity analysis is performed to investigate the location of the information content within the calibration data to confirm that our choice of objective function maximizes information retrieval from the cloud droplet size distribution. Cloud parcel models that employ a moving-centre based calculation of the cloud droplet size distribution pose additional difficulties when applying automatic search algorithms for studying cloud-aerosol interactions. To aid future studies, an increased resolution of the region of the size spectrum associated with droplet activation within cloud parcel models, or further development of fixed-sectional cloud models would be beneficial. Despite these improvements, it is demonstrated that powerful search algorithms remain necessary to efficiently explore the parameter space and successfully solve the cloud-aerosol inverse problem.We gratefully acknowledge the financial support of the Bert Bolin Centre for Climate research. We gratefully appreciate G. J. Roelofs, IMAU, Utrecht, the Netherlands, for providing us with the pseudo-adiabatic cloud parcel model used in this study. We gratefully acknowledge Hamish Struthers valuable discussions and his help to improve the readability of the manuscript. Some of the calculations made during the course of this study have been made possible using the LISA cluster from the SARA centre for parallel computing at the University of Amsterdam, the Netherlands. AS acknowledges support from an Office of Naval Research YIP award (N00014-10-1-0811).The authors acknowledge the Swedish Environmental Monitoring Program a

Sound-Induced Flash Illusion is Resistant to Feedback Training

A single flash accompanied by two auditory beeps tends to be perceived as two flashes (Shams et al. Nature 408:788, 2000, Cogn Brain Res 14:147–152, 2002). This phenomenon is known as ‘sound-induced flash illusion.’ Previous neuroimaging studies have shown that this illusion is correlated with modulation of activity in early visual cortical areas (Arden et al. Vision Res 43(23):2469–2478, 2003; Bhattacharya et al. NeuroReport 13:1727–1730, 2002; Shams et al. NeuroReport 12(17):3849–3852, 2001, Neurosci Lett 378(2):76–81, 2005; Watkins et al. Neuroimage 31:1247–1256, 2006, Neuroimage 37:572–578, 2007; Mishra et al. J Neurosci 27(15):4120–4131, 2007). We examined how robust the illusion is by testing whether the frequency of the illusion can be reduced by providing feedback. We found that the sound-induced flash illusion was resistant to feedback training, except when the amount of monetary reward was made dependent on accuracy in performance. However, even in the latter case the participants reported that they still perceived illusory two flashes even though they correctly reported single flash. Moreover, the feedback training effect seemed to disappear once the participants were no longer provided with feedback suggesting a short-lived refinement of discrimination between illusory and physical double flashes rather than vanishing of the illusory percept. These findings indicate that the effect of sound on the perceptual representation of visual stimuli is strong and robust to feedback training, and provide further evidence against decision factors accounting for the sound-induced flash illusion

Learning curve and interobserver reproducibility evaluation of liver stiffness measurement by transient elastography:

Background/Aims: Fibroscan allows liver stiffness examination (LSE) that is well correlated with fibrosis stages. Our main objective was to evaluate LSE learning curve.Methods: LSE results of five novice observers with different medical status were compared with those of five expert observers (physicians with >100 examinations) in 250 patients with chronic liver disease. Each novice–expert pair had to blindly examine 50 consecutive patients divided into five consecutive subgroups of 10 patients. Results: In each observer group, novice–expert agreement [intraclass correlation coefficient (Ric)] for LSE results was excellent from the first to the last subgroup. Novice–expert agreement for LSE results varied with liver stiffness level: <9 kPa: Ric=0.49; ≥9 kPa: Ric=0.87. Relative difference (%) between novice and expert LSE results was independently associated with the number of valid LSE measurements, and stabilizes around 20–30% after the fourth valid measurement. In each observer group, novice–expert agreement (Ric) for LSE success rate progressively increased as a function of time. Conclusion: LSE requires no learning curve: a novice is able to obtain a reliable result after a single training session, whatever the professional status. However, success rate will progressively increase. An LSE with less than four valid measurements should not be considered as reliable

Reproducibility of Liver Stiffness Measurement by Ultrasonographic Elastometry

Background & AimsFibroscan is a noninvasive device that assesses liver fibrosis by liver stiffness evaluation (LSE) with ultrasonographic elastometry. We evaluated LSE reproducibility and its influencing factors. Methods LSE was performed by 4 experienced physicians (>100 LSEs) in 46 patients with chronic liver disease at 4 different anatomic sites. Additional LSEs were performed for ancillary aims, so that 534 LSEs were available. Results Overall interobserver agreement for LSE results was considered as excellent, with intraclass coefficient correlation (Ric) of 0.93. Low LSE level, nonrecommended sites, LSE interquartile range > 25%, and body mass index ≥25 independently decreased agreement. Thus, agreement was fair (Ric = 0.53) for LSE < 9 kilopascals and excellent (Ric = 0.90) beyond. The best measurement site for LSE reproducibility was the median axillary line on the first intercostal space under the liver dullness upper limit, with the patient lying in dorsal decubitus. When LSE results were categorized into fibrosis Metavir stages, interobserver discordance was noticed in about 25% of the cases and was the highest for F2 and F3 stages and the lowest for F4. Intraobserver (Ric = 0.94), intersite (Ric = 0.92–0.98), and interequipment (Ric = 0.92) agreements for LSE results were excellent. Preliminary standard ultrasonography or probe pressure changes did not improve interobserver agreement. Conclusions The best measurement site for LSE is the one generally used for liver biopsy. Reproducibility of LSE is globally excellent but is fair in patient with low liver stiffness. The fibrosis diagnosis by ultrasonographic elastometry in low stages or categorized into fibrosis Metavir stages must be interpreted with caution

Robust averaging protects decisions from noise in neural computations

An ideal observer will give equivalent weight to sources of information that are equally reliable. However, when averaging visual information, human observers tend to downweight or discount features that are relatively outlying or deviant (‘robust averaging’). Why humans adopt an integration policy that discards important decision information remains unknown. Here, observers were asked to judge the average tilt in a circular array of high-contrast gratings, relative to an orientation boundary defined by a central reference grating. Observers showed robust averaging of orientation, but the extent to which they did so was a positive predictor of their overall performance. Using computational simulations, we show that although robust averaging is suboptimal for a perfect integrator, it paradoxically enhances performance in the presence of “late” noise, i.e. which corrupts decisions during integration. In other words, robust decision strategies increase the brain’s resilience to noise arising in neural computations during decision-making