Models for the perception of orientation in random dot patterns

The aim of this paper is to summarize and to compare some known mathematical models of orientation perception in random dot patterns and to propose new solutions of this question. The model adequacy is judged from the previously obtained experimental results. Apart from the models based on some simple function of the coordinates of dots forming a pattern, also models derived from the so-called image function of the pattern are analysed. The latter ones were found more flexible to render the different features of experimentally obtained data, mainly in the case of orientation ambiguity for some special patterns. The stochastic variants of the deterministic models are introduced.     

On visual orientation of dot patterns

Two-dimensional normally distributed random dot patterns were used in two experiments on visual orientation estimation. In the first experiment the patterns differed in their sample correlation and in dot number. In the second one the number of dots was maintained constant but the patterns were generated as a superposition of two normally distributed orthogonal sets composed of different number of dots. In both experiments the estimated orientation depended on stimuli correlation-with increasing correlation the estimated orientation gets closer to the orientation of the least square distance axis of the pattern. Even at very low unsignificant correlations there still remained a hint about stimulus orientation which was not estimated at random. Equalizing consecutively the number of dots in the two orthogonal dot patterns during the second experiment did not result in chance performance either. The bimodal angular distributions of the obtained responses permitted to approach the problem of orientation ambiguity. The results are discussed in terms of optimization processes taking place in the visual system.     

Distortions of length perception: anisotropy of the visual field and geometric illusions

A combined influence of stimulus orientation and structure on the judgement of length was tested in psychophysical experiments. The subjects adjusted the test part of a stimulus to be equal in length to the reference part. The V-shaped stimuli (three dots, or the Oppel-Kundt figure, or one dot and two Müller-Layer wings) were generated on the monitor. In the Oppel-Kundt and Müller-Layer figures, the filled part was considered as a reference and the empty part as a test. In session of the experiments, values of errors measured as functions of orientation of the parts of the stimuli. We assume that experiments with the three-dot stimuli yielded pure characteristics of visual field anisotropy, while those with the Oppel-Kundt and Müller-Layer figures showed a combined effect of both anisotropy and illusions. The data demonstrated that illusions and anisotropy are to be interpreted as independent factors, which converge to an algebraic summation in a simultaneous manifestation.     

A model for the perception of curves in dot figures: The role of local salience of “virtual lines”

In many models of visual information processing the notion of a virtual line or dipole is introduced in order to represent the configurational information, notably length and relative orientation, between identical figure elements in figures with discrete elements. Virtual lines have proven to be very useful in predicting perceptual phenomena (Julesz et al. 1973; Stevens 1978). In the present study, virtual lines are utilized in a model which aims to predict the perception of (dotted) curves in dot figures. Clearly many possible curves, formed by adjacent virtual lines, can be constructed within a set of dots. It is proposed that already at the local level of the virtual lines each line has a perceptual salience which results from the function induced by the global dot figure. It is this local line salience or connectivity that directs further processing and determines the curves to be seen in a dot figure. The model presented is an information processing model with a clear modular design. It entails three successive levels of representation. First image functions are derived through a convolution of the input with gaussian distribution functions. Next, a discrete internal representation is extracted from the image function consisting of two primitives; blobs, representing the dots, and virtual lines, representing pairwise relations between blobs. The attributes of the blobs are their positions in the image plane, while those of the virtual lines are length, relative orientation and connectivity. At the third level, the discrete internal representation is used to predict the perceived curves. It is shown that the model has advantages over other approaches, e.g. autocorrelation and network models.     

The development of quantum dot calibration beads and quantitative multicolor bioassays in flow cytometry and microscopy

The use of fluorescence calibration beads has been the hallmark of quantitative flow cytometry. It has enabled the direct comparison of interlaboratory data as well as quality control in clinical flow cytometry. In this article, we describe a simple method for producing color-generalizable calibration beads based on streptavidin functionalized quantum dots. Based on their broad absorption spectra and relatively narrow emission, which is tunable on the basis of dot size, quantum dot calibration beads can be made for any fluorophore that matches their emission color. In an earlier publication, we characterized the spectroscopic properties of commercial streptavidin functionalized dots (Invitrogen). Here we describe the molecular assembly of these dots on biotinylated beads. The law of mass action is used to readily define the site densities of the dots on the beads. The applicability of these beads is tested against the industry standard, namely commercial fluorescein calibration beads. The utility of the calibration beads is also extended to the characterization surface densities of dot-labeled epidermal growth factor ligands as well as quantitative indicators of the binding of dot-labeled virus particles to cells.     

Creating self-illuminating quantum dot conjugates

Semiconductor quantum dots are inorganic fluorescent nanocrystals that, because of their unique optical properties compared with those of organic fluorophores, have become popular as fluorescent imaging probes. Although external light excitation is typically required for imaging with quantum dots, a new type of quantum dot conjugate has been reported that can luminesce with no need for external excitation. These self-illuminating quantum dot conjugates can be prepared by coupling of commercially available carboxylate-presenting quantum dots to the light-emitting protein Renilla luciferase. When the conjugates are exposed to the luciferase's substrate coelenterazine, the energy released by substrate catabolism is transferred to the quantum dots through bioluminescence resonance energy transfer, leading to quantum dot light emission. This protocol describes step-by-step procedures for the preparation and characterization of these self-illuminating quantum dot conjugates. The preparation process is relatively simple and can be done in less than 2 hours. The availability of self-illuminating quantum dot conjugates will provide many new possibilities for in vivo imaging and detection, such as monitoring of in vivo cell trafficking, multiplex bioluminescence imaging and new quantum dot-based biosensors.     

Corner detection in curvilinear dot grouping

Corners, or discontinuities in orientation, are one of the most salient and useful properties of contours. But how sensitive are we in detecting them, and what does this sensitivity imply about the processes by which corners can be detected. In this paper we address both of these questions, starting with the observation that changing the samplign phase of a curve changes the geometry of its discrete trace, or the set of discrete (retinotopic) points onto which the curve projects. This motivates our stimuli — dotted curves —and our experimental design: if curves are represented by dots, the placement of the dots effects whether or not corners are perceived. Specifically, we present quantitative data on sensitivity to discontinuities as a function of dot phase, and address its theoretical explanation within a two-stage model of orientation selection. Curvature plays a key role in this model, and, finally, the model and experimental data are brought together by showing that a very coarse approximation to change in curvature (or differences in local curvature estimates) is sufficent to account for the psychophysical data on sensitivity to discontinuities.     

The perception of a dotted line in noise: a model of good continuation and some experimental results

A formal model is proposed, describing how the perceptual interpretation of dot figures is guided by the Gestalt rule of good continuation. The algorithm will be restricted to figures with a collinear dot array (line) embedded in a background of randomly placed dots. The model, CODE-2, is an elaboration of the model, CODE-1, of grouping dots on the basis of the Gestalt rule of (relative) proximity, and consists of the introduction of non-circular symmetric gaussian distribution functions for the representation of the orientation dependent strength of interaction between collinear dots. Supra-threshold contours of the function, resulting from a superposition on each dot of the gaussian functions, are assumed to predict the perceptual grouping of the dots. A quantitative measure for the perceptual salience of dotted lines was defined as the contrast between the internal coherence of the line dots, and their interference with the noise dots. For 20 stimuli the CODE-2 grouping of the dots is reported, together with the results of a line-in-noise latency experiment. There was a significant correlation between the predicted saliences and the experimental results. The results support the usefulness of representing good continuation between collinear dots by non-circular symmetric gaussian distribution functions.     

Cross- and auto-correlation in early vision

Neurons that respond selectively to the orientation of visual stimuli were discovered in V1 more than 50 years ago, but it is still not fully understood how or why this is brought about. We report experiments planned to show whether human observers use cross-correlation or auto-correlation to detect oriented streaks in arrays of randomly positioned dots, expecting that this would help us to understand what David Marr called the 'computational goal' of V1. The streaks were generated by two different methods: either by sinusoidal spatial modulation of the local mean dot density, or by introducing coherent pairs of dots to create moiré patterns, as Leon Glass did. A wide range of dot numbers was used in the randomly positioned arrays, because dot density affects cross- and auto-correlation differently, enabling us to infer which method was used. This difference stems from the fact that the cross-correlation task is limited by random fluctuations in the local mean density of individual dots in the noisy array, whereas the auto-correlation task is limited by fluctuations in the numbers of randomly occurring spurious pairs having the same separation and orientation as the deliberately introduced coherent pairs. After developing a new method using graded dot luminances, we were able to extend the range of dot densities that could be used by a large factor, and convincing results were obtained indicating that the streaks generated by amplitude modulation were discriminated by cross-correlation, while those generated as moiré patterns were discriminated by auto-correlation. Though our current results only apply to orientation selectivity, it is important to know that early vision can do more than simple filtering, for evaluating auto-correlations opens the way to more interesting possibilities, such as the detection of symmetries and suspicious coincidences.     

Loop-closure events during protein folding: rationalizing the shape of Phi-value distributions

In the past years, the folding kinetics of many small single-domain proteins has been characterized by mutational Phi-value analysis. In this article, a simple, essentially parameter-free model is introduced which derives folding routes from native structures by minimizing the entropic loop-closure cost during folding. The model predicts characteristic folding sequences of structural elements such as helices and beta-strand pairings. Based on few simple rules, the kinetic impact of these structural elements is estimated from the routes and compared to average experimental Phi-values for the helices and strands of 15 small, well-characterized proteins. The comparison leads on average to a correlation coefficient of 0.62 for all proteins with polarized Phi-value distributions, and 0.74 if distributions with negative average Phi-values are excluded. The diffuse Phi-value distributions of the remaining proteins are reproduced correctly. The model shows that Phi-value distributions, averaged over secondary structural elements, can often be traced back to entropic loop-closure events, but also indicates energetic preferences in the case of a few proteins governed by parallel folding processes.     

Division orientation: disentangling shape and mechanical forces

Oriented cell divisions are essential for the generation of cell diversity and for tissue shaping during morphogenesis. Cells in tissues are mechanically linked to their neighbors, upon which they impose, and from which they experience, physical force. Recent work in multiple systems has revealed that tissue-level physical forces can influence the orientation of cell division. A long-standing question is whether forces are communicated to the spindle orienting machinery via cell shape or directly via mechanosensing intracellular machinery. In this article, we review the current evidence from diverse model systems that show spindles are oriented by tissue-level physical forces and evaluate current models and molecular mechanisms proposed to explain how the spindle orientation machinery responds to extrinsic force.     

Control of the mitotic cleavage plane by local epithelial topology

For nearly 150 years, it has been recognized that cell shape strongly influences the orientation of the mitotic cleavage plane (e.g., Hofmeister, 1863). However, we still understand little about the complex interplay between cell shape and cleavage-plane orientation in epithelia, where polygonal cell geometries emerge from multiple factors, including cell packing, cell growth, and cell division itself. Here, using mechanical simulations, we show that the polygonal shapes of individual cells can systematically bias the long-axis orientations of their adjacent mitotic neighbors. Strikingly, analyses of both animal epithelia and plant epidermis confirm a robust and nearly identical correlation between local cell topology and cleavage-plane orientation in vivo. Using simple mathematics, we show that this effect derives from fundamental packing constraints. Our results suggest that local epithelial topology is a key determinant of cleavage-plane orientation, and that cleavage-plane bias may be a widespread property of polygonal cell sheets in plants and animals.     

Can vector summation describe the orientation system of juvenile ospreys and honey buzzards? – An analysis of ring recoveries and satellite tracking

Juvenile bird migrants are generally believed to use a clock‐and‐compass migratory orientation strategy. According to such a strategy migrants accomplish their migration by flying a number of successive flight steps with direction and number of steps controlled by an endogenous programme. One powerful way of testing this is by comparing predictions from a model of such a strategy with observed patterns. We used data from ringing and satellite‐based radio telemetry to investigate the orientation system of juvenile ospreys (Pandion haliaetus) and honey buzzards (Pernis apivorus) migrating from Sweden to tropical west Africa. The ring recoveries showed a much larger scatter in the orientation of ospreys than of honey buzzards, but there was only a slight such difference in the satellite tracks. These tracks of individuals of both species were rather straight with a high directional concentration per step. The honey buzzard data showed a close fit to a simple vector summation model, which is expected if birds follow a clock‐and‐compass strategy. However, the osprey data did not fit such a simple model, as ring recoveries showed a significantly greater deviation at short distances than predicted on the basis of long distance data. Satellite tracking also indicated less concentrated orientation on short distances. The pattern observed for the osprey can generally be explained by an extended vector summation model, including an important element of pre‐migration dispersal. The existence of extensive dispersal in the osprey stands in contrast to the apparent absence of such dispersal in the honey buzzard. The explanation for this difference between the species is unclear. The model of orientation by vector summation is very sensitive to the existence of differences in mean direction between individuals. Assuming such differences, as tentatively indicated by the satellite tracking data, makes simple compass orientation by vector summation inconsistent with the distribution of ring recoveries at long distances, with a high proportion of misoriented birds falling outside the normal winter range.     

Graphical Aids to the Estimation and Discrimination of Uncertain Numerical Data

This research investigates the performance of graphical dot arrays designed to make discrimination of relative numerosity as effortless as possible at the same time as making absolute (quantitative) numerosity estimation as effortful as possible. Comparing regular, random, and hybrid (randomized regular) configurations of dots, the results indicate that both random and hybrid configurations reduce absolute numerosity estimation precision, when compared with regular dots arrays. However, discrimination of relative numerosity is significantly more accurate for hybrid dot arrays than for random dot arrays. Similarly, human subjects report significantly lower levels of subjective confidence in judgments when using hybrid dot configurations as compared with regular configurations; and significantly higher levels of subjective confidence as compared with random configurations. These results indicate that data graphics based on the hybrid, randomized-regular configurations of dots are well-suited to applications that require decisions to be based on numerical data in which the absolute quantities are less certain than the relative values. Examples of such applications include decision-making based on the outputs of empirically-based mathematical models, such as health-related policy decisions using data from predictive epidemiological models.     

量子点在癌症研究中的应用

半导体量子点具有长时间、多目标和灵敏度高等独特的光化学性质,这些特性使量子点成为细胞标记和生物应用中得到了广泛的应用。利用量子点目标定位癌细胞,对于寻找癌变部位具有指导的作用。近年来,利用量子点作为光动力学治疗癌症的能量供体也得到了一定的研究。简单地介绍了量子点独特的光学性质,并从量子点标记癌细胞、可视化癌细胞表面功能和在光动力学治疗癌症等方面综述了量子点在癌症诊断和治疗中的应用。     

The influence of two-dimensional stimulus properties in a reconstruction task with minimal information stimuli

Effects of viewpoint that are typically found in shape recognition tasks have been interpreted in the past as strong evidence against approaches based on the use of geometric invariants by the human visual system. At first sight, the use of such invariants would indeed predict shape recognition to be viewpoint independent. It has been argued before, however, that the visual estimation of invariants need not itself be invariant. Changes of viewpoint introduce changes in 2D stimulus features. The latter may make the estimation of invariants by the visual system more or less difficult. The present study explores how such 2D features influence estimation distributions in a reconstruction paradigm. Subjects were shown four coplanar dots. They were asked to estimate the position of one of the dots relative to the three others on the basis of a slanted version of the configuration. An estimation distribution was obtained for every position of the dot to be estimated. Biases in these distributions indicated that subjects performed the task by using 2D reference axes that were unambiguously identifiable in both the images of the dot pattern.     

Visualization of functional rotor proteins of the bacterial flagellar motor in the cell membrane

The bacterial flagellar motor is a rotary motor driven by the electrochemical potentials of specific ions across the cell membrane. Direct interactions between the rotor protein FliG and the stator protein MotA are thought to generate the rotational torque. Here, we used total internal reflection fluorescent microscopy to observe the localization of green fluorescent protein (GFP)-fused FliG in Escherichia coli cells. We identified three types of fluorescent punctate signals: immobile dots, mobile dots that exhibited simple diffusion, and mobile dots that exhibited restricted diffusion. When GFP-FliG was expressed in a DeltafliG background, most of the cells were not mobile. When the cells were tethered to a glass side, however, rotating cells were commonly observed and a single fluorescent dot was always observed at the rotational center of the tethered cell. These fluorescent dots were likely positions at which functional GFP-FliG had been incorporated into a flagellar motor. Our results suggest that flagellar basal bodies diffuse in the cytoplasmic membrane until the axial structure and/or other structures assemble.     

Mitochondrial heterogeneity,metabolic scaling and cell death

Heterogeneity in mitochondrial content has been previously suggested as a major contributor to cellular noise, with multiple studies indicating its direct involvement in biomedically important cellular phenomena. A recently published dataset explored the connection between mitochondrial functionality and cell physiology, where a non‐linearity between mitochondrial functionality and cell size was found. Using mathematical models, we suggest that a combination of metabolic scaling and a simple model of cell death may account for these observations. However, our findings also suggest the existence of alternative competing hypotheses, such as a non‐linearity between cell death and cell size. While we find that the proposed non‐linear coupling between mitochondrial functionality and cell size provides a compelling alternative to previous attempts to link mitochondrial heterogeneity and cell physiology, we emphasise the need to account for alternative causal variables, including cell cycle, size, mitochondrial density and death, in future studies of mitochondrial physiology.     

含镉量子点的毒性研究进展

含镉量子点是典型的量子点,近年来受到广泛研究。含镉量子点的潜在毒性是其在生物成像及生物医药方面应用和发展的关键制约因素,因此,对其毒性作用的研究具有重要意义。目前对含镉量子点的体外毒性研究主要集中在人肝癌细胞(HepG2)、神经分泌细胞(PC12)等细胞实验及斑马鱼胚胎体外培养实验。体内毒性研究包括小鼠等动物实验。这些研究证实,量子点对HepG2等细胞系和小鼠、贻贝等动物均具细胞毒性。研究者们普遍认为,量子点是通过释放其组成中的重金属,诱导生物体产生活性氧自由基,进而引发细胞凋亡或自噬,但对量子点的具体毒性作用机制并不完全清楚。该文对含镉量子点的体内和体外毒性研究工作进展进行了综述,包括含镉量子点对肝肾细胞、神经细胞、血液细胞及免疫细胞等体外毒性研究工作,对陆生及水生动物等的体内毒性研究工作,旨在更好、更全面地评估含镉量子点的毒性,为今后对量子点的毒性作用机制研究提供方向,促进含镉量子点在生物医学方面的发展和应用。     

Inhibition, spike threshold, and stimulus selectivity in primary visual cortex

Ever since Hubel and Wiesel described orientation selectivity in the visual cortex, the question of how precise selectivity emerges has been marked by considerable debate. There are essentially two views of how selectivity arises. Feed-forward models rely entirely on the organization of thalamocortical inputs. Feedback models rely on lateral inhibition to refine selectivity relative to a weak bias provided by thalamocortical inputs. The debate is driven by two divergent lines of evidence. On the one hand, many response properties appear to require lateral inhibition, including precise orientation and direction selectivity and crossorientation suppression. On the other hand, intracellular recordings have failed to find consistent evidence for lateral inhibition. Here we demonstrate a resolution to this paradox. Feed-forward models incorporating the intrinsic nonlinear properties of cortical neurons and feed-forward circuits (i.e., spike threshold, contrast saturation, and spike-rate rectification) can account for properties that have previously appeared to require lateral inhibition.