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Research Fields

The following research fields are of interest to MotorLab members:
  • Motor Control
  • Cortical Physiology
  • Muscle Activity
  • Skeletal Biomechanics
  • Visual Motor Interconnection
  • Arm reaching
  • Reach to grasp
  • Control of dexterity
  • Neural Prosthetics
  • Robotics
  • Neural Statistics
  • System Control


  • Perception to Action

    A key question of volitional behavior is how the intention to move is transformed to movement execution. Movement perception is an important component of this process. Normally we perceive our actions accurately­ we know how we really move. In order to dissociate the perception of movement from the actual movement, we have designed a movement illusion. Subjects work in a virtual-reality environment in which they cannot see their own hands. Instead, their 3D hand position is represented by a ball that appears to be floating in space. The subject’s hand is tracked continuously and the task proceeds by placing the ball in an oval-shaped template projected in front of the chest and moving it around the oval five times. During the task, the gain of the cursor is gradually increased so that by the last cycle, the subject’s hand is moving in a circle. However, the subject perceives the movement as an oval. The dichotomy between action and perception is differentially represented. The perceived movement is extracted from ventral premotor cortex while the actual movement is represented in the primary motor cortex. We are now investigating how this disparate information flows from pre- to primary cortex in terms of single-cell transmission and population activity. This will also be examined using multi-dimensional clustering based on cell-cell and cell-behavior correlation.



    Cortical relation to muscle activity

    The primary motor cortex has anatomical connectivity to motoneurons in the spinal cord. This connectivity is complex and determining the causality of any given muscle contraction is a difficult problem. We use a correlation approach to compare single-unit activity recorded in motor cortex to EMG activity during a variety of arm movement tasks. So far, we have found that the correlation between cortical and muscle activity varies in a consistent way within a single task. For instance, during ellipse drawing, a neuron-muscle pair will be correlated for only a small segment of the trajectory. This correspondence appears to be determined by the ratio of a cortical cell’s preferred direction measured in a hand-centered coordinate system and the impulse-contraction-induced movement of the hand by the studied muscle. This non-stationary functional connectivity is being modeled and new data gathered to detail the general features of the corticomuscular system.



    Cortical prosthetics

    3D robot feeding task
    Over the last 10-12 years we have developed technology to transform cortical activity to a signal that controls a robotic arm during movements such as those used for reaching and feeding. Arrays of chronic microelectrodes are implanted permanently in the motor cortical areas of monkeys trained to move their arms in three-dimensional space. Single-unit activity recorded from these electrodes is discriminated and the resulting firing rates are processed with an extraction algorithm that generates a velocity signal of the hand every 30 ms. Initially, the monkeys worked in a virtual reality, reaching for targets located in different parts of the 3D space initially with their hands. In these experiments, the hand is tracked and displayed as a ball-shaped cursor. Once the animal is trained in the task, the electrodes are implanted and the animal moves the cursor only by modulating its cortical activity to produce a velocity signal in the absence of arm movement. Recently we have replaced the virtual reality environment with an anthropomorphic robot arm. The extracted velocity signal is used as an input to an inverse kinematic algorithm that gives joint-angles for each of the four robot motors. This child-sized arm has a fully mobile shoulder and elbow and is outfitted with a simple gripper. Using the principles we developed with the VR task, monkeys have been trained to used the arm with their cortical signals to reach out, grasp and retrieve vegetable pieces in a self-feeding task. This is accomplished with natural movements of the artificial arm. We are in the process of extending this control to the wrist and fingers with a more elaborate effector.