Hidden Markov models for the stimulus-response relationships of multistate neural systems

Given recent experimental results suggesting that neural circuits may evolve through multiple firing states, we develop a framework for estimating state-dependent neural response properties from spike train data. We modify the traditional hidden Markov model (HMM) framework to incorporate stimulus-driven, non-Poisson point-process observations. For maximal flexibility, we allow external, time-varying stimuli and the neurons' own spike histories to drive both the spiking behavior in each state and the transitioning behavior between states. We employ an appropriately modified expectation-maximization algorithm to estimate the model parameters. The expectation step is solved by the standard forward-backward algorithm for HMMs. The maximization step reduces to a set of separable concave optimization problems if the model is restricted slightly. We first test our algorithm on simulated data and are able to fully recover the parameters used to generate the data and accurately recapitulate the sequence of hidden states. We then apply our algorithm to a recently published data set in which the observed neuronal ensembles displayed multistate behavior and show that inclusion of spike history information significantly improves the fit of the model. Additionally, we show that a simple reformulation of the state space of the underlying Markov chain allows us to implement a hybrid half-multistate, half-histogram model that may be more appropriate for capturing the complexity of certain data sets than either a simple HMM or a simple peristimulus time histogram model alone.     

Using GPU Shaders for Visualization

GPU shaders seem used mostly for gaming and other forms of entertainment and simulation. But they have less-obvious visualization uses, for the same reasons that interest the gaming community: improved appearance and performance. This column looks at the use of shaders and the OpenGL shading language (GLSL) in two common visualization applications: point clouds and contour cutting planes.     

Accelerating geoscience and engineering system simulations on graphics hardware

Many complex natural systems studied in the geosciences are characterized by simple local-scale interactions that result in complex emergent behavior. Simulations of these systems, often implemented in parallel using standard central processing unit (CPU) clusters, may be better suited to parallel processing environments with large numbers of simple processors. Such an environment is found in graphics processing units (GPUs) on graphics cards.This paper discusses GPU implementations of three example applications from computational fluid dynamics, seismic wave propagation, and rock magnetism. These candidate applications involve important numerical modeling techniques, widely employed in physical system simulations, that are themselves examples of distinct computing classes identified as fundamental to scientific and engineering computing. The presented numerical methods (and respective computing classes they belong to) are: (1) a lattice-Boltzmann code for geofluid dynamics (structured grid class); (2) a spectral-finite-element code for seismic wave propagation simulations (sparse linear algebra class); and (3) a least-squares minimization code for interpreting magnetic force microscopy data (dense linear algebra class). Significant performance increases (between 10× and 30× in most cases) are seen in all three applications, demonstrating the power of GPU implementations for these types of simulations and, more generally, their associated computing classes.     

Implementation of wide-field integration of optic flow for autonomous quadrotor navigation

Insects are capable of robust visual navigation in complex environments using efficient information extraction and processing approaches. This paper presents an implementation of insect inspired visual navigation that uses spatial decompositions of the instantaneous optic flow to extract local proximity information. The approach is demonstrated in a corridor environment on an autonomous quadrotor micro-air-vehicle (MAV) where all the sensing and processing, including altitude, attitude, and outer loop control is performed on-board. The resulting methodology has the advantages of computation speed and simplicity, hence are consistent with the stringent size, weight, and power requirements of MAVs.     

Electromyography of the thigh muscles during lifting tasks in kneeling and squatting postures

Underground coal miners who work in low-seam mines frequently handle materials in kneeling or squatting postures. To assess quadriceps and hamstring muscle demands in these postures, nine participants performed lateral load transfers in kneeling and squatting postures, during which electromyographic (EMG) data were collected. EMG activity was obtained at five points throughout the transfer for three quadriceps muscles and two hamstring muscles from each thigh. ANOVA results indicated that EMG data for nine of 10 thigh muscles were affected by an interaction between posture and angular position of the load lifted (p < 0.001). Muscles of the right thigh were most active during the lifting portion of the task (lifting a block from the participant's right) and activity decreased as the block was transferred to the left. Left thigh muscles showed the opposite pattern. EMG activity for the majority of thigh muscles was affected by the size of the base of support provided by different postures, with lower EMG activity observed with a larger base of support and increased activity in postures where base of support was reduced (p < 0.05). Thigh EMG activity was lowest in postures with fully flexed knees, which may explain worker preference for this posture. However, such postures are also associated with increased risk of meniscal damage. STATEMENT OF RELEVANCE: Kneeling and squatting postures are sometimes used for manual lifting activities, but are associated with increased knee injury risk. This paper examines the EMG responses of knee extensors/flexors to lifting in these postures, discusses the impact of posture and kneepads on muscle recruitment and explores the implications for work in such postures.     

Cloud computing — The business perspective

The evolution of cloud computing over the past few years is potentially one of the major advances in the history of computing. However, if cloud computing is to achieve its potential, there needs to be a clear understanding of the various issues involved, both from the perspectives of the providers and the consumers of the technology. While a lot of research is currently taking place in the technology itself, there is an equally urgent need for understanding the business-related issues surrounding cloud computing. In this article, we identify the strengths, weaknesses, opportunities and threats for the cloud computing industry. We then identify the various issues that will affect the different stakeholders of cloud computing. We also issue a set of recommendations for the practitioners who will provide and manage this technology. For IS researchers, we outline the different areas of research that need attention so that we are in a position to advice the industry in the years to come. Finally, we outline some of the key issues facing governmental agencies who, due to the unique nature of the technology, will have to become intimately involved in the regulation of cloud computing.     

The BIOPHILE Sample Process Management System - Automated Sample Access at Ultra Low Temperatures

The genomics, proteomics, clinical, and drug discovery laboratories have a growing need to maintain valuable samples at ultra-low (−80°C) temperatures in a validated, secure environment. Automated sample processing systems have until now required manual (off-line) storage of samples at −80°C, reducing system reliability and speed. Both of these important needs are addressed by the Sample Process Management System being introduced by BIOPHILE Inc. Conventional sample management processes, such as storage, retrieval, and cataloging, are increasingly strained by the growing sample populations. There are variable sample types, access requirements and storage requirements. Security and inventory procedures are implemented manually. The evolving technologies present in the laboratory cannot interface with conventional manual storage techniques. Addressing these limitations, the primary benefits of BIOPHILE's solutions are:

• Fully validated sample management process that coordinates the life-cycles of samples and their related data.

• Robotic technology to securely store and retrieve samples, improving their accessibility and stability. Thermal shock is reduced, improving sample longevity and quality. The robotic technology allows integration with larger automation systems.

• A process program to develop a Sample Management Strategy. This strategy is developed by analyzing long-term research goals, current baseline processes, and identification of current sample life cycles. A full validation documentation package can be generated, providing a high level of quality assurance.

• Improved sample visibility and quality assurance - automated sample population cataloging; controlled sample management access and security.

     

Real-time path planning in dynamic virtual environments using multiagent navigation graphs

We present a novel approach for efficient path planning and navigation of multiple virtual agents in complex dynamic scenes. We introduce a new data structure, Multi-agent Navigation Graph (MaNG), which is constructed using first- and second-order Voronoi diagrams. The MaNG is used to perform route planning and proximity computations for each agent in real time. Moreover, we use the path information and proximity relationships for local dynamics computation of each agent by extending a social force model [Helbing05]. We compute the MaNG using graphics hardware and present culling techniques to accelerate the computation. We also address undersampling issues and present techniques to improve the accuracy of our algorithm. Our algorithm is used for real-time multi-agent planning in pursuit-evasion, terrain exploration and crowd simulation scenarios consisting of hundreds of moving agents, each with a distinct goal.     

Halogenated ligands and their interactions with amino acids: implications for structure-activity and structure-toxicity relationships

The properties of chemicals are rooted in their molecular structure. It follows that structural analysis of specific interactions between ligands and biomolecules at the molecular level is invaluable for defining structure-activity relationships (SARs) and structure-toxicity relationships (STRs). This study has elucidated the structural and molecular basis of interactions of biomolecules with alkyl and aryl halides that are extensively used as components in many commercial pesticides, disinfectants, and drugs. We analyzed the protein structures deposited in Protein Data Bank (PDB) for structural information associated with interactions between halogenated ligands and proteins. This analysis revealed distinct patterns with respect to the nature and structural characteristics of halogen interactions with specific types of atoms and groups in proteins. Fluorine had the highest propensity of interactions for glycine, while chlorine for leucine, bromine for arginine, and iodine for lysine. Chlorine, bromine and iodine had the lowest propensity of interactions for cysteine, while fluorine had a lowest propensity for proline. These trends for highest propensity shifted towards the hydrophobic residues for all the halogens when only interactions with the side chain were considered. Halogens had equal propensities of interaction for the halogen bonding partners (nitrogen and oxygen atoms), albeit with different geometries. The optimal angle for interactions with halogens was approximately 120 degrees for oxygen atoms, and approximately 96 degrees for nitrogen atoms. The distance distributions of halogens with various amino acids were mostly bimodal, and the angle distributions were unimodal. Insights gained from this study have implications for the rational design of safer drugs and commercially important chemicals.     

Arthemis: annotation software in an integrated capturing and analysis system for colonoscopy

Colonoscopy is an endoscopic technique that allows physicians to inspect the inside of the human colon. During a colonoscopic procedure, a tiny video camera at the tip of the endoscope generates a video signal of the internal mucosa of the colon. In current practice, the entire colonoscopic procedure is not routinely captured. Software tools providing easy access to important contents of videos that are digitally captured during colonoscopy are not available. Hence, it is very time consuming to review an entire video, locate important contents, annotate them, and extract the annotated contents for research, teaching, and training purposes. Arthemis, a software application, was developed to facilitate this process. For convenient data sharing, Arthemis allows annotation according to the European Gastrointestinal Society for Endoscopy (ESGE) Minimal Standard Terminology (MST), an internationally accepted standard for digestive endoscopy. Arthemis is part of our integrated capturing and content analysis system for colonoscopy called Endoscopic Multimedia Information System (EMIS). This paper presents Arthemis as a component of EMIS, the design and implementation of Arthemis, and key lessons learned from the development process.