Model-based influences on humans' choices and striatal prediction errors.

The mesostriatal dopamine system is prominently implicated in model-free reinforcement learning, with fMRI BOLD signals in ventral striatum notably covarying with model-free prediction errors. However, latent learning and devaluation studies show that behavior also shows hallmarks of model-based planning, and the interaction between model-based and model-free values, prediction errors, and preferences is underexplored. We designed a multistep decision task in which model-based and model-free influences on human choice behavior could be distinguished. By showing that choices reflected both influences we could then test the purity of the ventral striatal BOLD signal as a model-free report. Contrary to expectations, the signal reflected both model-free and model-based predictions in proportions matching those that best explained choice behavior. These results challenge the notion of a separate model-free learner and suggest a more integrated computational architecture for high-level human decision-making.

An expressive text-driven 3D talking head

Creating a realistic talking head, which given an arbitrary text as input generates a realistic looking face speaking the text, has been a long standing research challenge. Talking heads which cannot express emotion have been made to look very realistic by using concatenative approaches [Wang et al. 2011], however allowing the head to express emotion creates a much more challenging problem and model based approaches have shown promise in this area. While 2D talking heads currently look more realistic than their 3D counterparts, they are limited both in the range of poses they can express and in the lighting conditions that they can be rendered under. Previous attempts to produce videorealistic 3D expressive talking heads [Cao et al. 2005] have produced encouraging results but not yet achieved the level of realism of their 2D counterparts.

How neurons migrate: a dynamic in-silico model of neuronal migration in the developing cortex.

BACKGROUND: Neuronal migration, the process by which neurons migrate from their place of origin to their final position in the brain, is a central process for normal brain development and function. Advances in experimental techniques have revealed much about many of the molecular components involved in this process. Notwithstanding these advances, how the molecular machinery works together to govern the migration process has yet to be fully understood. Here we present a computational model of neuronal migration, in which four key molecular entities, Lis1, DCX, Reelin and GABA, form a molecular program that mediates the migration process. RESULTS: The model simulated the dynamic migration process, consistent with in-vivo observations of morphological, cellular and population-level phenomena. Specifically, the model reproduced migration phases, cellular dynamics and population distributions that concur with experimental observations in normal neuronal development. We tested the model under reduced activity of Lis1 and DCX and found an aberrant development similar to observations in Lis1 and DCX silencing expression experiments. Analysis of the model gave rise to unforeseen insights that could guide future experimental study. Specifically: (1) the model revealed the possibility that under conditions of Lis1 reduced expression, neurons experience an oscillatory neuron-glial association prior to the multipolar stage; and (2) we hypothesized that observed morphology variations in rats and mice may be explained by a single difference in the way that Lis1 and DCX stimulate bipolar motility. From this we make the following predictions: (1) under reduced Lis1 and enhanced DCX expression, we predict a reduced bipolar migration in rats, and (2) under enhanced DCX expression in mice we predict a normal or a higher bipolar migration. CONCLUSIONS: We present here a system-wide computational model of neuronal migration that integrates theory and data within a precise, testable framework. Our model accounts for a range of observable behaviors and affords a computational framework to study aspects of neuronal migration as a complex process that is driven by a relatively simple molecular program. Analysis of the model generated new hypotheses and yet unobserved phenomena that may guide future experimental studies. This paper thus reports a first step toward a comprehensive in-silico model of neuronal migration.

Degenerate four-wave-mixing signals from dc- and ac-driven semiconductor superlattice

Within the one-dimensional tight-binding model;rnd chi-3 approximation, we have calculated four-wave-mixing (FWM) signals for a semiconductor superlattice in the presence of both static and high-frequency electric fields. When the exciton effect is negligible, the time-periodic field dynamically delocalizes the otherwise localized Wannier-Stark states, and accordingly quasienergy band structures are formed, and manifest in the FWM spectra as a series of equally separated continua. The width of each continuum is proportional to the joint width of the valence and conduction minibands and is independent of the Wannier-Stark index. The realistic homogeneous broadening blurs the continua into broad peaks, whose line shapes, far from the Lorentzian, vary with the delay time in the FWM spectra. The swinging range of the peaks is just the quasienergy bandwidth. The dynamical delocalization (DDL) also induces significant FWM signals well beyond the excitation energy window. When the Coulomb interaction is taken into account, the unequal spacing between the excitonic Wannier-Stark levels weakens the DDL effect, and the FWM spectrum is transformed into groups of discrete lines. Strikingly, the groups are evenly spaced by the ac field frequency, reflecting the characteristic of the quasienergy states. The homogeneous broadening again smears out the line structures, leading to the excitonic FWM spectra quite similar to those without the exciton effect. However, all these features predicted by the dynamical theory do not appear in a recent experiment [Phys. Rev. Lett. 79, 301 (1997)], in which, by using the static approximation the observed Wannier-Stark ladder with delay-time-dependent spacing in the FWM spectra is attributed to a temporally periodic dipole field, produced by the Bloch oscillation of electrons in real space. The contradiction between the dynamical theory and the experiments is discussed. In addition, our calculation indicates that the dynamical localization coherently enhances the time-integrated FWM signals. The feasibility of using such a technique to study the dynamical localization phenomena is shown. [S0163-1829(99)10607-6].

Pipeline Architecture and Parallel Computation-Based Real-Time Stereovision Tracking System for Surgical Navigation

This paper studies the development of a real-time stereovision system to track multiple infrared markers attached to a surgical instrument. Multiple stages of pipeline in field-programmable gate array (FPGA) are developed to recognize the targets in both left and right image planes and to give each target a unique label. The pipeline architecture includes a smoothing filter, an adaptive threshold module, a connected component labeling operation, and a centroid extraction process. A parallel distortion correction method is proposed and implemented in a dual-core DSP. A suitable kinematic model is established for the moving targets, and a novel set of parallel and interactive computation mechanisms is proposed to position and track the targets, which are carried out by a cross-computation method in a dual-core DSP. The proposed tracking system can track the 3-D coordinate, velocity, and acceleration of four infrared markers with a delay of 9.18 ms. Furthermore, it is capable of tracking a maximum of 110 infrared markers without frame dropping at a frame rate of 60 f/s. The accuracy of the proposed system can reach the scale of 0.37 mm RMS along the x- and y-directions and 0.45 mm RMS along the depth direction (the depth is from 0.8 to 0.45 m). The performance of the proposed system can meet the requirements of applications such as surgical navigation, which needs high real time and accuracy capability.

Pipeline Architecture and Parallel Computation-Based Real-Time Stereovision Tracking System for Surgical Navigation

This paper studies the development of a real-time stereovision system to track multiple infrared markers attached to a surgical instrument. Multiple stages of pipeline in field-programmable gate array (FPGA) are developed to recognize the targets in both left and right image planes and to give each target a unique label. The pipeline architecture includes a smoothing filter, an adaptive threshold module, a connected component labeling operation, and a centroid extraction process. A parallel distortion correction method is proposed and implemented in a dual-core DSP. A suitable kinematic model is established for the moving targets, and a novel set of parallel and interactive computation mechanisms is proposed to position and track the targets, which are carried out by a cross-computation method in a dual-core DSP. The proposed tracking system can track the 3-D coordinate, velocity, and acceleration of four infrared markers with a delay of 9.18 ms. Furthermore, it is capable of tracking a maximum of 110 infrared markers without frame dropping at a frame rate of 60 f/s. The accuracy of the proposed system can reach the scale of 0.37 mm RMS along the x- and y-directions and 0.45 mm RMS along the depth direction (the depth is from 0.8 to 0.45 m). The performance of the proposed system can meet the requirements of applications such as surgical navigation, which needs high real time and accuracy capability.

Smoothing LDA Model for Text Categorization

Abstract. Latent Dirichlet Allocation (LDA) is a document level language model. In general, LDA employ the symmetry Dirichlet distribution as prior of the topic-words’ distributions to implement model smoothing. In this paper, we propose a data-driven smoothing strategy in which probability mass is allocated from smoothing-data to latent variables by the intrinsic inference procedure of LDA. In such a way, the arbitrariness of choosing latent variables'priors for the multi-level graphical model is overcome. Following this data-driven strategy,two concrete methods, Laplacian smoothing and Jelinek-Mercer smoothing, are employed to LDA model. Evaluations on different text categorization collections show data-driven smoothing can significantly improve the performance in balanced and unbalanced corpora.

Friction phenomena and phase transition in the underdamped two-dimensional Frenkel-Kontorova model

Locked-to-sliding phase transition has been studied in the driven two-dimensional Frenkel-Kontorova model with the square symmetric substrate potential. It is found that as the driving force increases, the system transfers from the locked state to the sliding state where the motion of particles is in the direction different from that of driving force. With the further increase in driving force, at some critical value, the particles start to move in the direction of driving force. These two critical forces, the static friction or depinning force, and the kinetic friction force for which particles move in the direction of driving force have been analyzed for different system parameters. Different scenarios of phase transitions have been examined and dynamical phases are classified. In the case of zero misfit angle, the analytical expressions for static and kinetic friction force have been obtained.

Daunomycin binding to detergent micelles: A model system for evaluating the hydrophobic contribution to drug-DNA interactions

The interaction of daunomycin with sodium dodecyl sulfate and Triton X-100 micelles was investigated as a model for the hydrophobic contribution to the free energy of DNA intercalation reactions. Measurements of visible absorbance, fluorescence lifetime, steady-state fluorescence emission intensity, and fluorescence anisotropy indicate that the anthraquinone ring partitions into the hydrophobic micelle interior. Fluorescence quenching experiments using both steady-state and lifetime measurements demonstrate reduced accessibility of daunomycin in sodium dodecyl sulfate micelles to the anionic quencher iodide and to the neutral quencher acrylamide. Quenching of daunomycin fluorescence by iodide in Triton X-100 micelles was similar to that seen with free daunomycin. Studies of the energetics of the interaction of daunomycin with micelles by fluorescence and absorbance titration methods and by isothermal titration calorimetry in the presence of excess micelles revealed that association with sodium dodecyl sulfate and Triton X-100 micelles is driven by a large negative enthalpy. Association of the drug with both types of micelles also has a favorable entropic contribution, which is larger in magnitude for Triton X-100 micelles than for sodium dodecyl sulfate micelles.

VEGF gene silencing by cytomegalovirus promoter driven ShRNA expression vector results in vascular development defects in zebrafish

Zebrafish has been generally considered as an excellent model in case of drug screening, disease model establishment, and vertebrate embryonic development study. In this work, the ability of human cytomegalovirus immediate early promoter (CMV promoter)-driven short hairpin RNA (shRNA) expression vector to induce shRNA against VEGF gene in zebrafish was tested, and its effect on vascular development was assed, too. Using RT-qPCR, blood vessel staining, and in situ hybridization, we confirmed certain transcriptional activity and down regulation of gene expression by the vector. In situ hybridization analysis indicated selective inhibition of NRP1 expression in the VEGF gene loss of function model, which might imply in turn that VEGF could not only activate endothelial cells directly but also could contribute to stimulating angiogenesis in vivo by a mechanism that involved up-regulation of its cognate receptor expression in zebrafish. This contributed to a better understanding of molecular mechanisms of cardiovascular development. The system improved the success rate in making inducible knockdown and widened the possibilities for better therapeutic targets in zebrafish.

A microwave emissivity model of sea surface under wave breaking

With the effective medium approximation theory of composites, a remedial model is proposed for estimating the microwave emissivity of sea surface under wave breaking driven by strong wind on the basis of an empirical model given by Pandey and Kakar. In our model, the effects of the shapes of seawater droplets and the thickness of whitecap layer (i.e. a composite layer of air and sea water droplets) over the sea surface on the microwave emissivity are investigated by calculating the effective dielectric constant of whitecaps layer. The wind speed is included in our model, and the responses of water droplets shapes, such as sphere and ellipsoid, to the emissivity are also discussed at different microwave frequencies. The model is in good agreement with the experimental data of microwave emissivity of sea surface at microwave frequencies of 6.6, 10.7 and 37GHz.

Towards an Example-Based Image Compression Architecture for Video-Conferencing

This paper consists of two major parts. First, we present the outline of a simple approach to very-low bandwidth video-conferencing system relying on an example-based hierarchical image compression scheme. In particular, we discuss the use of example images as a model, the number of required examples, faces as a class of semi-rigid objects, a hierarchical model based on decomposition into different time-scales, and the decomposition of face images into patches of interest. In the second part, we present several algorithms for image processing and animation as well as experimental evaluations. Among the original contributions of this paper is an automatic algorithm for pose estimation and normalization. We also review and compare different algorithms for finding the nearest neighbors in a database for a new input as well as a generalized algorithm for blending patches of interest in order to synthesize new images. Finally, we outline the possible integration of several algorithms to illustrate a simple model-based video-conference system.

A Model for Deliberation, Action, and Introspection

This thesis investigates the problem of controlling or directing the reasoning and actions of a computer program. The basic approach explored is to view reasoning as a species of action, so that a program might apply its reasoning powers to the task of deciding what inferences to make as well as deciding what other actions to take. A design for the architecture of reasoning programs is proposed. This architecture involves self-consciousness, intentional actions, deliberate adaptations, and a form of decision-making based on dialectical argumentation. A program based on this architecture inspects itself, describes aspects of itself, and uses this self-reference and these self-descriptions in making decisions and taking actions. The program's mental life includes awareness of its own concepts, beliefs, desires, intentions, inferences, actions, and skills. All of these are represented by self-descriptions in a single sort of language, so that the program has access to all of these aspects of itself, and can reason about them in the same terms.

Pancreatic and adrenal development and function in an ovine model of polycystic ovary syndrome.

Polycystic Ovary Syndrome (PCOS) is a complex disorder encompassing reproductive and metabolic dysfunction. Ovarian hyperandrogenism is an endocrine hallmark of human PCOS. In animal models, PCOS-like abnormalities can be recreated by in utero over-exposure to androgenic steroid hormones. This thesis investigated pancreatic and adrenal development and function in a unique model of PCOS. Fetal sheep were directly exposed (day 62 and day 82 of gestation) to steroidal excesses - androgen excess (testosterone propionate - TP), estrogen excess (diethylstilbestrol - DES) or glucocorticoid excess (dexamethasone - DEX). At d90 gestation there was elevated expression of genes involved in β- cell development and function: PDX-1 (P<0.001), and INS (P<0.05), INSR (P<0.05) driven by androgenic excess only in the female fetal pancreas. β- cell numbers (P<0.001) and in vitro insulin secretion (P<0.05) were also elevated in androgen exposed female fetuses. There was a significant increase in insulin secreting β-cell numbers (P<0.001) and in vivo insulin secretion (glucose stimulated) (P<0.01) in adult female offspring, specifically associated with prenatal androgen excess. At d90 gestation, female fetal adrenal gene expression was perturbed by fetal estrogenic exposure. Male fetal adrenal gene expression was altered more dramatically by fetal glucocorticoid exposure. In female adult offspring from androgen exposed pregnancies there was increased adrenal steroidogenic gene expression and in vivo testosterone secretion (P<0.01). This highlights that the adrenal glands may contribute towards excess androgen secretion in PCOS, but such effects might be secondary to other metabolic alterations driven by prenatal androgen exposure, such as excess insulin secretion Thus there may be dialogue between the pancreas and adrenal gland, programmed during early life, with implications for adult health Given both hyperinsulinaemia and hyperandrogenism are common features in PCOS, we suggest that their origins may be at least partially due to altered fetal steroidal environments, specifically excess androgenic stimulation

Steady drainage in emulsions: corrections for surface Plateau borders and a model for high aqueous volume fraction

Peron, N., Cox, S.J., Hutzler, S. and Weaire, D. (2007) Steady drainage in emulsions: corrections for surface Plateau borders and a model for high aqueous volume fraction. The European Physical Journal E - Soft Matter. 22: 341-351. Sponsorship: This research was supported by the European Space Agency (14914/02/NL/SH, 14308/00/NL/SG) (AO-99-031) CCN 002 MAP Project AO-99-075) and Science Foundation Ireland (RFP 05/RFP/PHY0016). SJC acknowledges support from EPSRC (EP/D071127/1).