A two dimensional model for saccade generation

A model for the generation of oblique saccades is constructed by extending and modifying the one dimensional local feedback model. It is proposed that the visual system stores target location in inertial coordinates, but that the feedback loop which guides saccades works in retinotopic coordinates. To achieve straight trajectories for centripetal and centrifugal saccades in all meridians, a comparator computes motor error as a vector and uses the vectorial error signal to drive two orthogonally-acting burst generators. The generation of straight saccade trajectories when the extraocular muscles are of unequal strengths requires the introduction of a burst-tonic cell input to motor neurons. The model accounts for the results of two-site stimulation of the superior colliculus and frontal eye fields by allowing simultaneous activation of more than one comparator. The postulated existence of multiple comparators suggests that motor error may be computed topographically.     

Recursive implementations of temporal filters for image motion computation

 Efficient algorithms for image motion computation are important for computer vision applications and the modelling of biological vision systems. Intensity-based image motion computation proceeds in two stages: the convolution of linear spatiotemporal filter kernels with the image sequence, followed by the non-linear combination of the filter outputs. If the spatiotemporal extent of the filter kernels is large, then the convolution stage can be very intensive computationally. One effective means of reducing the storage required and computation involved in implementing the temporal convolutions is the introduction of recursive filtering. Non-recursive methods require the number of frames of the image sequence stored at any given time to be equal to the temporal extent of the slowest temporal filter. In contrast, recursive methods encode recent stimulus history implicitly in the values of a small number of variables updated through a series of feedback equations. Recursive filtering reduces the number of values stored in memory during convolution and the number of mathematical operations involved in computing the filters' outputs. This paper extends previous recursive implementations of gradient- and correlation-based motion analysis algorithms [Fleet DJ, Langley K (1995) IEEE PAMI 17: 61–67; Clifford CWG, Ibbotson MR, Langley K (1997) Vis Neurosci 14: 741–749], describing a recursive implementation of causal band-pass temporal filters suitable for use in energy- and phase-based algorithms for image motion computation. It is shown that the filters' temporal frequency tuning curves fit psychophysical estimates of the temporal properties of human visual filters [Hess RF, Snowden RJ (1992) Vision Res 32: 47–60]. Received: 20 April 1999 /Accepted in revised form: 8 November 1999     

Toward a theory of evolutionary computation

We outline a theory of evolutionary computation using a formal model of evolutionary computation--the Evolutionary Turing Machine--which is introduced as the extension of the Turing Machine model. Evolutionary Turing Machines provide a better and a more complete model for evolutionary computing than conventional Turing Machines, algorithms, and Markov chains. The convergence and convergence rate are defined and investigated in terms of this new model. The sufficient conditions needed for the completeness and optimality of evolutionary search are investigated. In particular, the notion of the total optimality as an instance of the multiobjective optimization of the Universal Evolutionary Turing Machine is introduced. This provides an automatic way to deal with the intractability of evolutionary search by optimizing the quality of solutions and search costs simultaneously. Based on a new model a very flexible classification of optimization problem hardness for the evolutionary techniques is proposed. The expressiveness of evolutionary computation is investigated. We show that the problem of the best evolutionary algorithm is undecidable independently of whether the fitness function is time dependent or fixed. It is demonstrated that the evolutionary computation paradigm is more expressive than Turing Machines, and thus the conventional computer science based on them. We show that an Evolutionary Turing Machine is able to solve nonalgorithmically the halting problem of the Universal Turing Machine and, asymptotically, the best evolutionary algorithm problem. In other words, the best evolutionary algorithm does not exist, but it can be potentially indefinitely approximated using evolutionary techniques.     

Fly vision: neural mechanisms of motion computation

A wide range of novel approaches are being used to dissect the visual system of the fly, both the neural networks of motion detection and the performance of these networks under complex natural stimulus conditions.     

Mechanical stress inference for two dimensional cell arrays

Many morphogenetic processes involve mechanical rearrangements of epithelial tissues that are driven by precisely regulated cytoskeletal forces and cell adhesion. The mechanical state of the cell and intercellular adhesion are not only the targets of regulation, but are themselves the likely signals that coordinate developmental process. Yet, because it is difficult to directly measure mechanical stress in vivo on sub-cellular scale, little is understood about the role of mechanics in development. Here we present an alternative approach which takes advantage of the recent progress in live imaging of morphogenetic processes and uses computational analysis of high resolution images of epithelial tissues to infer relative magnitude of forces acting within and between cells. We model intracellular stress in terms of bulk pressure and interfacial tension, allowing these parameters to vary from cell to cell and from interface to interface. Assuming that epithelial cell layers are close to mechanical equilibrium, we use the observed geometry of the two dimensional cell array to infer interfacial tensions and intracellular pressures. Here we present the mathematical formulation of the proposed Mechanical Inverse method and apply it to the analysis of epithelial cell layers observed at the onset of ventral furrow formation in the Drosophila embryo and in the process of hair-cell determination in the avian cochlea. The analysis reveals mechanical anisotropy in the former process and mechanical heterogeneity, correlated with cell differentiation, in the latter process. The proposed method opens a way for quantitative and detailed experimental tests of models of cell and tissue mechanics.     

A simple model for the two dimensional blood flow in the collapse of veins

Veins in the cardiovascular system may collapse if the internal pressure is less than the external pressure. Such collapse or buckling will have important consequence in terms of the rate of blood flow. Here a steady, parallel unidirectional flow as an exact solution of the continuity and the Navier Stokes equations is constructed. Various stages of the deformation process of the elastic tube (before contact of opposite sides occurring), from an ellipse to a `strongly buckled' configuration, are obtained in analytical forms as a by-product of the calculations. The pressure – area and the pressure – flow rate diagrams computed numerically from the model agree with the trends measured experimentally. Partial Financial Support has been provided by the Research Grants Council Contract HKU 7184/04E.     

The computation of structure from fixed-axis motion: rigid structures

We show that three distinct orthographic views of three points in a rigid configuration are compatibel with at most 64 interpretations of the three-dimensional structure and motion of the points. If, in addition, one assumes that the three points spin about a fixed axis over the three views, then with probability one there is a unique three-dimensional interpretation (plus a reflection). Moreover the probability of false targets is zero. In the special case that the axis of rotation is parallel to the image plane three views of the three points are sufficient to obtain at most two interpretations (plus reflections)-unless one assumes the angular velocity about the axis is constant, in which case three views of two points are sufficient to determine a unique interpretation. Closed form solutions are obtained for each of these cases. The systems of equations studied here are in each case overconstraining (i.e. there are more independent equations than unknowns) and are amenable to solution by nonlinear programming. These two properties make possible the construction of noise insensitive algorithms for computer vision systems. Our uniqueness proofs employ the Principle of upper semicontinuity, a principle which underlies a general mathematical framework for the analysis of solutions to overconstraining systems of equations.     

The computation of structure from fixed-axis motion: Nonrigid structures

We show that an assumption of rigidity or quasi-rigidity is not necessary, in principle, for the computation of three-dimensional structure and motion from changing retinal images. In particular, we show that the three-dimensional structure of certain nonrigid objects, namely objects whose texture elements rotate about a common axis but at varying angular velocities, can in principle be computed from three successive retinal images of four texture elements, or from four successive images of two texture elements. We then show that in both cases the computed structure matches the actual structure of the object with probability one.     

Biological computation of image motion from flows over boundaries.

A theory of early motion processing in the human and primate visual system is presented which is based on the idea that spatio-temporal retinal image data is represented in primary visual cortex by a truncated 3D Taylor expansion that we refer to as a jet vector. This representation allows all the concepts of differential geometry to be applied to the analysis of visual information processing. We show in particular how the generalised Stokes theorem can be used to move from the calculation of derivatives of image brightness at a point to the calculation of image brightness differences on the boundary of a volume in space-time and how this can be generalised to apply to integrals of products of derivatives. We also provide novel interpretations of the roles of direction selective, bi-directional and pan-directional cells and of type I and type II cells in V5/MT.     

A semiclassical theory for nerve excitation by a low intensity electromagnetic field

A possible mechanism for microwave-neuron interaction, when the nerve is irradiated by a thermally insignificant electromagnetic field, is described. The radiation field is treated classically, but the atomic system which interacts with this field is treated quantum mechanically using the density matrix approach. Attention is given to both homogeneous and inhomogeneous broadening effects, and the degrading influence of inhomogeneous broadening upon the neural membrane's ability to interact with the electromagnetic field is shown.     

Multi/infinite dimensional neural networks, multi/infinite dimensional logic theory

A mathematical model of an arbitrary multi-dimensional neural network is developed and a convergence theorem for an arbitrary multi-dimensional neural network represented by a fully symmetric tensor is stated and proved. The input and output signal states of a multi-dimensional neural network/logic gate are related through an energy function, defined over the fully symmetric tensor (representing the connection structure of a multi-dimensional neural network). The inputs and outputs are related such that the minimum/maximum energy states correspond to the output states of the logic gate/neural network realizing a logic function. Similarly, a logic circuit consisting of the interconnection of logic gates, represented by a block symmetric tensor, is associated with a quadratic/higher degree energy function. Infinite dimensional logic theory is discussed through the utilization of infinite dimension/order tensors.     

A comparison of two warm-ups on joint range of motion

The purpose of this study was to compare a 5-minute treadmill activity at 70% maximum heart rate (MHR) and 5 to 6 minutes of ballistic stretching to a 5-minute treadmill activity at 60% of MHR and 5 to 6 minutes of static stretching. Thirty healthy college students, 7 men and 23 women, volunteered. Most volunteers were moderately active. All participants signed an informed consent. Participants received the aforementioned warm-ups in random order with 48 to 72 hours between warm-ups. The stretching exercises were a back stretch, a quadriceps stretch, and a hamstring stretch. Three trials for 30 seconds each were given. After each warm-up the participants performed the modified-modified Schober test for low back flexibility, active knee extension test for hamstring flexibility, and plantar flexion for ankle flexibility. There were no significant differences on any of the 3 range of motion (ROM) tests although the ankle ROM test was almost significantly greater (68.8 degrees ) after the warm-up with static stretching compared with 65.9 degrees after the warm-up with ballistic stretching. A more intense cardiovascular activity and ballistic stretching were similar to a less intense cardiovascular activity and static stretching on flexibility. If athletes perform a warm-up and static or ballistic stretching before their workouts, then they should continue to perform the warm-up and the stretching routine with which they are most familiar and comfortable.     

A field theory of neural nets: I: Derivation of field equations

A model is described in which neural activity is represented by a field quantity ϕ, with the neurons as the sources of ϕ. It is shown that, with certain physically realistic assumptions, ϕ satisfies a moderately nonlinear differential equation. It is also found that this equation is isotropic and of second order if and only if the neuronal connectivity has a dependence on distance,p, of the formp ⁻¹ e ^−1/2βp .