Jiping He - US grants

DESCRIPTION (Adapted from the Applicant's Abstract): The investigators have previously shown that the population vector of recorded motor cortical neurons predicts accurately and continuously the arm trajectory during a volitional movement. It is still unclear how this predictive signal relates to the muscle contractions used to move the arm and how it will interact with a perturbation in controlling arm movement. If an unexpected perturbation is applied to an animal s arm after its intended motion has already started, there will be deviations in movement trajectory and reactive changes in muscle activity. One would expect to see corresponding changes in the cortical activity patterns. This change may gradually evolve as the perturbation becomes a fixed feature of the movement. The investigators propose to examine this change in neuronal activities under both novel and adapted conditions toward the perturbation. The long term goal of this project is to understand control strategies used by the sensorimotor system as it interacts with an environment containing unexpected perturbations. The intent is that the information obtained through this investigation will help to develop control systems that utilize cortical signals to control neuromechanical prostheses or functional neuromuscular stimulation systems for humans with brain/spinal cord injury or other neurological damages. The proposed methodologies involve perturbing primate arm motions while simultaneously recording activities from a population of cortical neurons through a chronically implanted fine wire array electrode with up to 96 channels. Rhesus monkeys will be trained to perform a 3D, unrestrained, visually guided center->out reaching task. During each movement the investigators will simultaneously record and correlate arm trajectory, muscle activity and cortical cell activity. They will apply a transient perturbation to the arm by applying a sudden pulling force at the wrist after the initiation of the movement. This perturbation will be applied during every movement toward each of the eight pseudo-randomly presented targets. The effect of the perturbation on arm trajectory will be reduced as the animals learn that the perturbation is a fixed feature of the task. The perturbation will then be removed to examine the after-effects. They will examine the temporal relation among the activities of individual cortical cells and their population vectors, muscle activities, and endpoint movement directions and velocities, both before and after the perturbation. This is achieved by comparing data from four different phases of the experiment: the training phase for control data, the novel phase when the perturbation is first applied, the adaptation phase after the animals have learned the perturbation dynamics and effect, and the extinction phase upon removal of the perturbation. After the monkey adapts to the perturbations, they expect to see a predictive strategy demonstrated in the neuronal and muscle activity before the onset of the perturbation. The 3-D dynamic model of a monkey arm will be refined and used to evaluate strategies adopted by the monkey to minimize the effects of the perturbation.

9987619
Ji-Ping He - Arizona State University
IGERT: Neural and Musculoskeletal Adaptation in Forms and Function

This Integrative Graduate Education and Research Training (IGERT) award supports the establishment of a multidisciplinary graduate training program of education and research on neural and musculoskeletal adaptation in form and function. This theme is examined with integrated approaches from bioengineering, neurophysiology, physical anthropology, exercise sciences, computer and system sciences. The goal of the program is to introduce students with diverse biological and engineering backgrounds to the challenges of deciphering complex phenomena in integrative and computational neuroscience, motor diorders and rehabilitation. The program will foster interdisciplinary education and training in research efforts toward meeting these challenges. Graduate training will expand upon two related areas in which participating faculty have developed research and teaching collaborations: (1) mechanisms underlying neural control of movements, emphasizing hand function and locomotion, and (2) evolutionary morphology of the human hand and bipedality. Three interdisciplinary courses built around core research laboratories (Biomechanics/Anatomy, Neurophysiology/Neuroengineering, and Computation/Visualization) will anchor the program. Research training will be enhanced by access to medical imaging resources and by basic and applied research projects in collaboration with leading medical institutions, biomedical enterprises and evolutionary research resources at the Institute of Human Origins. The program addresses the multidisciplinary needs of graduate education, creates a rich environment for generation of innovative ideas for leading edge research in neuroengineering, evolutionary morphology, motor control, stereo modeling and visualization.

IGERT is an NSF-wide program intended to meet the challenges of educating Ph.D. scientists and engineers with the multidisciplinary backgrounds and the technical, professional, and personal skills needed for the career demands of the future. The program is intended to catalyze a cultural change in graduate education by establishing new, innovative models for graduate education and training in a fertile environment for collaborative research that transcends traditional disciplinary boundaries. In the third year of the program, awards are being made to nineteen institutions for programs that collectively span all areas of science and engineering supported by NSF. The intellectual foci of this specific award reside in the Directorates for Engineering; Biological Sciences; Social, Behavioral, and Economic Sciences; Computer and Information Science and Engineering; and Education and Human Resources.

0221597
Yamaguchi
This award provides support to continue Design Projects' activities begun under NSF award #9631744 at Arizona State University (ASC) in which students designed and built custom projects for people with disabilities. The objectives of the activities are to enhance engineering education, provide students with insight into careers in biomedical engineering, improve the quality of life of people with disabilities, and serve the community. The past 12 years of design projects activity at ASU led to the successful completion of 109 design projects and training of 115 undergraduate students in basic design principles.

The design projects' activity is structured to work successfully within the environment of ASU. Disability Resources for Students (DRS), which provides accommodations for hundreds of mentally and physically disabled students on the ASU campus, will be closely integrated with the student engineers' work. Ten senior design projects are to be pursued each year in conjunction with DRS to develop the prototype devices. Two undergraduate summer interns are to be supported under the program to work part-time at DRS to develop a listing of appropriate projects for the student engineers. A graduate student is to assist in administering the program by helping the undergraduate design teams and fostering new connections between ASU and nearby communities to serve and/or support persons with disabilities. This project is to introduce 10 to 20 new engineers each year to the daily problems faced by the disabled. Additionally, the disabled community will be directly involved as design consultants and thereby increase the participation of an underrepresented group in the activity.

Over the past decade, human motion analysis has become an important research area with critical applications. It is attracting significant research efforts in a number of disciplines, such as computer vision (vision-based motion capture, human computer interface, human identification), robotics (navigation), dance and choreography (automatic dance documentation and dance instruction), music (digital conducting) and bioengineering (rehabilitation and motor behavior). Motion analysis is a complex problem due to the 3D nature of the human body; the infinite possibilities of human movements; variability of movement execution between different people; continuously adaptive learning through feedback from and interactions with the environment; and the inherent multiple levels of movement structure in terms of time, space and energy. This makes it unrealistic for a single discipline to address all aspects. Therefore, progress within each discipline moves at a slow pace.
Intellectual Merit: Arizona State University has founded the Interdisciplinary Research Environment for Motion Analysis (IREMA) initiative that integrates researchers from ten disciplines to create a holistic model for motion analysis research and education. Within IREMA, ground-breaking collaborations have been established through networks of experts, infrastructures and important applications. Using this multi-level, networked research model, the principal investigators (PIs) are able to address many critical issues of real-time motion capture, analysis and feedback. Promising results of social significance are being achieved in areas such as: Rehabilitation Research to Restore Functional Walking Ability for Spinal Cord Injured, Auditory Display Systems for Aiding Interjoint Coordination, Modeling of Human and Robotic Heuristics for Projectile Interception, Movement Based Interactive Arts Environments, Experiential learning environments for children, Extraction and Recognition of Middle and Low Level Features of Movements, Vision-based Motion Capture Using Domain Knowledge.
Using the research infrastructure (RI) grant the PIs will create a multimodal sensing and feedback environment for human motion analysis research and movement-based interactive applications. They will increase their optical motion capture system to 24 cameras, create a high-speed, high resolution 24 video camera array, complete the building of a pressure sensitive floor, acquire a new EMG system and metabolic sensing equipment, acquire required hardware to integrate optical motion capture data with EMG and 2D visual as well as metabolic sensing, increasing processing and storage capacity, creating a mobile motion capture setup, and deploying the necessary hardware and software for interactive real-time feedback. The above sensing equipment would provide high-speed, high quality, synchronous video capture of multiple views, high-precision marker-based motion capture and pressure sensing in the floor as well as on the treadmill, and audio signals. It will enable the PIs to capture human movement in its full essence. The optical motion-capture data and the pressure sensing data will be fused to provide holistic motion capture. The processed, combined data of these systems will be used to train the video based system so that robust and accurate vision-based motion-capture can be acquired using low-cost video cameras. The physiological equipment will be used in the rehabilitation projects.
Broader Impact: During this five-year project, the PIs hope to achieve major advances in motion analysis and core computer science areas: computer vision, human-computer interaction, information and data management, geometric computation, knowledge systems and robotics. These advances will have significant social impact by producing major progress in movement rehabilitation and therapy, K-12 education, security applications (gait/face recognition), and all areas involving movement training (dance, theatre, sports, firefighting, military). Finally, IREMA can serve as a new model for research and interdisciplinary collaboration, which can be adapted to other areas thereby increasing their productivity. This RI grant will establish the necessary infrastructure for paradigm shifts in motion analysis and will facilitate the overall modeling of hybrid research.

This IGERT award at the Arts, Media and Engineering Program at Arizona State University will develop research and training mechanisms for the creation of a new class of media scientists. These scientists will produce new approaches for the integration of computational elements and digital media in the physical human experience. Their work will result in experiential media systems - hybrid physical-digital environments that address significant challenges in key areas of the human condition such as health, education and everyday living.

The knowledge required to create experiential media systems is currently fragmented across engineering, sciences and arts. This IGERT award will train a new generation of hybrid media engineers-scientists-artists who are equipped to transcend this fragmentation. The training will be realized through a large interdisciplinary network combining expertise from twelve contributing disciplines. This network will allow integrated advanced research in sensing, modeling, feedback, experiential construction and learning. The research will result in new knowledge in media systems as well as within each contributing area. It will also result in the development of large-scale applications of societal significance. The graduate training mechanisms are implemented through formally approved concentrations within the graduate degree programs of participating disciplines. They combine discipline specific education in one of the IGERT research areas with interdisciplinary training in media development. The framework of this IGERT allows for methodology found in the sciences to be combined with creativity found in the arts. It will bridge the gap between computation and the physical experience, advance human-centric technologies and produce major advances in education, rehabilitation, communication, and everyday living. IGERT is an NSF-wide program intended to meet the challenges of educating U.S. Ph.D. scientists and engineers with the interdisciplinary background, deep knowledge in a chosen discipline, and the technical, professional, and personal skills needed for the career demands of the future. The program is intended to catalyze a cultural change in graduate education by establishing innovative new models for graduate education and training in a fertile environment for collaborative research that transcends traditional disciplinary boundaries.

Abstract
OISE-0527231
He, Ji-Ping (Arizona State University)
US-China Workshop on Neural Interface Science and Technologies
This award supports the first joint USA-China workshop ever to be held on neural interface technology. The workshop, jointly organized and sponsored by Arizona State University and Huazhong University of Science and Technology (HUST) in Wuhan, Fudan University in Shanghai, and Tsinghua University in Beijing, China, will take place at HUST in China, May 2006. The major objective of the workshop is to discuss the technical advancement and challenges facing researchers in this emerging, fast growing and important field. It is expected to give rise to significant new US-China collaborations that advance the field. This award is aimed to encourage and attract the participation of young scientists and graduate students to begin work on neural technology and its applications. 60-80 people, 30 from the USA and 40 from China, and a few from other countries will attend the workshop.