Research

Neural Plasticity & Neuro-Repair

Nicholas Hatsopoulos PhD (Department of Organismal Biology and Anatomy) studies the neural basis of motor control and learning. He is investigating what features of motor behavior are encoded and how this information is represented in the collective activity of neuronal ensembles in the motor cortex. He is also interested in what way these representations change as motor learning occurs. Specifically, he is trying to understand how neuronal ensembles in the cortex act together to control, coordinate, and learn complex movements of the arm and hand. Dr. Hatsopoulos’ research studies, the electrical discharge of many motor cortical neurons is recorded using multi-electrode arrays while animals perform various motor behaviors with the goal of asking four fundamental questions:

  • What motor features are encoded in motor cortical ensembles;
  • How they are encoded in motor cortical ensembles;
  • Whether these feature codes exhibit plasticity as a consequence of motor learning; and
  • What is the nature of the transformations that occur between different motor cortical areas.

Current results suggest that specific spatio-temporal patterns of activity across multiple neurons encode aspects of movement that are not revealed from single electrode recording.

Beyond the basic scientific questions the applied goals of this research are to develop a brain-machine interface by which a monkey or human can control an external device in real-time by activating the appropriate neuronal signals. This research has lead to a FDA IDE clinical trial conducted by a company called Cyberkinetics Neurotechnology Systems, to determine whether patients with spinal cord injuries and ALS can use motor cortical signals to control a computer cursor. Implants have recently been made in two tetraplegic patients using this same array technolog, enabling recording of multiple signals from neurons in the motor cortex of these patients. It has been shown that they can voluntarily activate those neurons when imagining moving their paralyzed arms, and by feeding these signals through various decoding algorithms they can voluntarily guide the movement of a cursor in a goal-directed fashion.