SCI Publications

2009


D.F. Wang, R.M. Kirby, C.R. Johnson. “Finite Element Discretization Strategies for the Inverse Electrocardiographic (ECG) Problem,” In Proceedings of the 11th World Congress on Medical Physics and Biomedical Engineering, Munich, Germany, Vol. 25/2, pp. 729-732. September, 2009.


D.F. Wang, R.M. Kirby, C.R. Johnson. “Finite Element Refinements for Inverse Electrocardiography: Hybrid-Shaped Elements, High-Order Element Truncation and Variational Gradient Operator,” In Proceeding of Computers in Cardiology 2009, Park City, September, 2009.


Y. Wang, A.R.C. Paiva, J.C. Principe, J.C. Sanchez. “Sequential Monte Carlo Point Process Estimation of Kinematics from Neural Spiking Activity for Brain Machine Interfaces,” In Neural Computation, Vol. 21, No. 10, pp. 2894--2930. 2009.


D. Xiu, J. Shen. “Efficient Stochastic Galerkin Methods for Random Diffusion Equations,” In Journal of Computational Physics, Vol. 228, No. 2, pp. 266--281. 2009.
DOI: 10.1016/j.jcp.2008.09.008

ABSTRACT

We discuss in this paper efficient solvers for stochastic diffusion equations in random media. We employ generalized polynomial chaos (gPC) expansion to express the solution in a convergent series and obtain a set of deterministic equations for the expansion coefficients by Galerkin projection. Although the resulting system of diffusion equations are coupled, we show that one can construct fast numerical methods to solve them in a decoupled fashion. The methods are based on separation of the diagonal terms and off-diagonal terms in the matrix of the Galerkin system. We examine properties of this matrix and show that the proposed method is unconditionally stable for unsteady problems and convergent for steady problems with a convergent rate independent of discretization parameters. Numerical examples are provided, for both steady and unsteady random diffusions, to support the analysis.

Keywords: Generalized polynomial chaos, Stochastic Galerkin, Random diffusion, Uncertainty quantification


D. Xiu. “Fast Numerical Methods for Stochastic Computations: a Review,” In Communications in Computational Physics, Vol. 5, No. 2-4, pp. 242--272. 2009.
DOI: 10.1.1.148.5499

ABSTRACT

This paper presents a review of the current state-of-the-art of numerical methods for stochastic computations. The focus is on efficient high-order methods suitable for practical applications, with a particular emphasis on those based on generalized polynomial chaos (gPC) methodology. The framework of gPC is reviewed, along with its Galerkin and collocation approaches for solving stochastic equations. Properties of these methods are summarized by using results from literature. This paper also attempts to present the gPC based methods in a unified framework based on an extension of the classical spectral methods into multi-dimensional random spaces.

Keywords: Stochastic differential equations, generalized polynomial chaos, uncertainty quantification, spectral methods


F. Zhang, E.R. Hancock, C. Goodlett, G. Gerig. “Probabilistic White Matter Fiber Tracking using, Particle Filtering and von Mises-Fisher Sampling,” In Medical Image Analysis, Vol. 13, No. 1, pp. 5--18. 2009.
PubMed ID: 18602332

2008


G. Adluru, E.V.R. DiBella, C.J. McGann. “Data Acquisition and Reconstruction of Undersampled Radial MR Myocardial Perfusion,” In Proceedings of the 11th Annual Scientific Sessions of the Society for Cardiovascular Magnetic Resonance (SCMR) 2008, pp. 215. 2008.


G. Adluru, E.V.R. DiBella. “A Comparison of L1 and L2 Norms as Temporal Constraints for Reconstruction of Undersampled Dynamic Contrast Enhanced Cardiac Scans with Respiratory Motion,” In Proceedings of the 16th Scientific Meeting and Exhibition of the International Society for Magnetic Resonance in Medicine (ISMRM) 2008, pp. 340. 2008.


G. Adluru, E.V.R. DiBella. “Data Reordering for Improved Constrained Reconstruction from Undersampled k-space Data,” In Proceedings of the 16th Scientific Meeting and Exhibition of the International Society for Magnetic Resonance in Medicine (ISMRM) 2008, pp. 3153. 2008.


A.E. Anderson, B.J. Ellis, C.L. Peters, J.A. Weiss. “Cartilage Thickness: Factors Influencing Multidetector CT Measurements in a Phantom Study,” In Radiology, Vol. 246, No. 1, pp. 133-141. 2008.
PubMed ID: 18982614


A.E. Anderson, B.J. Ellis, S.A. Maas, C.L. Peters, J.A. Weiss. “Validation of Finite Element Predictions of Cartilage Contact Pressure in the Human Hip Joint,” In ASME Journal of Biomechanical Engineering, Vol. 130, No. 3, pp. 051008-1--10. May, 2008.


E.W. Anderson, J. Ahrens, K. Heitmann, S. Habib, C.T. Silva. “Provenance in Comparative Analysis: A Study in Cosmology,” In Computing in Science and Engineering, Vol. 10, No. 3, pp. 30--37. 2008.


A.E. Anderson, B.J. Ellis, C.L. Peters, J.A. Weiss. “Factors Influencing Cartilage Thickness Measurements with Multi-Detector CT: A Phantom Study,” In Radiology, Vol. 246, No. 1, pp. 144-141. 2008.


A. Baptista, B. Howe, J. Freire, D. Maier, C.T. Silva. “Scientific Exploration in the Era of Ocean Observatories,” In Computing in Science and Engineering, Vol. 10, No. 3, pp. 53--58. 2008.


L. Bavoil, S.P. Callahan, and C.T. Silva. “Robust Soft Shadow Mapping with Depth Peeling,” In Journal of Graphics Tools, Vol. 13, No. 1, pp. 19--30. 2008.


E.W. Bethel, H. Childs, A. Mascarenhas, V. Pascucci, Prabhat. “Scientific Data Management Challenges in High Performance Visual Data Analysis,” In Scientific Data Management: Challenges, Existing Technology, and Deployment, Chapman Hall/CRC Press, 2008.


D. Brayford, M. Turner, W.T. Hewitt. “A Physical Model for the Polarized Scattering of Light,” In Proceedings of The sixth Theory and Practice of Computer Graphics 2008 Conference (TPCG08), University of Manchester, UK, Note: Best Paper Award, June, 2008.


K. Buerger, P. Kondratieva, J. Krüger, R. Westermann. “Importance-Driven Particle Techniques for Flow Visualization,” In Proceedings of IEEE VGTC PacificVis 2008, pp. 71--78. 2008.


C.R. Butson, G.A. Clark. “Mechanisms of noise-induced improvement in light-intensity encoding in Hermissenda photoreceptor network,” In Journal of Neurophysiology, Vol. 99, No. 1, pp. 155--165. January, 2008.
ISSN: 0022-3077
DOI: 10.1152/jn.01250.2006
PubMed ID: 18003872

ABSTRACT

In a companion paper we showed that random channel and synaptic noise improve the ability of a biologically realistic, GENESIS-based computational model of the Hermissenda eye to encode light intensity. In this paper we explore mechanisms for noise-induced improvement by examining contextual spike-timing relationships among neurons in the photoreceptor network. In other systems, synaptically connected pairs of spiking cells can develop phase-locked spike-timing relationships at particular, well-defined frequencies. Consequently, domains of stability (DOS) emerge in which an increase in the frequency of inhibitory postsynaptic potentials can paradoxically increase, rather than decrease, the firing rate of the postsynaptic cell. We have extended this analysis to examine DOS as a function of noise amplitude in the exclusively inhibitory Hermissenda photoreceptor network. In noise-free simulations, DOS emerge at particular firing frequencies of type B and type A photoreceptors, thus producing a nonmonotonic relationship between their firing rates and light intensity. By contrast, in the noise-added conditions, an increase in noise amplitude leads to an increase in the variance of the interspike interval distribution for a given cell; in turn, this blocks the emergence of phase locking and DOS. These noise-induced changes enable the eye to better perform one of its basic tasks: encoding light intensity. This effect is independent of stochastic resonance, which is often used to describe perithreshold stimuli. The constructive role of noise in biological signal processing has implications both for understanding the dynamics of the nervous system and for the design of neural interface devices.

Keywords: Action Potentials, Action Potentials: physiology, Animals, Artifacts, Computer Simulation, Eye, Eye: cytology, Hermissenda, Hermissenda: physiology, Invertebrate, Invertebrate: physiology, Nerve Net, Nerve Net: physiology, Neurons, Neurons: physiology, Ocular, Ocular Physiological Phenomena, Ocular: physiology, Photic Stimulation, Photoreceptor Cells, Reaction Time, Reaction Time: physiology, Sensory Thresholds, Sensory Thresholds: physiology, Synaptic Transmission, Synaptic Transmission: physiology, Vision


C.R. Butson, G.A. Clark. “Random noise paradoxically improves light-intensity encoding in Hermissenda photoreceptor network,” In Journal of Neurophysiology, Vol. 99, No. 1, pp. 146--154. January, 2008.
ISSN: 0022-3077
DOI: 10.1152/jn.01247.2006
PubMed ID: 18003873

ABSTRACT

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Neurons are notoriously noisy devices. Although the traditional view posits that noise degrades system performance, recent evidence suggests that noise may instead enhance neural information processing under certain conditions. Here we report that random channel and synaptic noise improve the ability of a biologically realistic computational model of the Hermissenda eye to encode light intensity. The model was created in GENESIS and is based on a previous model used to examine effects of changes in type B photoreceptor excitability, synaptic strength, and network architecture. The network consists of two type A and three type B multicompartmental photoreceptors. Each compartment contains a population of Hodgkin-Huxley-type ion channels and each cell is stimulated via artificial light currents. We found that the addition of random channel and synaptic noise yielded a significant improvement in the accuracy of the network's encoding of light intensity across eight light levels spanning 3.5 log units (P

Keywords: Action Potentials, Action Potentials: physiology, Animals, Artifacts, Computer Simulation, Eye, Eye: cytology, Hermissenda, Hermissenda: physiology, Invertebrate, Invertebrate: physiology, Nerve Net, Nerve Net: physiology, Neurons, Neurons: physiology, Ocular, Ocular Physiological Phenomena, Ocular: physiology, Photic Stimulation, Photoreceptor Cells, Reaction Time, Reaction Time: physiology, Sensory Thresholds, Sensory Thresholds: physiology, Synaptic Transmission, Synaptic Transmission: physiology, Vision