A model of handwriting

The research reported here is concerned with hand trajectory planning for the class of movements involved in handwriting. Previous studies show that the kinematics of human two-joint arm movements in the horizontal plane can be described by a model which is based on dynamic minimization of the square of the third derivative of hand position (jerk), integrated over the entire movement. We extend this approach to both the analysis and the synthesis of the trajectories occurring in the generation of handwritten characters. Several basic strokes are identified and possible stroke concatenation rules are suggested. Given a concise symbolic representation of a stroke shape, a simple algorithm computes the complete kinematic specification of the corresponding trajectory. A handwriting generation model based on a kinematics from shape principle and on dynamic optimization is formulated and tested. Good qualitative and quantitative agreement was found between subject recordings and trajectories generated by the model. The simple symbolic representation of hand motion suggested here may permit the central nervous system to learn, store and modify motor action plans for writing in an efficient manner.     

A parsimonious oscillatory model of handwriting

We propose an oscillatory model that is theoretically parsimonious, empirically efficient and biologically plausible. Building on Hollerbach’s (Biol Cybern 39:139–156, 1981) model, our Parsimonious Oscillatory Model of Handwriting (POMH) overcomes the latter’s main shortcomings by making it possible to extract its parameters from the trace itself and by reinstating symmetry between the \(x\) and \(y\) coordinates. The benefit is a capacity to autonomously generate a smooth continuous trace that reproduces the dynamics of the handwriting movements through an extremely sparse model, whose efficiency matches that of other, more computationally expensive optimizing methods. Moreover, the model applies to 2D trajectories, irrespective of their shape, size, orientation and length. It is also independent of the endeffectors mobilized and of the writing direction.     

A computational thrombus formation model: application to an idealized two-dimensional aneurysm treated with bare metal coils

Cardiovascular implantable devices alter the biofluid dynamics and biochemistry of the blood in which they are placed. These perturbations can lead to thrombus formation which may or may not be desired, depending on the application. In this work, a computational model is developed that couples biofluid dynamics and biochemistry to predict the clotting response of blood to such devices. The model consists of 28 advection–diffusion–reaction partial differential equations to track proteins in the blood involved in clotting and utilizes boundary flux terms to model the initiation of the intrinsic clotting pathway at thrombogenic device surfaces. We use this model to simulate the transient clot growth within a 2D idealized bifurcation aneurysm filled with various distributions of bare metal coils with similar packing densities. The clot model predicts initial clot formation to occur in areas along coil surfaces where flow is minimal and where time-averaged shear rates are the smallest. Among the six coil-filled aneurysm cases simulated, maximum thrombus occlusion ranged between 80.8 and 92.2% of the post-treatment aneurysm volume and was achieved 325–450 s after treatment. With further refinement and validation, the computational clotting model will be a valuable engineering tool for evaluating and comparing the relative performance of cardiovascular implantable devices.     

A computational model for cell differentiation

In this paper, we present a word set generating mechanism, called cell-differentiation system, inspired by the tissue process formation in multicellular organisms, which might model some properties of evolving communities of living cells at the syntactical level. The tools utilized to model these biological phenomena belong to the formal language theory. In this context chromosomal mutations are defined as operations on strings and the differentiation according to the control of gene expression is represented by some random-context conditions in formal languages.In the presented formal framework we prove that in a simplified form of this formalism, with only one cell-type which is regular, one single cell and no mitosis involved, the problem of establishing whether or not the set of vectors of integers indicating the number of cells in each population, is finite, linear or semilinear, is recursively undecidable. However, one can algorithmically decide whether or not a cell-differentiation system of finite cell-type can produce a specific generation of cells.     

A computational model of visual anisotropy

Visual anisotropy has been demonstrated in multiple tasks where performance differs between vertical, horizontal, and oblique orientations of the stimuli. We explain some principles of visual anisotropy by anisotropic smoothing, which is based on a variation on Koenderink's approach in [1]. We tested the theory by presenting gaussian elongated luminance profiles and measuring the perceived orientations by means of an adjustment task. Our framework is based on the smoothing of the image with elliptical gaussian kernels and it correctly predicted an illusory orientation bias towards the vertical axis. We discuss the scope of the theory in the context of other anisotropies in perception.     

A computational model for feature binding

The "Binding Problem" is an important problem across many disciplines, including psychology, neuroscience, computational modeling, and even philosophy. In this work, we proposed a novel computational model, Bayesian Linking Field Model, for feature binding in visual perception, by combining the idea of noisy neuron model, Bayesian method, Linking Field Network and competitive mechanism. Simulation Experiments demonstrated that our model perfectly fulfilled the task of feature binding in visual perception and provided us some enlightening idea for future research.     

A computational model of ameboid deformation and locomotion

Traditional continuum models of ameboid deformation and locomotion are limited by the computational difficulties intrinsic in free boundary conditions. A new model using the immersed boundary method overcomes these difficulties by representing the cell as a force field immersed in fluid domain. The forces can be derived from a direct mechanical interpretation of such cell components as the cell membrane, the actin cortex, and the transmembrane adhesions between the cytoskeleton and the substratum. The numerical cytoskeleton, modeled as a dynamic network of immersed springs, is able to qualitatively model the passive mechanical behavior of a shear-thinning viscoelastic fluid (Bottino 1997). The same network is used to generate active protrusive and contractile forces. When coordinated with the attachment-detachment cycle of the cell's adhesions to the substratum, these forces produce directed locomotion of the model ameba. With this model it is possible to study the effects of altering the numerical parameters upon the motility of the model cell in a manner suggestive of genetic deletion experiments. In the context of this ameboid cell model and its numerical implementation, simulations involving multicellular interaction, detailed internal signaling, and complex substrate geometries are tractable. Received: 5 January 1998 / Revised version: 23 March 1998 / Accepted: 26 March 1998     

Pattern formation and morphogenesis: A reaction-diffusion model

The problem of cellular differentiation and consequent pattern generation during embryonic development has been mathematically investigated with the help of a reaction-diffusion model. It is by now a well-recognized fact that diffusion of micromolecules (through intercellular gap junctions), which is dependent on the spatial parameter (r), serve the purpose of ‘positional information’ for differentiation. Based on this principle the present model has been constructed by coupling the Goodwin-type equations for RNA and protein synthesis with the diffusion process. The homogeneous Goodwin system can exhibit stable periodic solution if the value of the cooperativity as measured by the Hill coefficient (ρ) is greater than 8, which is not biologically realistic. In the present work it has been observed that inclusion of a negative cross-diffusion can drive the system into local instability for any value of ρ and thus a time-periodic spatial solution is possible around the unstable local equilibrium, eventually leading to a definite pattern formation. Inclusion of a negative cross-diffusion thus makes the system biologically realistic. The cross-diffusion can also give rise to a stationary wave-like dissipative structure.     

Water and ion permeability of a claudin model: A computational study

At present, the three‐dimensional structure of the multimeric paracellular claudin pore is unknown. Using extant biophysical data concerning the size of the pore and permeation of water and cations through it, two three‐dimensional models of the pore are constructed in silico. Molecular Dynamics (MD) calculations are then performed to compute water and sodium ion permeation fluxes under the influence of applied hydrostatic pressure. Comparison to experiment is made, under the assumption that the hydrostatic pressure applied in the simulations is equivalent to osmotic pressure induced in experimental measurements of water/ion permeability. One model, in which pore‐lining charged is distributed evenly over a selectivity filter section 10–16 Å in length, is found to be generally consistent with experimental data concerning the dependence of water and ion permeation on channel pore diameter, pore length, and the sign and magnitude of pore lining charge. The molecular coupling mechanism between water and ion flow under conditions where hydrostatic pressure is applied is computationally elucidated. Proteins 2016; 84:305–315. © 2016 Wiley Periodicals, Inc.     

A computational model of chemotaxis-based cell aggregation

We present a computational model that successfully captures the cell behaviors that play important roles in 2-D cell aggregation. A virtual cell in our model is designed as an independent, discrete unit with a set of parameters and actions. Each cell is defined by its location, size, rates of chemoattractant emission and response, age, life cycle stage, proliferation rate and number of attached cells. All cells are capable of emitting and sensing a chemoattractant chemical, moving, attaching to other cells, dividing, aging and dying. We validated and fine-tuned our in silico model by comparing simulated 24-h aggregation experiments with data derived from in vitro experiments using PC12 pheochromocytoma cells. Quantitative comparisons of the aggregate size distributions from the two experiments are produced using the Earth Mover's Distance (EMD) metric. We compared the two size distributions produced after 24 h of in vitro cell aggregation and the corresponding computer simulated process. Iteratively modifying the model's parameter values and measuring the difference between the in silico and in vitro results allow us to determine the optimal values that produce simulated aggregation outcomes closely matched to the PC12 experiments. Simulation results demonstrate the ability of the model to recreate large-scale aggregation behaviors seen in live cell experiments.     

A computational model of the human thyroid

The thyroid, the largest gland in the endocrine system, secretes hormones that help promote bodily growth and development. This gland regulates hormonal secretion rate in spite of changes in dietary iodine which is a key ingredient in the hormone's biosynthesis. The thyroid relies on several feedback mechanisms for this regulation, and in this paper we use recent molecular-level and clinical observations to engineer a computational thyroid model. We use simulation and analysis to show that this models captures known aspects of thyroid physiology. We identify features in the model that are responsible for hormonal regulation, and use the model to identify and evaluate competing hypotheses associated with Wolff-Chaikoff escape.     

A computational model of transmembrane integrin clustering

The presented work describes a structural model for integrin homooligomerization, focusing on the transmembrane domains. The two noncovalently linked integrin subunits, alpha and beta, were previously shown to homodimerize or homotrimerize, respectively. Our work is based on published mutational work that induced homotrimerization of beta3 integrins. The mutations provided structural restraints for the creation of a structural model of the beta3 homotrimer by a computational search of the conformational space of homomeric interactions of the beta3 integrin. Additionally, we explored possible conformations of the alphaIIb integrin homodimer, for which no unique solution was found. Two possible models of signal transduction, involving two different alphaIIb conformations, are discussed. One of the possible homodimeric alphaIIb conformations is GpA like, which is in line with experimental evidence. Based on our here-presented structural models and on recent experiments, we will argue that most probably the heteromeric alpha/beta transmembrane complex separates in the course of clustering.     

A computational model for telomere-dependent cell-replicative aging

Telomere shortening provides a molecular basis for the Hayflick limit. Recent data suggest that telomere shortening also influence mitotic rate. We propose a stochastic growth model of this phenomena, assuming that cell division in each time interval is a random process which probability decreases linearly with telomere shortening. Computer simulations of the proposed stochastic telomere-regulated model provides good approximation of the qualitative growth of cultured human mesenchymal stem cells.     

A computational model of intussusceptive microvascular growth and remodeling

Non-sprouting angiogenesis, also known as intussusceptive angiogenesis (IA), is an important modality of blood vessel morphogenesis in growing tissues. We present a novel computational framework for simulation of IA to answer some of the questions concerning the underlying mechanisms of the remodeling process. The model relies on mechanical interactions between blood and tissue, includes the structural maturation of the vessel wall, and is controlled by stimulating or inhibiting chemical agents. The model provides a simple explanation for the formation of microvessels and bifurcations from capillaries via IA, allowing for both maintenance and avoidance of shunt vessels. Detailed hemodynamic and transport properties for oxygen, metabolites or growth factors can be predicted. The model is an in silico framework for testing certain conceptual ideas about the mechanisms of intussusceptive growth and remodeling, in particular those related to mechanical and transport phenomena.     

A novel and versatile computational tool to model translation

MOTIVATION: Much is now known about the mechanistic details of gene translation. There are also rapid advances in high-throughput technologies to determine quantitative aspects of the system. As a consequence-realistic and system-wide simulation models of translation are now feasible. Such models are also needed as devices to integrate a large volume of highly fragmented data known about translation. Software: In this application note, we present a novel, highly efficient software tool to model translation. The tool represents the main aspects of translation. Features include a representation of exhaustible tRNA pools, ribosome-ribosome interactions and differential initiation rates for different mRNA species. The tool is written in Java, and is hence portable and can be parameterized for any organism. AVAILABILITY: The model can be obtained from the authors or directly downloaded from the authors' home-page (http://goo.gl/JUWvI).     

Appendix: A model of plaque formation

Equations describing plaque formation in soft agar have been based on certain simplifying assumptions, for which data are presented. The derived equations permit one to calculate (i) average plaque size as a function of the initial density of indicator cells (D_o), (ii) the number of cells lysed per plaque as a function of D_o, and (iii) the cumulative number of cells lysed at various stages of plaque development. The calculated values agree well with those determined experimentally.     

A computational model of selection by consequences: log survivor plots

[McDowell, J.J, 2004. A computational model of selection by consequences. J. Exp. Anal. Behav. 81, 297-317] instantiated the principle of selection by consequences in a virtual organism with an evolving repertoire of possible behaviors undergoing selection, reproduction, and mutation over many generations. The process is based on the computational approach, which is non-deterministic and rules-based. The model proposes a causal account for operant behavior. McDowell found that the virtual organism consistently showed a hyperbolic relationship between response and reinforcement rates according to the quantitative law of effect. To continue validation of the computational model, the present study examined its behavior on the molecular level by comparing the virtual organism's IRT distributions in the form of log survivor plots to findings from live organisms. Log survivor plots did not show the "broken-stick" feature indicative of distinct bouts and pauses in responding, although the bend in slope of the plots became more defined at low reinforcement rates. The shape of the virtual organism's log survivor plots was more consistent with the data on reinforced responding in pigeons. These results suggest that log survivor plot patterns of the virtual organism were generally consistent with the findings from live organisms providing further support for the computational model of selection by consequences as a viable account of operant behavior.     

The Freter model: A simple model of biofilm formation

A simple, conceptual model of biofilm formation, due to R. Freter et al. (1983), is studied analytically and numerically in both CSTR and PFR. Two steady state regimes are identified, namely, the complete washout of the microbes from the reactor and the successful colonization of both the wall and bulk fluid. One of these is stable for any particular set of parameter values and sharp and explicit conditions are given for the stability of each. The effects of adding an anti-microbial agent to the CSTR are examined.Supported by NSF Grant DMS 0107439 and UTA Grant REP 14748717Supported by NSF Grant DMS 0107160