Cue combination in the motion correspondence problem

Image motion is a primary source of visual information about the world. However, before this information can be used the visual system must determine the spatio-temporal displacements of the features in the dynamic retinal image, which originate from objects moving in space. This is known as the motion correspondence problem. We investigated whether cross-cue matching constraints contribute to the solution of this problem, which would be consistent with physiological reports that many directionally selective cells in the visual cortex also respond to additional visual cues. We measured the maximum displacement limit (Dmax) for two-frame apparent motion sequences. Dmax increases as the number of elements in such sequences decreases. However, in our displays the total number of elements was kept constant while the number of a subset of elements, defined by a difference in contrast polarity, binocular disparity or colour, was varied. Dmax increased as the number of elements distinguished by a particular cue was decreased. Dmax was affected by contrast polarity for all observers, but only some observers were influenced by binocular disparity and others by colour information. These results demonstrate that the human visual system exploits local, cross-cue matching constraints in the solution of the motion correspondence problem.     

Orientation variance as a quantifier of structure in texture

I consider how structure is derived from texture containing changes in orientation over space, and propose that multi-local orientation variance (the average orientation variance across a series of discrete images locales) is an estimate of the degree of organization that is useful both for spatial scale selection and for discriminating structure from noise. The oriented textures used in this paper are Glass patterns, which contain structure at a narrow range of scales. The effect of adding noise to Glass patterns, on a structure versus noise task (Maloney et al., 1987), is compared to discrimination based on orientation variance and template matching (i.e. having prior knowledge of the target's orientation structure). At all but very low densities, the variance model accounts well for human data. Next, both models' estimates of tolerable orientation variance are shown to be broadly consistent with human discrimination of texture from noise. However, neither model can account for subjects' lower tolerance to noise for translational patterns than other (e.g. rotational) patterns. Finally, to investigate how well these structural measures preserve local orientation discontinuities, I show that the presence of a patch of unstructured dots embedded in a Glass pattern produces a change in multi-local orientation variance that is sufficient to account for human detection (Hel Or and Zucker, 1989). Together, these data suggest that simple orientation statistics could drive a range of 'texture tasks', although the dependency of noise resistance on the pattern type (rotation, translation, etc.) remains to be accounted for.     

Motion detection in human vision: a unifying approach based on energy and features

Most studies of human motion perception have been based on the implicit assumption that the brain has only one motion-detection system, or at least that only one is operational in any given instance. We show, in the context of direction perception in spatially filtered two-frame random-dot kinematograms, that two quite different mechanisms operate simultaneously in the detection of such patterns. One mechanism causes reversal of the perceived direction (reversed-phi motion) when the image contrast is reversed between frames, and is highly dependent on the spatial-frequency content of the image. These characteristics are both signatures of detection based on motion energy. The other mechanism does not produce reversed-phi motion and is unaffected by spatial filtering. This appears to involve the tracking of unsigned complex spatial features. The perceived direction of a filtered dot pattern typically reflects a mixture of the two types of behaviour in any given instance. Although both types of mechanism have previously been invoked to explain the perception of motion of different types of image, the simultaneous involvement of two mechanisms in the detection of the same simple rigid motion of a pattern suggests that motion perception in general results from a combination of mechanisms working simultaneously on different principles in the same circumstances.     

Self-Organized Shape and Frontal Density of Fish Schools

Models of swarming (based on avoidance, alignment and attraction) produce patterns of behaviour also seen in schools of fish. However, the significance of such similarities has been questioned, because some model assumptions are unrealistic [e.g. speed in most models is constant with random error, the perception is global and the size of the schools that have been studied is small (up to 128 individuals)]. This criticism also applies to our former model, in which we demonstrated the emergence of two patterns of spatial organization, i.e. oblong school form and high frontal density, which are supposed to function as protection against predators. In our new model we respond to this criticism by making the following improvements: individuals have a preferred ‘cruise speed’ from which they can deviate in order to avoid others or to catch up with them. Their range of perception is inversely related to density, with which we take into account that high density limits the perception of others that are further away. Swarm sizes range from 10 to 2000 individuals. The model is three‐dimensional. Further, we show that the two spatial patterns (oblong shape and high frontal density) emerge by self‐organization as a side‐effect of coordination at two speeds (of two or four body lengths per second) for schools of sizes above 20. Our analysis of the model leads to the development of a new set of hypotheses. If empirical data confirm these hypotheses, then in a school of real fish these patterns may arise as a side‐effect of their coordination in the same way as in the model.     

Visual motion induces a forward prediction of spatial pattern

Cortical motion analysis continuously encodes image velocity but might also be used to predict future patterns of sensory input along the motion path. We asked whether this predictive aspect of motion is exploited by the human visual system. Targets can be more easily detected at the leading as compared to the trailing edge of motion [1], but this effect has been attributed to a nonspecific boost in contrast gain at the leading edge, linked to motion-induced shifts in spatial position [1-4]. Here we show that the detectability of a local sinusoidal target presented at the ends of a region containing motion is phase dependent at the leading edge, but not at the trailing edge. These two observations rule out a simple gain control mechanism that modulates contrast energy and passive filtering explanations, respectively. By manipulating the relative orientation of the moving pattern and target, we demonstrate that the resulting spatial variation in detection threshold along the edge closely resembles the superposition of sensory input and an internally generated predicted signal. These findings show that motion induces a forward prediction of spatial pattern that combines with the cortical representation of the future stimulus.     

Symmetry: Modeling the Effects of Masking Noise,Axial Cueing and Salience

Symmetry detection is an interesting probe of pattern processing because it requires the matching of novel patterns without the benefit of prior recognition. However, there is evidence that prior knowledge of the axis location plays an important role in symmetry detection. We investigated how the prior information about the symmetry axis affects symmetry detection under noise-masking conditions. The target stimuli were random-dot displays structured to be symmetric about vertical, horizontal, or diagonal axes and viewed through eight apertures (1.2° diameter) evenly distributed around a 6° diameter circle. The information about axis orientation was manipulated by (1) cueing of axis orientation before the trial and (2) varying axis salience by including or excluding the axis region within the noise apertures. The percentage of correct detection of the symmetry was measured at for a range of both target and masking noise densities. The threshold vs. noise density function was flat at low noise density and increased with a slope of 0.75–0.8 beyond a critical density. Axis cueing reduced the target threshold 2–4fold at all noise densities while axis salience had an effect only at high noise density. Our results are inconsistent with an ideal observer or signal-to-noise account of symmetry detection but can be explained by a multiple-channel model is which the response in each channel is the ratio between the nonlinear transform of the responses of sets of early symmetry detectors and the sum of external and intrinsic sources of noise.     

Detection of coloured patterns by honeybees through chromatic and achromatic cues

We asked whether the detection range of two-coloured centre-surround patterns differs from that of single-coloured targets. Honeybees Apis mellifera were trained to distinguish between the presence and absence of a single-coloured disc or a coloured pattern at different visual angles. The patterns presented colours which were either different in chromatic and L-receptor contrasts to the background, equal in chromatic but different in L-receptor contrasts, or vice-versa. Patterns with colours presenting only chromatic contrast were also tested. Patterns with higher L-receptor contrast in its outer than in its inner element were better detected than patterns with a reversed L-contrast distribution. However, both were detected worse than single-coloured discs of the respective colours. When the L-receptor contrast was the same for both elements, the detection range of the two-coloured and single-coloured targets was the same. Patterns whose colours lacked L-receptor contrast were detected just as single-coloured targets of the same colours. These results demonstrate that both chromatic and L-receptor contrasts mediate the detection of coloured patterns and that particular distributions of L-receptor contrast within a target are better detected than others. This finding is consistent with the intervention of neurons with centre-surround receptive fields in the detection of coloured patterns.     

Genomewide Transmission/Disequilibrium Testing-Consideration of the Genotypic Relative Risks at Disease Loci

Genomewide association studies are set to become the tool of the future for detection of small-effect genes in complex diseases. It will therefore be necessary to calculate sufficient sample sizes with which to perform them. In this paper I illustrate how to calculate the required number of families for general genotypic relative risks (GRRs). I show the superior sensitivity of the genomewide association study over the standard genomewide affected-sib-pair linkage analysis, for a range of different underlying GRR patterns. I also illustrate the extent of change in the sample sizes that is necessary for a genomewide association analysis depending on the pattern of the GRRs at the disease locus. In many cases, the comparative numbers of families required under different genetic mechanisms vary by several orders of magnitude. These sometimes dramatic differences have important implications for the determination of the size of the collection of samples prior to analysis and for the types of effects that are likely--and unlikely--to be detected by such an analysis.     

Combined influence of substrate stiffness and surface topography on the antiadhesive properties of Acr-sP(EO-stat-PO) hydrogels

Biomaterials that prevent nonspecific protein adsorption and cell adhesion are of high relevance for diverse applications in tissue engineering and diagnostics. One of the most widely applied materials for this purpose is Poly(ethylene glycol) (PEG). We have investigated how micrometer line topography and substrate elasticity act upon the antiadhesive properties of PEG-based hydrogels. In our studies we apply bulk hydrogel cross-linked from star-shaped poly(ethylene oxide-stat-propylene oxide) macromonomers. Substrate surfaces were topographically patterned via replica molding. Additionally, the mechanical properties were altered by variations in the cross-linking density. Surface patterns with dimensions in the range of the cells' own size, namely 10 μm wide grooves, induced significant cell adhesion and spreading on the Acr-sP(EO-stat-PO) hydrogels. In contrast, there was only little adhesion to smaller and larger pattern sizes and no adhesion at all on the smooth substrates, regardless the rigidity of the gel. The effect of varied substrate stiffness on cell behavior was only manifest in combination with topography. Softer substrates with line patterns lead to significantly higher cell adhesion and spreading than stiff substrates. We conclude that the physical and mechanical surface characteristics can eliminate the nonadhesive properties of PEG-based hydrogels to a large extent. This has to be taken into account when designing surfaces for biomedical application such as scaffolds for tissue engineering which rely on the inertness of PEG.     

Binary patterning of polar and nonpolar amino acids in the sequences and structures of native proteins

Protein sequences can be represented as binary patterns of polar (○) and nonpolar (?) amino acids. These binary sequence patterns are categorized into two classes: Class A patterns match the structural repeat of an idealized amphiphilic α-helix (3.6 residues per turn), and class B patterns match the structural repeat of an idealized amphiphilic β-strand (2 residues per turn). The difference between these two classes of sequence patterns has led to a strategy for de novo protein design based on binary patterning of polar and nonpolar amino acids. Here we ask whether similar binary patterning is incorporated in the sequences and structures of natural proteins. Analysis of the Protein Data Bank demonstrates the following. (1) Class A sequence patterns occur considerably more frequently in the sequences of natural proteins than would be expected at random, but class B patterns occur less often than expected. (2) Each pattern is found predominantly in the secondary structure expected from the binary strategy for protein design. Thus, class A patterns are found more frequently in α-helices than in β-strands, and class B patterns are found more frequently in β-strands than in α-helices. (3) Among the α-helices of natural proteins, the most commonly used binary patterns are indeed the class A patterns. (4) Among all β-strands in the database, the most commonly used binary patterns are not the expected class B patterns. (5) However, for solvent-exposed β-strands, the correlation is striking: All β-strands in the database that contain the class B patterns are exposed to solvent. (6) The bias of class A patterns for α-structure over β-structure and the bias of class B patterns for β-structure over α-structure are significant, not merely when compared to other binary patterns of polar (○) and nonpolar (?) amino acids, but also when compared to the full range of sequences in the database. The implications for the design of novel proteins are discussed.     

Influence of Correspondence Noise and Spatial Scaling on the Upper Limit for Spatial Displacement in Fully-Coherent Random-Dot Kinematogram Stimuli

Correspondence noise is a major factor limiting direction discrimination performance in random-dot kinematograms [1]. In the current study we investigated the influence of correspondence noise on Dmax, which is the upper limit for the spatial displacement of the dots for which coherent motion is still perceived. Human direction discrimination performance was measured, using 2-frame kinematograms having leftward/rightward motion, over a 200-fold range of dot-densities and a four-fold range of dot displacements. From this data Dmax was estimated for the different dot densities tested. A model was proposed to evaluate the correspondence noise in the stimulus. This model summed the outputs of a set of elementary Reichardt-type local detectors that had receptive fields tiling the stimulus and were tuned to the two directions of motion in the stimulus. A key assumption of the model was that the local detectors would have the radius of their catchment areas scaled with the displacement that they were tuned to detect; the scaling factor k linking the radius to the displacement was the only free parameter in the model and a single value of k was used to fit all of the psychophysical data collected. This minimal, correspondence-noise based model was able to account for 91% of the variability in the human performance across all of the conditions tested. The results highlight the importance of correspondence noise in constraining the largest displacement that can be detected.     

Sensitivity of the Goldfish Motion Detection System Revealed by Incoherent Random Dot Stimuli: Comparison of Behavioural and Neuronal Data

Background

Global motion detection is one of the most important abilities in the animal kingdom to navigate through a 3-dimensional environment. In the visual system of teleost fish direction-selective neurons in the pretectal area (APT) are most important for global motion detection. As in all other vertebrates these neurons are involved in the control of slow phase eye movements during gaze stabilization. In contrast to mammals cortical pathways that might influence motion detection abilities of the optokinetic system are missing in teleost fish.

Results

To test global motion detection in goldfish we first measured the coherence threshold of random dot patterns to elicit horizontal slow phase eye movements. In addition, the coherence threshold of the optomotor response was determined by the same random dot patterns. In a second approach the coherence threshold to elicit a direction selective response in neurons of the APT was assessed from a neurometric function. Behavioural thresholds and neuronal thresholds to elicit slow phase eye movements were very similar, and ranged between 10% and 20% coherence. In contrast to these low thresholds for the optokinetic reaction and APT neurons the optomotor response could only be elicited by random dot patterns with coherences above 40%.

Conclusion

Our findings suggest a high sensitivity for global motion in the goldfish optokinetic system. Comparison of neuronal and behavioural thresholds implies a nearly one-to-one transformation of visual neuron performance to the visuo-motor output. In addition, we assume that the optomotor response is not mediated by the optokinetic system, but instead by other motion detection systems with higher coherence thresholds.     

Temporal patterns recognized by a network of coordinated time delays and coincidence detectors

A computational model of a neuronal network is described which performs a fundamental task of general perception: recognition of temporal patterns in continuous and uncued neuronal spike trains. The presented network is able to recognize each pattern element (100 ms interval composed of sets of 10, 20, 30 and 40 ms interspike intervals combined in linear order) as it arrives. Its operation is based upon biologically plausible filtering mechanisms and population neurodynamics.     

Robust velocity computation from a biologically motivated model of motion perception

Current computational models of motion processing in the primate motion pathway do not cope well with image sequences in which a moving pattern is superimposed upon a static texture. The use of non-linear operations and the need for contrast normalization in motion models mean that the separation of the influences of moving and static patterns on the motion computation is not trivial. Therefore, the response to the superposition of static and moving patterns provides an important means of testing various computational strategies. Here we describe a computational model of motion processing in the visual cortex, one of the advantages of which is that it is highly resistant to interference from static patterns.     

Visual Acceleration Perception for Simple and Complex Motion Patterns

Humans are able to judge whether a target is accelerating in many viewing contexts, but it is an open question how the motion pattern per se affects visual acceleration perception. We measured acceleration and deceleration detection using patterns of random dots with horizontal (simpler) or radial motion (more visually complex). The results suggest that we detect acceleration better when viewing radial optic flow than horizontal translation. However, the direction within each type of pattern has no effect on performance and observers detect acceleration and deceleration similarly within each condition. We conclude that sensitivity to the presence of acceleration is generally higher for more complex patterns, regardless of the direction within each type of pattern or the sign of acceleration.     

Human liver akdehyde dehydrogenase. Kinetics of aldehyde oxidation.

Steady state initial velocity studies were carried out to determine the kinetic mechanism of human liver aldehyde dehydrogenase. Intersecting double reciprocal plots obtained in the absence of inhibitors demonstrated that the dehydrogenase reaction proceeded by sequential addition of both substrates prior to release of products. Dead end inhibition patterns obtained with coenzyme and substrate analogues (e.g. thionicotinamide-AD+ and chloral hydrate) indicated that NAD+ and aldehyde can bind in random fashion. The patterns of inhibition by the product NADH and of substrate inhibition by glyceraldehyde were also consistent with this mechanism. However, comparisons between kinetic constants associated with the dehydrogenase and esterase activities of this enzyme suggested that most of the dehydrogenase reaction flux proceeds via formation of an initial binary NAD+-enzyme complex over a wide range of substrate and coenzyme concentrations.     

A model of motion adaptation and motion after-effects based upon principal component regression

A computational model to help explain effects of adaptation to moving signals is compared with established energy (linear regression) models of motion detection. The proposed model assumes that processed image signals are subject to error in both dimensions of space and time. This assumption constrains models of motion perception to be based upon principal component regression rather than linear regression. It is shown that response suppression of model complex cell neurons that input into the model may account for (1) increases in perceived speed after adaptation to static patterns and testing with slowly moving patterns, (2) significant increases in perceived speed after adaptation to patterns moving at a medium speed and testing at high speed, and (3) decreases in perceived speed in the opponent direction to a quickly moving adapting signal. Neither of predictions (2) or (3) are general features of established accounts of motion detection by visual processes based upon linear regression. Comparisons of the proposed model's speed transfer function with existing psychophysical data suggests that the visual system processes motion signals with the tacit assumption that image measurements are subject to error in both space and time. Received: 24 January 2000 / Accepted in revised form: 8 May 2000     

Cuttlefish camouflage: context-dependent body pattern use during motion

It is virtually impossible to camouflage a moving target against a non-uniform background, but strategies have been proposed to reduce detection and targeting of movement. Best known is the idea that high contrast markings produce ‘motion dazzle’, which impairs judgement of speed and trajectory. The ability of the cuttlefish Sepia officinalis to change its visual appearance allows us to compare the animal''s choice of patterns during movement to the predictions of models of motion camouflage. We compare cuttlefish body patterns used during movement with those expressed when static on two background types; one of which promotes low-contrast mottle patterns and the other promotes high-contrast disruptive patterns. We find that the body pattern used during motion is context-specific and that high-contrast body pattern components are significantly reduced during movement. Thus, in our experimental conditions, cuttlefish do not use high contrast motion dazzle. It may be that, in addition to being inherently conspicuous during movement, moving high-contrast patterns will attract attention because moving particles in coastal waters tend to be of small size and of low relative contrast.     

Non-Conscious Processing of Motion Coherence Can Boost Conscious Access

Research on the scope and limits of non-conscious vision can advance our understanding of the functional and neural underpinnings of visual awareness. Here we investigated whether distributed local features can be bound, outside of awareness, into coherent patterns. We used continuous flash suppression (CFS) to create interocular suppression, and thus lack of awareness, for a moving dot stimulus that varied in terms of coherence with an overall pattern (radial flow). Our results demonstrate that for radial motion, coherence favors the detection of patterns of moving dots even under interocular suppression. Coherence caused dots to break through the masks more often: this indicates that the visual system was able to integrate low-level motion signals into a coherent pattern outside of visual awareness. In contrast, in an experiment using meaningful or scrambled biological motion we did not observe any increase in the sensitivity of detection for meaningful patterns. Overall, our results are in agreement with previous studies on face processing and with the hypothesis that certain features are spatiotemporally bound into coherent patterns even outside of attention or awareness.     

The complex effects of mass extinctions on morphological disparity

Studies of biodiversity through deep time have been a staple for biologists and paleontologists for over 60 years. Investigations of species richness (diversity) revealed that at least five mass extinctions punctuated the last half billion years, each seeing the rapid demise of a large proportion of contemporary taxa. In contrast to diversity, the response of morphological diversity (disparity) to mass extinctions is unclear. Generally, diversity and disparity are decoupled, such that diversity may decline as morphological disparity increases, and vice versa. Here, we develop simulations to model disparity changes across mass extinctions using continuous traits and birth-death trees. We find no simple null for disparity change following a mass extinction but do observe general patterns. The range of trait values decreases following either random or trait-selective mass extinctions, whereas variance and the density of morphospace occupation only decline following trait-selective events. General trends may differentiate random and trait-selective mass extinctions, but methods struggle to identify trait selectivity. Long-term effects of mass extinction trait selectivity change support for phylogenetic comparative methods away from the simulated Brownian motion toward Ornstein-Uhlenbeck and Early Burst models. We find that morphological change over mass extinction is best studied by quantifying multiple aspects of morphospace occupation.