Vision without Frames: A Semiotic Paradigm of Event Based Computer Vision

Conventional imagers and almost all vision processes use and rely on theories that are based on the principle of static image-frames. A frame is a 2D matrix that represents the spatial locations of intensities of a scene projected on the imager. The notion of a frame itself is so embedded in machine vision, that it is usually taken for granted that this is how biological systems store light information. This paper presents a biosinpired event-based image formation principle, which output data rely on an asynchronous acquisition process. The generated information is stored in temporal volumes, which size and information depend only on the dynamic content of observed scenes. Practical analysis of such information will shows that the processing of visual information can only be based on a semiotic process. The paper also provides a general definition of the notion of visual features as the interpretation of signs according to different possible readings of the codified visual signal.     

Fitting of enzyme kinetic data without prior knowledge of weights.

A method is described for fitting equations to enzyme kinetic data that requires minimal assumptions about the error structure of the data. The dependence of the variances on the velocities is not assumed, but is deduced from internal evidence in the data. The effect of very bad observations ('outliers') is mitigated by decreasing the weight of observations that give large deviations from the fitted equation. The method works well in a wide range of circumstances when applied to the Michaelis-Menten equation, but it is not limited to this equation. It can be applied to most of the equations in common use for the analysis of steady-state enzyme kinetics. It has been implemented as a computer program that can fit a wide variety of equations with two, three or four parameters and two or three variables.     

Vision drives correlated activity without patterned spontaneous activity in developing Xenopus retina

Developing amphibians need vision to avoid predators and locate food before visual system circuits fully mature. Xenopus tadpoles can respond to visual stimuli as soon as retinal ganglion cells (RGCs) innervate the brain, however, in mammals, chicks and turtles, RGCs reach their central targets many days, or even weeks, before their retinas are capable of vision. In the absence of vision, activity-dependent refinement in these amniote species is mediated by waves of spontaneous activity that periodically spread across the retina, correlating the firing of action potentials in neighboring RGCs. Theory suggests that retinorecipient neurons in the brain use patterned RGC activity to sharpen the retinotopy first established by genetic cues. We find that in both wild type and albino Xenopus tadpoles, RGCs are spontaneously active at all stages of tadpole development studied, but their population activity never coalesces into waves. Even at the earliest stages recorded, visual stimulation dominates over spontaneous activity and can generate patterns of RGC activity similar to the locally correlated spontaneous activity observed in amniotes. In addition, we show that blocking AMPA and NMDA type glutamate receptors significantly decreases spontaneous activity in young Xenopus retina, but that blocking GABA(A) receptor blockers does not. Our findings indicate that vision drives correlated activity required for topographic map formation. They further suggest that developing retinal circuits in the two major subdivisions of tetrapods, amphibians and amniotes, evolved different strategies to supply appropriately patterned RGC activity to drive visual circuit refinement.     

H-CORE: enabling genome-scale Bayesian analysis of biological systems without prior knowledge

The Bayesian network is a popular tool for describing relationships between data entities by representing probabilistic (in)dependencies with a directed acyclic graph (DAG) structure. Relationships have been inferred between biological entities using the Bayesian network model with high-throughput data from biological systems in diverse fields. However, the scalability of those approaches is seriously restricted because of the huge search space for finding an optimal DAG structure in the process of Bayesian network learning. For this reason, most previous approaches limit the number of target entities or use additional knowledge to restrict the search space. In this paper, we use the hierarchical clustering and order restriction (H-CORE) method for the learning of large Bayesian networks by clustering entities and restricting edge directions between those clusters, with the aim of overcoming the scalability problem and thus making it possible to perform genome-scale Bayesian network analysis without additional biological knowledge. We use simulations to show that H-CORE is much faster than the widely used sparse candidate method, whilst being of comparable quality. We have also applied H-CORE to retrieving gene-to-gene relationships in a biological system (The 'Rosetta compendium'). By evaluating learned information through literature mining, we demonstrate that H-CORE enables the genome-scale Bayesian analysis of biological systems without any prior knowledge.     

XII. Something on Vision from Within

Earlier I attempted to show that Shpet was able to penetrate behind the external form of the word through its shell, which in itself is by no means simple, into its inner form, which proved to be immeasurably more complex than the external form. For me it still remains a mystery: How was he able to penetrate into the "living soul" of the word? Of course, he was helped in this by encyclopedic knowledge. He was, after all, a philosopher, a linguist, a psychologist, and an art cognoscente; he completed two years at the physics and mathematics and the history and philology departments of Kiev University. And Shpet also knew seventeen (!) languages. It seems to me that Shpet saw language (languages) and the word from within. He blended into the word rather than manipulated it. "Vision from within" is not a fantasy of my own. Goethe, who in the words of Ralph Waldo Emerson could see with his every pore, knew how to see from within. Ortega y Gasset in 1932 published a special article on this subject: "Goethe's vision from within." What Daniil Kharms saw from within was the absurd.     

Efficient docking of peptides to proteins without prior knowledge of the binding site

Reliability in docking of ligand molecules to proteins or other targets is an important challenge for molecular modeling. Applications of the docking technique include not only prediction of the binding mode of novel drugs, but also other problems like the study of protein-protein interactions. Here we present a study on the reliability of the results obtained with the popular AutoDock program. We have performed systematical studies to test the ability of AutoDock to reproduce eight different protein/ligand complexes for which the structure was known, without prior knowledge of the binding site. More specifically, we look at factors influencing the accuracy of the final structure, such as the number of torsional degrees of freedom in the ligand. We conclude that the Autodock program package is able to select the correct complexes based on the energy without prior knowledge of the binding site. We named this application blind docking, as the docking algorithm is not able to "see" the binding site but can still find it. The success of blind docking represents an important finding in the era of structural genomics.     

Quantifying viable virus-specific T cells without a priori knowledge of fine epitope specificity

Identification of pathogen-specific T cells has been greatly facilitated by the advent of synthetic peptide-major histocompatibility complex (MHC) tetramers. In many cases, however, specific epitopes have not been defined, necessitating detection methods that function independently of exact peptide-MHC specificity. Lymphocytes acquire surface proteins from antigen-presenting cells (APCs), and we have exploited this phenomenon to develop the T-cell recognition of APCs by protein transfer (TRAP) assay. This method is based on biotinylation and streptavidin-fluorochrome labeling of APCs, followed by subsequent acquisition of this label by antigen-specific T cells. The TRAP procedure detects MHC class I-restricted T cells regardless of their cytokine profiles or peptide-MHC affinities, and provides a versatile tool for monitoring the phenomenon of APC membrane acquisition by antigen-specific T cells.     

Analysis of ligand-binding data without knowledge of bound or free ligand molar concentration

A method is proposed to set the parameters in a nonlinear regression procedure to determine the equilibrium dissociation constant (Kd) and the high affinity receptor concentration (Bmax) of systems consisting of one ligand, one high affinity receptor, and n low affinity binding sites. This method is suitable when neither bound or free ligand formal concentrations nor the maximum of the binding signal can be deduced from the experimental data. The method makes use of (i) the abscissa of the first inflection point of the plot of any signal proportional to the binding of ligand to receptors versus the logarithm of the total ligand concentration, and (ii) the initial slope of the saturation curve plotted in direct coordinates. We first demonstrate that when such an inflection point exists, its abscissa lies between Bmax/2 + Kd(1 + d) and Bmax + 2Kd(1 + d), where d is a parameter representative of the binding to the low affinity sites. Second, we demonstrate that the initial slopes of two saturation curves in direct coordinates, where Bmax varies by a known factor, allows an estimation of the Bmax/Kd ratio, within certain limits. From these two sets of data it is subsequently possible to define a precise window for the values of both Bmax and Kd. The performance of the method has been evaluated in representative cases using Monte Carlo studies. The results establish conditions for the existence of an inflection point as well as the influence of low affinity binding, whether or not proportional to Bmax.