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Biological Visualization, Imaging and Simulation(Bio-VIS) at NASA Ames Research Center: Developing New Software and Technology for Astronaut Training and Biology Research in Space

The Bio- Visualization, Imaging and Simulation (BioVIS) Technology Center at NASA's Ames Research Center is dedicated to developing and applying advanced visualization, computation and simulation technologies to support NASA Space Life Sciences research and the objectives of the Fundamental Biology Program. Research ranges from high resolution 3D cell imaging and structure analysis, virtual environment simulation of fine sensory-motor tasks, computational neuroscience and biophysics to biomedical/clinical applications. Computer simulation research focuses on the development of advanced computational tools for astronaut training and education. Virtual Reality (VR) and Virtual Environment (VE) simulation systems have become important training tools in many fields from flight simulation to, more recently, surgical simulation. The type and quality of training provided by these computer-based tools ranges widely, but the value of real-time VE computer simulation as a method of preparing individuals for real-world tasks is well established. Astronauts routinely use VE systems for various training tasks, including Space Shuttle landings, robot arm manipulations and extravehicular activities (space walks). Currently, there are no VE systems to train astronauts for basic and applied research experiments which are an important part of many missions. The Virtual Glovebox (VGX) is a prototype VE system for real-time physically-based simulation of the Life Sciences Glovebox where astronauts will perform many complex tasks supporting research experiments aboard the International Space Station. The VGX consists of a physical display system utilizing duel LCD projectors and circular polarization to produce a desktop-sized 3D virtual workspace. Physically-based modeling tools (Arachi Inc.) provide real-time collision detection, rigid body dynamics, physical properties and force-based controls for objects. The human-computer interface consists of two magnetic tracking devices (Ascention Inc.) attached to instrumented gloves (Immersion Inc.) which co-locate the user's hands with hand/forearm representations in the virtual workspace. Force-feedback is possible in a work volume defined by a Phantom Desktop device (SensAble inc.). Graphics are written in OpenGL. The system runs on a 2.2 GHz Pentium 4 PC. The prototype VGX provides astronauts and support personnel with a real-time physically-based VE system to simulate basic research tasks both on Earth and in the microgravity of Space. The immersive virtual environment of the VGX also makes it a useful tool for virtual engineering applications including CAD development, procedure design and simulation of human-system systems in a desktop-sized work volume.

Smith, Jeffrey

Introduction to Concepts in Artificial Neural Networks

This introduction to artificial neural networks summarizes some basic concepts of computational neuroscience and the resulting models of artificial neurons. The terminology of biological and artificial neurons, biological and machine learning and neural processing is introduced. The concepts of supervised and unsupervised learning are explained with examples from the power system area. Finally, a taxonomy of different types of neurons and different classes of artificial neural networks is presented.

Artificial Neural

Introduction to NASA Goddard Workshop on Artificial Intelligence

Artificial Intelligence (AI) is a collection of advanced technologies that allows machines to think and act, both humanly and rationally, through sensing, comprehending, acting and learning. AI's foundations lie at the intersection of several traditional fields Philosophy, Mathematics, Economics, Neuroscience, Psychology and Computer Science. Although the inception of AI started in the 1950's, it has recently made a strong comeback in all aspects of society and all over the world; this is mainly due to the timely combination of increased data volumes, advanced and mature algorithms, and improvements in computing power and storage. Current AI applications include big data analytics, robotics, intelligent sensing, assisted decision making, and speech recognition just to name a few.This workshop will be investigating how AI technologies can be adapted or developed to address the following challenges: Discover events of interest and correlations in large amounts of science data; improve the outcomes of science modeling and data assimilation using improved data processing, integration, and analysis. Design advisors for mission planning and operations, including anomaly detection and spacecraft health monitoring. Develop tools for engineering support, including advanced manufacturing, orbit determination, new component design and system engineering. Customize intelligent user interfaces, including visual analytics and natural language processing.

Le Moigne, Jacqueline

Overview of Artificial Intelligence (AI) at NASA Goddard

Artificial Intelligence (AI) is a collection of advanced technologies that allows machines to think and act, both humanly and rationally, through sensing, comprehending, acting and learning. AI's foundations lie at the intersection of several traditional fields Philosophy, Mathematics, Economics, Neuroscience, Psychology and Computer Science. Although the inception of AI started in the 1950's, it has recently made a strong comeback in all aspects of society and all over the world; this is mainly due to the timely combination of increased data volumes, advanced and mature algorithms, and improvements in computing power and storage. Current AI applications include big data analytics, robotics, intelligent sensing, assisted decision making, and speech recognition just to name a few. During the Tour, we will show a few examples of the current AI activities at NASA Goddard.

Le Moigne, Jacqueline

Sensing and perception: Connectionist approaches to subcognitive computing

New approaches to machine sensing and perception are presented. The motivation for crossdisciplinary studies of perception in terms of AI and neurosciences is suggested. The question of computing architecture granularity as related to global/local computation underlying perceptual function is considered and examples of two environments are given. Finally, the examples of using one of the environments, UCLA PUNNS, to study neural architectures for visual function are presented.

Skrrypek, J.

Computational Approaches to Vestibular Research

The Biocomputation Center at NASA Ames Research Center is dedicated to a union between computational, experimental and theoretical approaches to the study of neuroscience and of life sciences in general. The current emphasis is on computer reconstruction and visualization of vestibular macular architecture in three-dimensions (3-D), and on mathematical modeling and computer simulation of neural activity in the functioning system. Our methods are being used to interpret the influence of spaceflight on mammalian vestibular maculas in a model system, that of the adult Sprague-Dawley rat. More than twenty 3-D reconstructions of type I and type II hair cells and their afferents have been completed by digitization of contours traced from serial sections photographed in a transmission electron microscope. This labor-intensive method has now been replace d by a semiautomated method developed in the Biocomputation Center in which conventional photography is eliminated. All viewing, storage and manipulation of original data is done using Silicon Graphics workstations. Recent improvements to the software include a new mesh generation method for connecting contours. This method will permit the investigator to describe any surface, regardless of complexity, including highly branched structures such as are routinely found in neurons. This same mesh can be used for 3-D, finite volume simulation of synapse activation and voltage spread on neuronal surfaces visualized via the reconstruction process. These simulations help the investigator interpret the relationship between neuroarchitecture and physiology, and are of assistance in determining which experiments will best test theoretical interpretations. Data are also used to develop abstract, 3-D models that dynamically display neuronal activity ongoing in the system. Finally, the same data can be used to visualize the neural tissue in a virtual environment. Our exhibit will depict capabilities of our computational approaches and some of our findings from their application. For example, our research has demonstrated that maculas of adult mammals retain the property of synaptic plasticity. Ribbon synapses increase numerically and undergo changes in type and distribution (p<0.0001) in type II hair cells after exposure to microgravity for as few as nine days. The finding of macular synaptic plasticity is pertinent to the clinic, and may help explain some. balance disorders in humans. The software used in our investigations will be demonstrated for those interested in applying it in their own research.

Ross, Muriel D.

Self-motion perception: assessment by real-time computer-generated animations

We report a new procedure for assessing complex self-motion perception. In three experiments, subjects manipulated a 6 degree-of-freedom magnetic-field tracker which controlled the motion of a virtual avatar so that its motion corresponded to the subjects' perceived self-motion. The real-time animation created by this procedure was stored using a virtual video recorder for subsequent analysis. Combined real and illusory self-motion and vestibulo-ocular reflex eye movements were evoked by cross-coupled angular accelerations produced by roll and pitch head movements during passive yaw rotation in a chair. Contrary to previous reports, illusory self-motion did not correspond to expectations based on semicircular canal stimulation. Illusory pitch head-motion directions were as predicted for only 37% of trials; whereas, slow-phase eye movements were in the predicted direction for 98% of the trials. The real-time computer-generated animations procedure permits use of naive, untrained subjects who lack a vocabulary for reporting motion perception and is applicable to basic self-motion perception studies, evaluation of motion simulators, assessment of balance disorders and so on.

Non-NASA Center

Self-motion perception: assessment by computer-generated animations

The goal of this research is more precise description of adaptation to sensory rearrangements, including microgravity, by development of improved procedures for assessing spatial orientation perception. Thirty-six subjects reported perceived self-motion following exposure to complex inertial-visual motion. Twelve subjects were assigned to each of 3 perceptual reporting procedures: (a) animation movie selection, (b) written report selection and (c) verbal report generation. The question addressed was: do reports produced by these procedures differ with respect to complexity and reliability? Following repeated (within-day and across-day) exposures to 4 different "motion profiles," subjects either (a) selected movies presented on a laptop computer, or (b) selected written descriptions from a booklet, or (c) generated self-motion verbal descriptions that corresponded most closely with their motion experience. One "complexity" and 2 reliability "scores" were calculated. Contrary to expectations, reliability and complexity scores were essentially equivalent for the animation movie selection and written report selection procedures. Verbal report generation subjects exhibited less complexity than did subjects in the other conditions and their reports were often ambiguous. The results suggest that, when selecting from carefully written descriptions and following appropriate training, people may be better able to describe their self-motion experience with words than is usually believed.

Non-NASA Center

Robust pupil center detection using a curvature algorithm

Determining the pupil center is fundamental for calculating eye orientation in video-based systems. Existing techniques are error prone and not robust because eyelids, eyelashes, corneal reflections or shadows in many instances occlude the pupil. We have developed a new algorithm which utilizes curvature characteristics of the pupil boundary to eliminate these artifacts. Pupil center is computed based solely on points related to the pupil boundary. For each boundary point, a curvature value is computed. Occlusion of the boundary induces characteristic peaks in the curvature function. Curvature values for normal pupil sizes were determined and a threshold was found which together with heuristics discriminated normal from abnormal curvature. Remaining boundary points were fit with an ellipse using a least squares error criterion. The center of the ellipse is an estimate of the pupil center. This technique is robust and accurately estimates pupil center with less than 40% of the pupil boundary points visible.

Non-NASA Center

Simulation studies of vestibular macular afferent-discharge patterns using a new, quasi-3-D finite volume method

A quasi-three-dimensional finite-volume numerical simulator was developed to study passive voltage spread in vestibular macular afferents. The method, borrowed from computational fluid dynamics, discretizes events transpiring in small volumes over time. The afferent simulated had three calyces with processes. The number of processes and synapses, and direction and timing of synapse activation, were varied. Simultaneous synapse activation resulted in shortest latency, while directional activation (proximal to distal and distal to proximal) yielded most regular discharges. Color-coded visualizations showed that the simulator discretized events and demonstrated that discharge produced a distal spread of voltage from the spike initiator into the ending. The simulations indicate that directional input, morphology, and timing of synapse activation can affect discharge properties, as must also distal spread of voltage from the spike initiator. The finite volume method has generality and can be applied to more complex neurons to explore discrete synaptic effects in four dimensions.

NASA Center ARC

New approaches to virtual environment surgery

This research focused on two main problems: 1) low cost, high fidelity stereoscopic imaging of complex tissues and organs; and 2) virtual cutting of tissue. A further objective was to develop these images and virtual tissue cutting methods for use in a telemedicine project that would connect remote sites using the Next Generation Internet. For goal one we used a CT scan of a human heart, a desktop PC with an OpenGL graphics accelerator card, and LCD stereoscopic glasses. Use of multiresolution meshes ranging from approximately 1,000,000 to 20,000 polygons speeded interactive rendering rates enormously while retaining general topography of the dataset. For goal two, we used a CT scan of an infant skull with premature closure of the right coronal suture, a Silicon Graphics Onyx workstation, a Fakespace Immersive WorkBench and CrystalEyes LCD glasses. The high fidelity mesh of the skull was reduced from one million to 50,000 polygons. The cut path was automatically calculated as the shortest distance along the mesh between a small number of hand selected vertices. The region outlined by the cut path was then separated from the skull and translated/rotated to assume a new position. The results indicate that widespread high fidelity imaging in virtual environment is possible using ordinary PC capabilities if appropriate mesh reduction methods are employed. The software cutting tool is applicable to heart and other organs for surgery planning, for training surgeons in a virtual environment, and for telemedicine purposes.

NASA Discipline Neuroscience

A system for the accurate measurement of pointing responses

We present an accurate, yet relatively inexpensive, system for measuring the direction of pointing responses. This system utilizes off-the-shelf business presentation components in a novel way to help detect and quantify the pointing measurements. The system configuration, measurement features, and procedures to enhance measurement accuracy are described.

NASA Center JSC

A simulator for evaluating methods for the detection of lesion-deficit associations

Although much has been learned about the functional organization of the human brain through lesion-deficit analysis, the variety of statistical and image-processing methods developed for this purpose precludes a closed-form analysis of the statistical power of these systems. Therefore, we developed a lesion-deficit simulator (LDS), which generates artificial subjects, each of which consists of a set of functional deficits, and a brain image with lesions; the deficits and lesions conform to predefined distributions. We used probability distributions to model the number, sizes, and spatial distribution of lesions, to model the structure-function associations, and to model registration error. We used the LDS to evaluate, as examples, the effects of the complexities and strengths of lesion-deficit associations, and of registration error, on the power of lesion-deficit analysis. We measured the numbers of recovered associations from these simulated data, as a function of the number of subjects analyzed, the strengths and number of associations in the statistical model, the number of structures associated with a particular function, and the prior probabilities of structures being abnormal. The number of subjects required to recover the simulated lesion-deficit associations was found to have an inverse relationship to the strength of associations, and to the smallest probability in the structure-function model. The number of structures associated with a particular function (i.e., the complexity of associations) had a much greater effect on the performance of the analysis method than did the total number of associations. We also found that registration error of 5 mm or less reduces the number of associations discovered by approximately 13% compared to perfect registration. The LDS provides a flexible framework for evaluating many aspects of lesion-deficit analysis.

NASA Program Biomedical Research and Countermeasur

A dynamical model for reflex activated head movements in the horizontal plane

We present a controls systems model of horizontal-plane head movements during perturbations of the trunk, which for the first time interfaces a model of the human head with neural feedback controllers representing the vestibulocollic (VCR) and the cervicocollic (CCR) reflexes. This model is homeomorphic such that model structure and parameters are drawn directly from anthropomorphic, biomechanical and physiological studies. Using control theory we analyzed the system model in the time and frequency domains, simulating neck movement responses to input perturbations of the trunk. Without reflex control, the head and neck system produced a second-order underdamped response with a 5.2 dB resonant peak at 2.1 Hz. Adding the CCR component to the system dampened the response by approximately 7%. Adding the VCR component dampened head oscillations by 75%. The VCR also improved low-frequency compensation by increasing the gain and phase lag, creating a phase minimum at 0.1 Hz and a phase peak at 1.1 Hz. Combining all three components (mechanics, VCR and CCR) linearly in the head and neck system reduced the amplitude of the resonant peak to 1.1 dB and increased the resonant frequency to 2.9 Hz. The closed loop results closely fit human data, and explain quantitatively the characteristic phase peak often observed.

NASA Discipline Neuroscience

Effects of characteristics of image quality in an immersive environment

Image quality issues such as field of view (FOV) and resolution are important for evaluating "presence" and simulator sickness (SS) in virtual environments (VEs). This research examined effects on postural stability of varying FOV, image resolution, and scene content in an immersive visual display. Two different scenes (a photograph of a fountain and a simple radial pattern) at two different resolutions were tested using six FOVs (30, 60, 90, 120, 150, and 180 deg.). Both postural stability, recorded by force plates, and subjective difficulty ratings varied as a function of FOV, scene content, and image resolution. Subjects exhibited more balance disturbance and reported more difficulty in maintaining posture in the wide-FOV, high-resolution, and natural scene conditions.

Non-NASA Center

A national center for biocomputation: in search of a patient-specific interactive virtual surgery workbench

This report describes the three-dimensional imaging and virtual environment technologies developed in NASA's Biocomputation Center for scientific purposes that have now led to applications in the field of medicine. A major goal is to develop a virtual environment surgery workbench for planning complex craniofacial and breast reconstructive surgery, and for training surgeons.

NASA Discipline Neuroscience

A model of cerebellar computations for dynamical state estimation

The cerebellum is a neural structure that is essential for agility in vertebrate movements. Its contribution to motor control appears to be due to a fundamental role in dynamical state estimation, which also underlies its role in various non-motor tasks. Single spikes in vestibular sensory neurons carry information about head state. We show how computations for optimal dynamical state estimation may be accomplished when signals are encoded in spikes. This provides a novel way to design dynamical state estimators, and a novel way to interpret the structure and function of the cerebellum.

NASA Discipline Neuroscience