Neuronal model for stereoscopic vision

A neuronal model for stereopsis is described and simulated. Without the assumption of specific feature detectors, objects are unambiguously located in three-dimensional visual space. Random-dot stereograms are correctly resolved in depth with stimulus details conserved within planar contours.     

Mosaic model for color vision

Color vision in man is based upon three different cone types, which are quite likely arranged in a semi-ordered array in the retina. The model proposes that this ordering is an inherent part of the genetic code that sets up the color vision mechanism, and that the specification for each cone type (red, green or blue) also includes a specification for its place in the larger structure of which it is a part. One possible positional mosaic for the three cone types is proposed, together with its degeneracies into anomalous (red-green) color mechanisms. Assuming only one fixed probability for a degenerate transition, the population frequencies for color anomalies predicted from the model agree closely with the observed frequencies.     

Optimum probabilistic processing in colour perception. II. Colour vision as template matching.

A statistical approach to account for psychophysical phenomena in human colour vision is presented. The central visual processor is viewed as an optimum recognizer of stochastic patterns supplied by the periphery. The processor makes an optimum estimate of the spectral parameters of the stimulus, given the wavelength filter characteristics of the periphery, the stochastic nature of the information and an internal template to which the external stimulus is matched. The estimate is constrained in ways inferred from empirical phenomena. Subjective brightness of monochromatic stimuli and related constant brightness manifolds in the colour space constitute the constraint for brightness estimation. Results analogous and in accord with those of earlier line element theories are obtained. The Bezold-Brücke hue shift constitutes the basic constraint for hue estimation. The hue estimate involves interrelation between the fields in the experiment. Similarities and differences both in basic conceptions and results introduced by the template matching notions are discussed.     

A homology model of SERT based on the LeuT(Aa) template

A human serotonin transporter (SERT) model has been constructed based on the crystal structure of the bacterial homologue of Na(+)/Cl(-)-dependent neurotransmitter transporters from Aquifex aeolicus (LeuT(Aa)). Amino acids in the ligand binding area predicted by ICM pocket finder included Tyr95, Ala96, Asp98, Gly100 (transmembrane helix (TMH) 1), Ala169, Ile172, Ala173, Tyr176 (TMH3), Phe335, Ser336, Gly338, Phe341, Val343 (TMH6), Thr439, Ala441, and Gly442 (TMH8). The present model is an updated working tool for experimental studies on SERT.     

A template matching model for pattern recognition: Self-organization of templates and template matching by a disinhibitory neural network

A template matching model for pattern recognition is proposed. By following a previouslyproposed algorithm for synaptic modification (Hirai, 1980), the template of a stimulus pattern is selforganized as a spatial distribution pattern of matured synapses on the cells receiving modifiable synapses. Template matching is performed by the disinhibitory neural network cascaded beyond the neural layer composed of the cells receiving the modifiable synapses. The performance of the model has been simulated on a digital computer. After repetitive presentations of a stimulus pattern, a cell receiving the modifiable synapses comes to have the template of that pattern. And the cell in the latter layer of the disinhibitory bitory neural network that receives the disinhibitory input from that cell becomes electively sensitive to that pattern. Learning patterns are not restricted by previously learned ones. They can be subset or superset patterns of the ones previously learned. If an unknown pattern is presented to the model, no cell beyond the disinhibitory neural network will respond. However, if previously learned patterns are embedded in that pattern, the cells which have the templates of those patterns respond and are assumed to transmit the information to higher center. The computer simulation also shows that the model can organize a clean template under a noisy environment.     

In support of the “photopigment model” of vision in invertebrates

Summary Observations of the prolonged depolarising afterpotential (PDA) show that the rate of decay of a PDA is directly proportional of the extent of conversions of rhodopsin to metarhodopsin (regulated by controlled light stimuli). The experiments were designed to detect the effects of a hypothetical inhibitor (proposed by the Excitor-Inhibitor model of invertebrate vision); the results do not support the existence of an inhibitor, but further corroborate the already proposed Photopigment Model.Abbreviations E-I model Excitor-Inhibitor model - LRP late receptor potential - PDA prolonged depolarising afterpotential This work was part of the programme of the Sonderforschungsbereich 114, financed by the Deutsche Forschungsgemeinschaft     

Geometry of binocular vision and a model for stereopsis

If a binocular observer looks at surfaces, the disparity is a continuous vector field defined on the manifold of cyclopean visual directions. We derive this field for the general case that the observer is presented with a curved surface and fixates an arbitrary point. We expand the disparity field in the neighbourhood of a visual direction. The first order approximation can be decomposed into congruences, similarities and deformations. The deformation component is described by the traceless part of the symmetric part of the gradient of the disparity. The deformation component carries all information concerning the slant of a surface element that is contained in the disparity field itself; it is invariant for changes of fixation, differential cyclotorsion and uniform aniseikonia. The deformation component can be found from a comparison of the orientation of surface details in the left and right retinal images. The theory provides a geometric explanation of the percepts obtained with uniform and oblique meridional aniseikonia. We utilize the geometric theory to construct a mechanistic model of stereopsis that obviates the need for internal zooming mechanisms, but nevertheless is insensitive to differential cyclotorsion or uniform aniseikonia.     

A model of color vision in trichromats and protans

A model which explains the human vision protanopic deficiency and its biologic prototype with the absence of red-absorbing pigment (rabbit) was constructed from neuron-like elements. In behavioral experiments and by means of evoked potential technique it was shown that the rabbit's color space is characterized by a spherical four-dimensional with a reduction of red-coding area. Similar spherical four-dimensional structure of color space is characteristic for a group of protanopic human subjects. The perceptive space of another group of protanopic subjects (protanomals) is characterized by a reduction of both parts of the red-green opponent axis. These disorders are reproduced in the model either by a loss of some color-coding elements (the absence of the red-absorbing pigment as in protanops) or a shift of the spectral characteristics of the red pigment towards those of the green one (protanomals).     

The Gaussian derivative model for spatial-temporal vision: I. Cortical model

How do we see the motion of objects as well as their shapes? The Gaussian Derivative (GD) spatial model is extended to time to help answer this question. The GD spatio-temporal model requires only two numbers to describe the complete three-dimensional space-time shapes of individual receptive fields in primate visual cortex. These two numbers are the derivative numbers along the respective spatial and temporal principal axes of a given receptive field. Nine transformation parameters allow for a standard geometric association of these intrinsic axes with the extrinsic environment. The GD spatio-temporal model describes in one framework the following properties of primate simple cell fields: motion properties, number of lobes in space-time, spatial orientation. location, and size. A discrete difference-of-offset-Gaussians (DOOG) model provides a plausible physiological mechanism to form GD-like model fields in both space and time. The GD model hypothesizes that receptive fields at the first stage of processing in the visual cortex approximate 'derivative analyzers' that estimate local spatial and temporal derivatives of the intensity profile in the visual environment. The receptive fields as modeled provide operators that can allow later stages of processing in either a biological or machine vision system to estimate the motion as well as the shapes of objects in the environment.     

Restoration of cone vision in a mouse model of achromatopsia

Loss of cone function in the central retina is a pivotal event in the development of severe vision impairment for many prevalent blinding diseases. Complete achromatopsia is a genetic defect resulting in cone vision loss in 1 in 30,000 individuals. Using adeno-associated virus (AAV) gene therapy, we show that it is possible to target cones and rescue both the cone-mediated electroretinogram response and visual acuity in the Gnat2 ( cpfl3 ) mouse model of achromatopsia.     

Benchmarking template selection and model quality assessment for high-resolution comparative modeling

Comparative modeling is presently the most accurate method of protein structure prediction. Previous experiments have shown the selection of the correct template to be of paramount importance to the quality of the final model. We have derived a set of 732 targets for which a choice of ten or more templates exist with 30-80% sequence identity and used this set to compare a number of possible methods for template selection: BLAST, PSI-BLAST, profile-profile alignment, HHpred HMM-HMM comparison, global sequence alignment, and the use of a model quality assessment program (MQAP). In addition, we have investigated the question of whether any structurally defined subset of the sequence could be used to predict template quality better than overall sequence similarity. We find that template selection by BLAST is sufficient in 75% of cases but that there are examples in which improvement (global RMSD 0.5 A or more) could be made. No significant improvement is found for any of the more sophisticated sequence-based methods of template selection at high sequence identities. A subset of 118 targets extending to the lowest levels of sequence similarity was examined and the HHpred and MQAP methods were found to improve ranking when available templates had 35-40% maximum sequence identity. Structurally defined subsets in general are found to be less discriminative than overall sequence similarity, with the coil residue subset performing equivalently to sequence similarity. Finally, we demonstrate that if models are built and model quality is assessed in combination with the sequence-template sequence similarity that a extra 7% of "best" models can be found.     

Structural activation of Mad2 in the mitotic spindle checkpoint: the two-state Mad2 model versus the Mad2 template model

The inheritance of a normal assortment of chromosomes during each cell division relies on a cell-cycle surveillance system called the mitotic spindle checkpoint. The existence of sister chromatids that do not achieve proper bipolar attachment to the mitotic spindle in a cell activates this checkpoint, which inhibits the ubiquitin ligase activity of the anaphase-promoting complex or cyclosome (APC/C) and delays the onset of anaphase. The mitotic arrest deficiency 2 (Mad2) spindle checkpoint protein inhibits APC/C through binding to its mitotic-specific activator, Cdc20. Binding of Mad2 to Cdc20 involves a large conformational change of Mad2 and requires the Mad1-Mad2 interaction in vivo. Two related but distinct models of Mad1-assisted activation of Mad2, the "two-state Mad2" and the "Mad2 template" models, have been proposed. I review the recent structural, biochemical, and cell biological data on Mad2, discuss the differences between the two models, and propose experiments that test their key principles.     

A self-similar stack model for human and machine vision

A new model is proposed that not only exhibits the major properties of primate spatial vision but also has a structure that can be implemented efficiently in a machine vision system. The model is based on a self-similar stack structure with a spatial resolution that varies with eccentricity. It correctly reproduces the visual cortical mapping function, yet it has the important attribute that it can produce invariant responses to local changes in the size and position of image features. By proposing a novel purpose for cortical bar-detectors, the model can also produce invariance to more general distortions. The structure of the model allows efficient hierarchical search to be made and it naturally embraces the concept of attention area. Exploitation of this model has already confirmed these properties and has also revealed its robust ability to control the focus and gain of machine vision systems.     

Color distance derived from a receptor model of color vision in the honeybee

A model calculation is presented for investigating the domain between the two well-examined fields of color vision in the bee, i.e. choice behavior with respect to color stimuli, and photoreceptor physiology. Based on the properties of the receptors, the model explains quantitatively the results obtained in color discrimination experiments. The model predicts curved lines which connect the loci of most similar color stimuli in the receptor plane and makes quantitative predictions about the magnitude of the Bezold-Abney hue shift. A measure for color difference is derived from the number of the just-noticeabledifference (jnd) steps determined by the noise thresholds of the photoreceptor cells.     

Feature detection in human vision: a phase-dependent energy model

This paper presents a simple and biologically plausible model of how mammalian visual systems could detect and identify features in an image. We suggest that the points in a waveform that have unique perceptual significance as 'lines' and 'edges' are the points where the Fourier components of the waveform come into phase with each other. At these points 'local energy' is maximal. Local energy is defined as the square root of the sum of the squared response of sets of matched filters, of identical amplitude spectrum but differing in phase spectrum by 90 degrees: one filter type has an even-symmetric line-spread function, the other an odd-symmetric line-spread function. For a line the main contribution to the local energy peak is in the output of the even-symmetric filters, whereas for edges it is in the output of the odd-symmetric filters. If both filter types respond at the peak of local energy, both edges and lines are seen, either simultaneously or alternating in time. The model was tested with a series of images, and shown to predict well the position of perceived features and the organization of the images.     

Energy model for contrast detection: spatiotemporal characteristics of threshold vision

A model for contrast detection of spatiotemporal stimuli is proposed which consists of a spatiotemporal linear filter, an energy device and a threshold device. Assuming the existence of independent intrinsic noise, the probability of stimulus detection was approximated by a Weibull function of the response energy. With this assumption, the stimulus energy is a constant at fixed detection probability. This energy model for contrast detection satisfactorily accounted for the elliptical threshold contours of line pairs at stimulus separations within the range 2–30 min and at stimulus onset asynchronies within the range 20–140 ms. The threshold contour at a large stimulus onset asynchrony (300 ms) was in the form of a rounded square. This finding was explained by assuming that the probability of seeing the line pair was determined by the joint probability that at least one stimulus had been detected. With the energy model, the temporal and spatial autocorrelation functions of the response to a flashed line were evaluated. The autocorrelation functions thus determined were used to predict the temporal contrast sensitivity function to a flickering line stimulus and the spatial contrast sensitivity function to flashed gratings, which were in agreement with the experimental data. The data obtained were fitted adequately by an impulse response approximated by a spatiotemporal Gabor-like function. Received: 08 December 1997 / Accepted in revised form: 26 January 1999     

Reduction of the blocking effect in block-coded images using a model of early human vision

We propose a method, based on lowpass and bandpass components of Granrath's early human vision model, which reduces the blocking effect in block-coded images. The method consists of a lowpass filtering stage to smooth out the blocking effect and a contrast-enhancement stage to increase contrast in the restored image. Experimental results of the method show better performance than that of conventional methods for reducing blocking effects.