Dynamic decorrelation as a unifying principle for explaining a broad range of brightness phenomena.

The visual system is highly sensitive to spatial context for encoding luminance patterns. Context sensitivity inspired the proposal of many neural mechanisms for explaining the perception of luminance (brightness). Here we propose a novel computational model for estimating the brightness of many visual illusions.

Large plasmonic color metasurfaces fabricated by super resolution deep UV lithography.

In this paper, we demonstrate plasmonic color metasurfaces as large as ∼60 cm fabricated by deep UV projection lithography employing an innovative combination of resolution enhancement techniques. Briefly, in addition to the established off-axis dipole illumination, double- and cross-exposure resolution enhancement of lithography, we introduce a novel element, the inclusion of transparent assist features to the mask layout. With this approach, we demonstrate the fabrication of relief arrays having critical dimensions such as 159 nm nanopillars or 210 nm nanoholes with 300 nm pitches, which is near the theoretical resolution limit expressed by the Rayleigh criterion for the 248 nm lithography tool used in this work.

A calcium-influx-dependent plasticity model exhibiting multiple STDP curves.

Hebbian plasticity means that if the firing of two neurons is correlated, then their connection is strengthened. Conversely, uncorrelated firing causes a decrease in synaptic strength. Spike-timing-dependent plasticity (STDP) represents one instantiation of Hebbian plasticity.

Luminance gradients and non-gradients as a cue for distinguishing reflectance and illumination in achromatic images: A computational approach.

The brain analyses the visual world through the luminance patterns that reach the retina. Formally, luminance (as measured by the retina) is the product of illumination and reflectance. Whereas illumination is highly variable, reflectance is a physical property that characterizes each object surface.

Dendritic Pooling of Noisy Threshold Processes Can Explain Many Properties of a Collision-Sensitive Visual Neuron.

Power laws describe brain functions at many levels (from biophysics to psychophysics). It is therefore possible that they are generated by similar underlying mechanisms. Previously, the response properties of a collision-sensitive neuron were reproduced by a model which used a power law for scaling its inhibitory input.

The time course of estimating time-to-contact: switching between sources of information.

The different sources of information that can be used to estimate time-to-contact may have different degrees of reliability across time. For example, after a given presentation or display time, an absolute change of angular size can be more reliable than the corresponding estimation of the rate of angular expansion (e.g.

Unifying time to contact estimation and collision avoidance across species.

The τ-function and the η-function are phenomenological models that are widely used in the context of timing interceptive actions and collision avoidance, respectively. Both models were previously considered to be unrelated to each other: τ is a decreasing function that provides an estimation of time-to-contact (ttc) in the early phase of an object approach; in contrast, g has a maximum before ttc. Furthermore, it is not clear how both functions could be implemented at the neuronal level in a biophysically plausible fashion.

People favour imperfect catching by assuming a stable world.

The visual angle that is projected by an object (e.g. a ball) on the retina depends on the object's size and distance.

Are predefined decoy sets of ligand poses able to quantify scoring function accuracy?

Due to the large number of different docking programs and scoring functions available, researchers are faced with the problem of selecting the most suitable one when starting a structure-based drug discovery project. To guide the decision process, several studies comparing different docking and scoring approaches have been published. In the context of comparing scoring function performance, it is common practice to use a predefined, computer-generated set of ligand poses (decoys) and to reevaluate their score using the set of scoring functions to be compared.

Differential intrinsic bias of the 3-D perceptual environment and its role in shape constancy.

In a three-dimensional (3-D) environment, sensory information is projected on a 2-D retina with the consequence that the visual system needs space information for accurately reconstructing the visual world. However, the 3-D environment is not accurately represented in the brain; in particular, the perception of distances in depth is imprecise. It has been argued that the visual system has an intrinsic bias of visual space where targets located on the ground floor are perceived on an implicit elevated surface.

Feed-forward segmentation of figure-ground and assignment of border-ownership.

Figure-ground is the segmentation of visual information into objects and their surrounding backgrounds. Two main processes herein are boundary assignment and surface segregation, which rely on the integration of global scene information. Recurrent processing either by intrinsic horizontal connections that connect surrounding neurons or by feedback projections from higher visual areas provide such information, and are considered to be the neural substrate for figure-ground segmentation.

"I look in your eyes, honey": internal face features induce spatial frequency preference for human face processing.

Numerous psychophysical experiments found that humans preferably rely on a narrow band of spatial frequencies for recognition of face identity. A recently conducted theoretical study by the author suggests that this frequency preference reflects an adaptation of the brain's face processing machinery to this specific stimulus class (i.e.

Molecular visualization in the rational drug design process.

The visualization of molecular scenarios on an atomic level can help to interpret experimental and theoretical findings. This is demonstrated in this review article with the specific field of drug design. State-of-the-art visualization techniques are described and applied to the different stages of the rational design process.

Preferred spatial frequencies for human face processing are associated with optimal class discrimination in the machine.

Psychophysical studies suggest that humans preferentially use a narrow band of low spatial frequencies for face recognition. Here we asked whether artificial face recognition systems have an improved recognition performance at the same spatial frequencies as humans. To this end, we estimated recognition performance over a large database of face images by computing three discriminability measures: Fisher Linear Discriminant Analysis, Non-Parametric Discriminant Analysis, and Mutual Information.

Does face image statistics predict a preferred spatial frequency for human face processing?

Psychophysical experiments suggested a relative importance of a narrow band of spatial frequencies for recognition of face identity in humans. There exists, however, no conclusive evidence of why it is that such frequencies are preferred. To address this question, I examined the amplitude spectra of a large number of face images and observed that face spectra generally fall off more steeply with spatial frequency compared with ordinary natural images.

Comparison of Composer and ORCHESTRAR.

Although the number of known protein structures is increasing, the number of protein sequences without determined structures is still much larger. Three-dimensional (3D) protein structure information helps in the understanding of functional mechanisms, but solving structures by X-ray crystallography or NMR is often a lengthy and difficult process. A relatively fast way of determining a protein's 3D structure is to construct a computer model using homologous sequence and structure information.

Gradient representations and the perception of luminosity.

The neuronal mechanisms that serve to distinguish between light emitting and light reflecting objects are largely unknown. It has been suggested that luminosity perception implements a separate pathway in the visual system, such that luminosity constitutes an independent perceptual feature. Recently, a psychophysical study was conducted to address the question whether luminosity has a feature status or not.

Gradient representation and perception in the early visual system--a novel account of Mach band formation.

Recent evidence suggests that object surfaces and their properties are represented at early stages in the visual system of primates. Most likely invariant surface properties are extracted to endow primates with robust object recognition capabilities. In real-world scenes, luminance gradients are often superimposed on surfaces.

Smooth gradient representations as a unifying account of Chevreul's illusion, Mach bands, and a variant of the Ehrenstein disk.

Recent evidence suggests that the primate visual system generates representations for object surfaces (where we consider representations for the surface attribute brightness). Object recognition can be expected to perform robustly if those representations are invariant despite environmental changes (e.g.

Recovering real-world images from single-scale boundaries with a novel filling-in architecture.

Filling-in models were successful in predicting psychophysical data for brightness perception. Nevertheless, their suitability for real-world image processing has never been examined. A unified architecture for both predicting psychophysical data and real-world image processing would constitute a powerful theory for early visual information processing.

Pattern recognition strategies for molecular surfaces: III. Binding site prediction with a neural network.

An algorithm for the identification of possible binding sites of biomolecules, which are represented as regions of the molecular surface, is introduced. The algorithm is based on the segmentation of the molecular surface into overlapping patches as described in the first article of this series.1 The properties of these patches (calculated on the basis of physical and chemical properties) are used for the analysis of the molecular surfaces of 7821 proteins and protein complexes.

Pattern recognition strategies for molecular surfaces. II. Surface complementarity.

Fuzzy logic based algorithms for the quantitative treatment of complementarity of molecular surfaces are presented. Therein, the overlapping surface patches defined in article I1 of this series are used. The identification of complementary surface patches can be considered as a first step for the solution of molecular docking problems.

Pattern recognition strategies for molecular surfaces. I. Pattern generation using fuzzy set theory.

A new method for the characterization of molecules based on the model approach of molecular surfaces is presented. We use the topographical properties of the surface as well as the electrostatic potential, the local lipophilicity/hydrophilicity, and the hydrogen bond density on the surface for characterization. The definition and the calculation method for these properties are reviewed shortly.