Andrew Schwartz - US grants

DESCRIPTION (provided by applicant): The generation of visually guided movement takes place in a dense network comprised of many interconnected cortical regions. To study this process, we have developed a task based on a motor illusion that dissociates visualization of drawing from the movement used to produce it. Multielectrode recording techniques have been proven and will be used to record single-unit activity from populations of neurons in three nodes of the parietal-frontal portion of the network. A number of advanced analyses will be used to identify groups of cells with activity related to different aspects of this behavioral task. The conventional population vector algorithm will be applied to large populations of cells and a new, more sensitive; particle filter will be used on small groups. Both of these population algorithms wilt be used to extract neural representations of the arm trajectory (drawn shape). With these neural trajectories and the illusion task, it will be possible to determine whether a population is related to the visualized or executed movement, a determination that we have shown (in preliminary data) can be made for at least two of the nodes to be studied. These techniques will allow us to measure timing of the representations relative to the movement and thereby ascertain which groups are acting as feed forward and feedback elements of the control process. This will help build a schematic of the overall process used in visuomotor behavior.

DESCRIPTION (provided by applicant): The goal of this project is to build and demonstrate an anthropomorphic prosthetic arm and hand that is controlled by cortical output. The human arm and hand have approximately 30 degrees- of-freedom (dot- independent joint rotations) and are very complex mechanical structures. Hands are an example of an advanced evolutionary specialization, which along with binocular vision and bipedal locomotion, led to tool use- a major determinant of human brain development and behavior. Yet, little is known about the neural control of the hand during natural behavior. Regarding active prosthetic hands, there has been a paucity of work on robot hand control and only recently has there been an effort to make a truly accurate functioning hand replica. Primate reach-to-grasp behavior is characterized by four components- reach, hand shaping, orientation and the closing of the fingers around the object. Dexterity, characterized by the active generation of force through the fingertips to maintain stable grasp and/or to manipulate an object, can be considered as an additional component of hand behavior. Given our success in developing an anthropomorphic arm prosthesis, we expect to extract the signals necessary to achieve dexterous prosthetic hand control using activity recorded from populations of single neurons. In our present arm-only control scheme, we have successfully extracted the velocity of the arm from the recorded brain activity. To reach our ultimate goal of dexterous control, we will also need to control wrist orientation, hand shape and finger force application. Since each of these control categories is multidimensional, the overall control problem is very difficult. We will use a number of strategies to address this difficult problem. An interdisciplinary team of neurophysiologists, engineers, statisticians, robotocists and psychophysicists with a strong history of collaboration has been assembled to develop the pieces needed for this project. The project will be led by Andrew Schwartz at the University of Pittsburgh where the prosthetic control will take place. Yoky Matsuoka at Carnegie Mellon will build the highly anthropomorphic robots and behavioral manipulanda. Rob Kass, also at Carnegie Mellon, will develop the extraction algorithms relating neural activity to movement. Marco Santello and Stephen Helms-Tillery at Arizona State University will develop the behavioral tasks using a primate model and then record cortical activity as these tasks are performed. Dr. Soechting, at the University of Minnesota, will provide detailed psychophysical data describing the way subjects exert finger forces to manipulate objects. Peter Allen, at Columbia, will develop automated robotic grasp and finger placement algorithms for the brain-controlled prosthetic hand.

DESCRIPTION (provided by applicant): This application addresses broad Challenge Area: Enabling Technologies, Challenge Topic =06-HD-101, Improved Interfaces for Prostheses to Impact Rehabilitation Outcomes. Recent advances in decoding motor intentions and the technology to record populations of neural activity patterns, has created one of the most exciting research areas in neuroscience because this work holds the promise of restoring lost motor output to those who are paralyzed. The success of brain-controlled interfaces depends critically on the user's ability to modulate neural activity in a specific way. To date, subjects are trained with methods that are ad hoc. However, as more sophisticated devices are developed, the need for concurrent improvements in learning techniques is becoming critical. Based on our success with state-of-the-art brain-driven prosthetics, we are proposing a novel, model-driven training approach. With these interfaces, all behavior is driven directly by neural activity and we have an unparalleled opportunity to manipulate task difficulty and monitor performance. This will allow us to model the learning process, use a novel operator-computer shared-control algorithm and define set points to drive learning in a way that minimizes the amount of training needed to master control of complex, brain-controlled prosthetic devices. These methods are likely to generalize to motor rehabilitation of paralyzed individuals. Brain-controlled prosthetics provide a direct link between recorded neural activity and the movement of external devices. Subjects must learn to modulate their neural activity patterns to control these devices successfully. This proposal outlines a novel method to facilitate a learning method leading to the control of complex, brain-controlled interfaces that may be generalized to a wide range of therapeutic rehabilitation.

Facilities and Services. This Core is designed to address the 2 fundamental, but advanced technology needs of neuroscience investigators working with NHPs: 1) specialized mechanical and electronic equipment design and repair; and 2) data collection, management, analysis and storage. A further, critical function of this Core is System Administration, i.e., the maintenance of the computer networks that link computers within and between labs. A key task for this core will be to develop an enlarged database structure to accommodate all types of experimental data, including neurophysiological, anatomical and imaging results. The initial approach to this problem will use database techniques based on open-source PostgreSQL. As a consequence, the database will be compatible with ongoing efforts in the computational neuroscience community (INCF- brain atlases, PANDORA, XooNlps ). Not only will this facilitate sharing programs and data between investigators, but users will have the opportunity to employ a wide range of open source analysis tools on their data. By organizing data in this way, the Core will facilitate communication and interaction with expert consultants who will be able to access the data in a straightforward manner. The Core will have an advanced shop and trained staff who will assist in design, maintenance and repair of specialized mechanical, electronic and computer equipment (e.g., primate chairs, reward-delivery mechanisms, power-conditioning devices, etc.).

Project Summary Over one billion people worldwide are affected by iron overload, iron deficiency, and states of malnutrition that perturb iron homeostasis. The master regulator of systemic iron metabolism is hepcidin, a hormone that is predominately synthesized and released by the liver. The function of hepcidin is to bind to the only mammalian iron exporter, ferroportin, resulting in ubiquitination, internalization, and degradation of ferroportin. Therefore, in the presence of hepcidin, small amounts of iron are mobilized from stores; in the absence of hepcidin, iron is rapidly mobilized into circulation. Mutations that disrupt the hepcidin/ferroportin signaling axis give rise to iron overload and iron deficiency in mammals, demonstrating that hepcidin and ferroportin are essential for the regulation of systemic iron homeostasis. Our lab has shown that the transcription factor, HIF-2?, is a cellular iron sensor and is the master intestinal regulator of apical and basolateral iron transporters. Moreover, HIF-2? is essential for iron absorption following iron deficiency, the hyperabsorption of iron that leads to tissue iron accumulation during iron overload, and for efficient erythropoiesis. However, it is currently unknown whether the systemic iron regulator, hepcidin, and the intestinal iron regulator, HIF-2?, integrate on the molecular level to maintain organism level iron homeostasis. Using a novel genetic mouse model that allows for tamoxifen-inducible deletion of hepatic hepcidin, our data shows that temporal loss of hepcidin increases intestinal HIF-2? activity and the expression of HIF-2?-specific intestinal iron transporters. Ferroportin is the only known target of hepcidin. To further address this crosstalk, we have also begun to investigate the mechanism by which hepcidin initiates the internalization and degradation of ferroportin, which remains unknown. Our preliminary data shows that, once ubiquitinated and internalized, ferroportin is trafficked to the lysosome independent of canonical macroautophagic machinery. Using a cell based immunoprecipitation approach coupled to mass spectrometry, we identified and confirmed that heat shock 70 kDa protein 8 (HSC70) interacts with ferroportin. HSC70 is the rate limiting cargo protein involved in a process of selective lysosomal degradation that is discrete from macroautophagy, known as chaperone-mediated autophagy. This research proposal will test the hypothesis that rapid activation of intestinal HIF-2? by increased systemic iron demand is mediated by the hepcidin/ferroportin degradation axis in the intestine. This hypothesis will be tested through two interconnected specific aims: (1) Determine the requirement for ferroportin-mediated iron flux in intestinal HIF-2? regulation by hepcidin. (2) Characterize the molecular mechanisms of hepcidin-mediated ferroportin degradation. The proposed studies will unveil the mechanisms by which the liver and the intestine communicate to maintain systemic iron homeostasis, which is essential for the understanding and treatment of iron-related disorders.

Project Summary A large body of research has led to statistical models showing how movement velocity is encoded in the motor cortex. These models have been validated by the control of neural prosthetics which restore natural arm and hand movement to paralyzed individuals. However, forces also need to be controlled in harmony with motion when interacting with objects. While many studies have examined force and motion separately, research has rarely focused on how the motor system coordinates both together. The simultaneous variation of force and motion is incorporated in the definition of impedance. Our current neural models do not describe impedance encoding, which poses severe limitations on our understanding of the control of object interaction, an important aspect of human behavior. The proposed research will develop new models of motor cortical impedance encoding during object interaction. Using these new models to decode ongoing impedance signaling, we will substantiate an advanced theory of impedance control used by the motor system to produce accurate object displacement in response to the forces applied by the hand. This research bridges the expertise of Dr. Schwartz in neurophysiology and of Dr. Hogan in robot control. Monkey subjects will perform tasks with real and virtual tools that naturally encourage the use of impedance control. We will record the activity of motor cortical neurons during these tasks and develop new mathematical models to describe the relation between neural activity and force, motion and impedance. Results from electromyography recordings, joint angle measurements and torque calculations, together with the neural models, will be used to better understand how impedance is regulated at the level of muscles and joints and how the impedance of the hand is signaled during object interaction. This work promises to extend our understanding of the neural control principles governing the way we use our arms and hands to interact with our surroundings. These principles can be used to build new theories of the cognitive processes used to predict and effect changes in the world around us. At the same time, elucidation of the neural and mechanical details of forceful interaction will lead to new rehabilitative and neural prosthetic approaches to paralysis.

Project Summary A large body of research has led to statistical models showing how movement velocity is encoded in the motor cortex. However, forces also need to be controlled in harmony with motion when interacting with objects and research has rarely focused on how the motor system coordinates both together. The simultaneous variation of force and motion is incorporated in the definition of impedance. Our current neural models do not describe impedance encoding, which limits our understanding of object interaction, an important aspect of human behavior. The proposed research will develop new models of motor cortical impedance encoding during object interaction. Using these new models to decode ongoing impedance signaling, we will substantiate an advanced theory of impedance control used by the motor system to produce accurate object displacement in response to the forces applied by the hand. This research bridges the expertise of Dr. Schwartz in neurophysiology and of Dr. Hogan in robot control. Monkey subjects will perform tasks with real and virtual tools that naturally encourage the use of impedance control. We will record the activity of motor cortical neurons during these tasks and develop new mathematical models to describe the relation between neural activity and force, motion and impedance. Results from electromyography recordings, joint angle measurements and torque calculations, together with the neural models, will be used to better understand how impedance is regulated at the level of muscles and joints. Contributions of stretch reflexes to impedance will be studied and compared to the predictive impedance signaling decoded from motor cortex. This work promises to extend our understanding of the neural control principles governing the way we use our arms and hands to interact with our surroundings. These principles can be used to build new theories of the cognitive processes used to predict and effect changes in the world around us. At the same time, elucidation of the neural and mechanical details of forceful interaction will lead to new rehabilitative and neural prosthetic approaches to paralysis.