A novel interpretation for the collicular role in saccade generation

Recently, we found evidence that the activity of neurons in the deep layers of the monkey superior colliculus (SC) is modulated by initial eye position (gain fields). In this paper, we propose a quantitative model of the motor SC which incorporates these new findings. Inputs to the motor map represent the desired eye displacement vector (motor error), as well as initial eye position. A unit's activity in the motor map is described by multiplying a weak linear eye position sensitivity with a gaussian tuning to motor error. The motor map projects to several sets of output neurons, representing the coordinates of the desired eye displacement vector, the desired eye position in the head, and the three-dimensional ocular rotation axis for saccades in Listing's plane, respectively. All these signals have been hypothesized in the literature to drive the saccade burst generator. We show that these signals can be extracted from the motor map by a linear weighting of the population activity. The saccadic system may employ all coding strategies in parallel to ensure high spatial accuracy in many complex sensorimotor tasks, such as orienting to multimodal stimuli.     

Binocular coupling in chameleon saccade generation

Chameleons are capable of making a saccade with one eye while the other does not move. This virtually unique feature poses questions regarding the organization of the saccadic system of the chameleon. By comparing real data with a simulated test signal, we studied whether the saccade generation of the left and right eye can be considered as truly independent. This appeared not to be the case, since there was an increased likelihood to start saccades in close temporal proximity in the two eyes. However, the coupling does not reflect a common saccadic motor signal for both eyes, since even saccades that were made in close temporal proximity did not have correlated metrics. Received: 21 April 1997 / Accepted in revised form: 15 September 1997     

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.     

A two dimensional field theory for motion computation

The local extraction of motion information from brightness patterns by individual movement detectors of the correlation-type is considered in the first part of the paper. A two-dimensional field theory of movement detection is developed by treating the distance between two adjacent photoreceptors as a differential. In the first approximation of the theory we only consider linear terms of the time interval between the reception of a contrast element and its delayed representation by the detector and linear terms of the spatial distances between adjacent photoreceptors. As a result we may neglect terms of higher order than quadratic in a Taylor series development of the brightness pattern. The responses of pairs of individual movement detectors are combined to a local response vector. In the first approximation of the detector field theory the response vector is proportional to the instantaneous pattern velocity vector and linearly dependent on local properties of the moving pattern. The linear dependence on pattern properties is represented by a two by two tensor consisting of elements which are nonlinear, local functional of the moving pattern. Some of the properties of the tensor elements are treated in detail. So, for instance, it is shown that the off-diagonal elements of the tensor disappear when the moving pattern consists of x- and y-dependent separable components. In the second part of the paper the tensor relation leading to the output of a movement detector pair is spatially integrated. The result of the integration is an approximation to a summation of the outputs of an array of detector pairs. The spatially integrated detector tensor relates the translatory motion vector to the resultant output vector. It is shown that the angle between the motion vector and the resultant output vector is always smaller than ±90° whereas the angle between the motion vector and local response vectors, elicited by detector pairs, may cover the entire angular range. In the discussion of the paper the limits of the field theory for motion computation as well as its higher approximations are pointed out in some detail. In a special chapter the dependence of the detector response on the pattern properties is treated and in another chapter questions connected with the so called aperture problem are discussed. Furthermore, properties for compensation of the pattern dependent deviation angle by spatial physiological integration are mentioned in the discussion.     

Finite element analysis of two dimensional steady flow in model arterial bifurcation

The purpose of the investigation reported in this paper is to determine theoretically the fluid dynamic field in models of common iliac arterial bifurcation and to identify the flow features which might influence the predominant occurrence of atherosclerotic lesions at such sites. This has been accomplished by numerically simulating fluid flow through 90 degrees symmetric bifurcations with branch-to-trunk area ratios of 0.8-1.414 and for Reynolds numbers ranging from 100 to 400. The analysis predicts flow reversal along the outer wall in models with area ratios over unity for high Reynolds number range, while no flow reversal occurred in models with area ratio below unity; a low shear zone along the outer wall and high shear stresses at the divider lip. Adverse pressure gradients are observed along the outer wall downstream of the corner point, the magnitudes increased with Reynolds number for a given branch to area ratio. Biological implication of the results is discussed with specific reference to the sites of atherosclerotic lesions found in man for these geometries.     

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 model for the interaction of two chemicals

We describe a method for studying the interaction of two anesthetic agents, Morphine and Midazolam, acting simultaneously in the same individual. Representing the levels of the two chemicals by diffusion processes, we assume their interaction is governed by a linear combination of the separate components. Pharmacological data is used to estimate the model parameters and, in particular, to determine the coefficient in the linear combination. This leads to the conclusion that the two chemicals have a counteractive effect.     

Frontal eye field inactivation alters the readout of superior colliculus activity for saccade generation in a task-dependent manner

Saccades require a spatiotemporal transformation of activity between the intermediate layers of the superior colliculus (iSC) and downstream brainstem burst generator. The dynamic linear ensemble-coding model (Goossens and Van Opstal 2006) proposes that each iSC spike contributes a fixed mini-vector to saccade displacement. Although biologically-plausible, this model assumes cortical areas like the frontal eye fields (FEF) simply provide the saccadic goal to be executed by the iSC and brainstem burst generator. However, the FEF and iSC operate in unison during saccades, and a pathway from the FEF to the brainstem burst generator that bypasses the iSC exists. Here, we investigate the impact of large yet reversible inactivation of the FEF on iSC activity in the context of the model across four saccade tasks. We exploit the overlap of saccade vectors generated when the FEF is inactivated or not, comparing the number of iSC spikes for metrically-matched saccades. We found that the iSC emits fewer spikes for metrically-matched saccades during FEF inactivation. The decrease in spike count is task-dependent, with a greater decrease accompanying more cognitively-demanding saccades. Our results show that FEF integrity influences the readout of iSC activity in a task-dependent manner. We propose that the dynamic linear ensemble-coding model be modified so that FEF inactivation increases the gain of a readout parameter, effectively increasing the influence of a single iSC spike. We speculate that this modification could be instantiated by FEF and iSC pathways to the cerebellum that could modulate the excitability of the brainstem burst generator.

     

A DNA assembly model of sentence generation

Recent results of corpus-based linguistics demonstrate that context-appropriate sentences can be generated by a stochastic constraint satisfaction process. Exploiting the similarity of constraint satisfaction and DNA self-assembly, we explore a DNA assembly model of sentence generation. The words and phrases in a language corpus are encoded as DNA molecules to build a language model of the corpus. Given a seed word, the new sentences are constructed by a parallel DNA assembly process based on the probability distribution of the word and phrase molecules. Here, we present our DNA code word design and report on successful demonstration of their feasibility in wet DNA experiments of a small scale.     

A one dimensional moving bed biofilm reactor model for nitrification of municipal wastewaters

This work presents a one-dimensional model of a moving bed bioreactor (MBBR) process designed for the removal of nitrogen from raw wastewaters. A comprehensive experimental strategy was deployed at a semi-industrial pilot-scale plant fed with a municipal wastewater operated at 10–12 °C, and surface loading rates of 1–2 g filtered COD/m² d and 0.4–0.55 g NH₄-N/m² d. Data were collected on influent/effluent composition, and on measurement of key variables or parameters (biofilm mass and maximal thickness, thickness of the limit liquid layer, maximal nitrification rate, oxygen mass transfer coefficient). Based on time-course variations in these variables, the MBBR model was calibrated at two time-scales and magnitudes of dynamic conditions, i.e., short-term (4 days) calibration under dynamic conditions and long-term (33 days) calibration, and for three types of carriers. A set of parameters suitable for the conditions was proposed, and the calibrated parameter set is able to simulate the time-course change of nitrogen forms in the effluent of the MBBR tanks, under the tested operated conditions. Parameters linked to diffusion had a strong influence on how robustly the model is able to accurately reproduce time-course changes in effluent quality. Then the model was used to optimize the operations of MBBR layout. It was shown that the main optimization track consists of the limitation of the aeration supply without changing the overall performance of the process. Further work would investigate the influence of the hydrodynamic conditions onto the thickness of the limit liquid layer and the “apparent” diffusion coefficient in the biofilm parameters.

     

A hierarchical neuronal model for generation and online recognition of birdsongs

The neuronal system underlying learning, generation and recognition of song in birds is one of the best-studied systems in the neurosciences. Here, we use these experimental findings to derive a neurobiologically plausible, dynamic, hierarchical model of birdsong generation and transform it into a functional model of birdsong recognition. The generation model consists of neuronal rate models and includes critical anatomical components like the premotor song-control nucleus HVC (proper name), the premotor nucleus RA (robust nucleus of the arcopallium), and a model of the syringeal and respiratory organs. We use Bayesian inference of this dynamical system to derive a possible mechanism for how birds can efficiently and robustly recognize the songs of their conspecifics in an online fashion. Our results indicate that the specific way birdsong is generated enables a listening bird to robustly and rapidly perceive embedded information at multiple time scales of a song. The resulting mechanism can be useful for investigating the functional roles of auditory recognition areas and providing predictions for future birdsong experiments.     

A model for the competitive growth of two diatoms

A parallel between an experimental situation in marine microecology and its analytical model is presented. Two diatoms are cultured in a continuous flow apparatus and are studied for their competitive performance. A differential equations model is proposed to represent their growth behavior. The parameters of the model are evaluated from the experimental data and it is then identified from additional data.     

A positive feedback model for switching between two activities

We describe a model for the alternation between two activities. Each activity has an associated tendency, and the model performs the activity with the higher tendency. The tendencies depend on both negative and positive feedback from the performance of the activities. In general the behaviour of the model is periodic, with bout, durations that depend on the ratio of the maximum response rates. Increasing the maximum rate of a behaviour increases the magnitude of its bouts. The behaviour of the model is similar in several respects to the model developed by Ludlow (1980), which suggests that it may not be easy to distinguish between various models of feeding and drinking behaviour.     

A simple model of dynamic receptor pattern generation

A dynamic pattern generating automaton has been constructed. The rules controlling its function furnish the non-random generation of sub-patterns in consecutive cycles, within a large plane area, covered by four different classes of units of constant mean frequency in each class (standard system). The stabilization of certain specific sub-patterns over 100 subsequent cycles of pattern generation (modified systems) resulted in the modification of the frequency and frequency distribution of the sub-patterns relative to the standard system. Some new types of sub-patterns, not encountered in the standard system, also made appearance in the modified systems. The functioning of the standard and modified systems was analyzed and compared by the methods of mathematical statistics. The automaton was used to model certain features of the cytoplasmic membrane. The latter was regarded as a device by which the cell collects information about its environment. The dynamic generation of sub-patterns was taken as the cell's manner of asking questions, and the complementary chemical structures present in the environment were treated as possible answers to these. The irreversible question-answer interactions were regarded as signals and were modelled by the stabilization of specific sub-patterns. It was found that in a dynamic system like the model presented, it is not necessary to code each possible sub-pattern individually. Precise coding of the relative frequency of units per class and of their possible interactions is sufficient to furnish statistically constant mean frequencies for a given range of sub-patterns. In a dynamic system, the actual range of sub-patterns arisen in a population of identical individuals depends only on the size of the population. If the latter is appropriately large, all possible sub-patterns may be simultaneously present at any time at the average frequencies characteristic of each. Stabilized sub-patterns (signals) seem to modify specifically the frequencies of the other sub-patterns generated by the normal automaton. Some sub-patterns may disappear permanently, while others (new ones) may turn up and persist at given frequencies. Missense signals may definitively put the automaton out of order, i.e. result in the cell's complete misorientation in respect of its relations to the normal tissue structure.Reader of publications in physics, Gondolat Publishing House, Budapest, Hungary     

A model of oscillation generation by molluscan neurons

A model describing slow oscillations of membrane potential in molluscan neurons is suggested. It is based on the view that the depolarization phase is due to the slow calcium current, whereas the hyperpolarization phase is due to the potassium current activated by intracellular Ca ions. It is shown that depending on values of the parameters of the model there are three possible types of electrical activity of the neurons: stable membrane hyperpolarization up to the resting potential which is between ?49 and ?53 mV; slow oscillations of membrane potential from ?30 to ?60 mV, with a period of 12–17 sec, and stable membrane depolarization to between ?40 and ?30 mV, which may lead to the onset of stable rhythmic activity of these neurons. Dependence of the amplitude of the oscillations of potential on the extracellular concentration of Ca, K, and Na ions was calculated and agrees qualitatively with the experimental data of Barker and Gainer [4].     

A bifurcating autoregression model for cell lineages with variable generation means.

The bifurcating autoregression model for cell lineage data is extended to allow for observations whose means vary from generation to generation. The maximum likelihood estimates of this extended model are found and used to estimate the generation means and overall variance. The model is also used to test for inherited effects as measured by mother-daughter correlation, and for environmental effects as measured by the sister-sister correlation, conditional on inherited effects. Applications to data sets on EMT6 cells and Escherichia coli are given.