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Participant grasping robotic arm during an experiment.

The human brain is perhaps the most remarkable motor control device in existence.  More than 10 billion neurons comprise the motor system in the human brain. In the face of long sensory delays, high levels of noise from multiple sources, and more than 600 highly interdependent muscles to control, our motor systems can deftly and robustly command motor activation patterns that allow us to talk and sing; sit and stand; run and jump; and throw and catch - often without even paying attention.   Furthermore, with practice we can learn a myriad of seemingly "unnatural" motor skills from surfing and skiing to dribbling a basketball and driving a stick-shift car.

How do we accomplish these things?  How do our brains maintain robust control over the physical movements of our bodies?   How do we learn new motor skills? And how do these control mechanisms go bad in neurologic disease?  Unfortunately, we, as neuroscientists and neuroengineers, do not yet have good answers to these questions. These are the questions that my research lab addresses.

We are broadly interested in how the human brain controls movement, in particular how the brain learns and perfects new motor skills.  Our work focuses on understanding motor learning in general.  However, as a model we study how the brain optimizes the execution of voluntary reaching arm movements. We study both how this process works in healthy individuals and how it goes awry in neurologic disease.

To explore these questions, our lab combines approaches from robotics, computational modeling, functional brain imaging, and behavioral neuroscience.  We use robot arms to produce novel perturbations and force environments that alter the dynamics of movement. Subjects are asked to make arm movements while holding onto the handle of a robot manipulandum that produces these novel force environments, and with practice, their brains learn to adapt to these environments by gradually altering patterns of muscle activation. 

Using such systems, we have shown that in-flight and trial-to-trial compensatory mechanisms have distinct neural bases and are differentially disturbed in certain neurologic diseases. We have shown that the brain’s ability to perform real-time error feedback control can be dramatically disturbed in Huntington’s disease.  Furthermore, our work has revealed that such dysfunction begins to surface years before the disease’s symptoms become apparent, making it an attractive marker for future clinical tests of drugs to stave off the disease.

In addition to revealing markers useful for studying therapeutic efficacy, we study motor learning in patients neurologic disease in order to gain insight into the roles different parts of the brain play in motor learning. We have shown that trial-to-trial error correction (motor adaptation), but not “in flight” error correction (error feedback control), is profoundly disturbed in patients with cerebellar degeneration. The opposite is true in patients with Huntington’s disease. Because neural death is largely confined to the basal ganglia in patients with Huntington’s disease, these results suggest that the basal ganglia and the cerebellum play distinct roles in the control of reaching movement. Such insight may lead to the design of new rehabilitation strategies that reduce the motor disability caused by these diseases.

We also study the fundamental properties of the intact human motor learning system in healthy people. Our recent work has shown that the process of motor adaptation is itself adaptable, indicating that people are not only able to learn to adapt their motor performance but also able to optimize the rate at which this adaptation takes place. The idea that the optimal rate of learning can itself be learned may change the way we think about learning. More practically, this finding may allow for the first time independent identification of the neural correlates of the dynamics of motor adaptation. and the neural correlates of the motor errors that drive this adaptation.


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