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MAR 11, 2020 12:00 PM PDT

PANEL: Thought to action: developing brain machine interfaces to assist individuals with paralysis

Presented at: Neuroscience 2020
C.E. Credits: P.A.C.E. CE Florida CE
Speakers
  • Member of Professional Staff, Executive Director, T&C Brain-Machine Interface Center, Division of Biology and Biological Engineering, California Institute of Technology
    Biography
      For the last 15 years, Tyson Aflalo has studied how the brain controls movements with applications to neural prosthetics. Tyson received his PhD from Princeton University in 2012, studying how natural behaviors are coded in the primate brain. After his PhD, Tyson moved to the California Institute of Technology as a postdoctoral scholar in the lab of Richard Andersen, where he helped initiate the first human clinical trial to directly decode high-level goals from neural implants in tetraplegic individuals. Currently, Tyson is Executive Director of the T&C Chen Brain Machine Interface Center at the California Institute of Technology. In this role, he helps to oversee a clinical study comparing how populations of neurons encode intentions in posterior parietal and primary motor cortices.
    • James G. Boswell Professor of Neuroscience,T&C Chen Brain-Machine Interface Center Leadership Chair Director, T&C Brain-Machine Interface Center Division of Biology and Biological Engineering
      Biography
        Richard Andersen obtained his Ph.D. from the University of California, San Francisco and completed a postdoctoral fellowship at the Johns Hopkins Medical School. He was a faculty member of the Salk Institute and MIT before coming to Caltech. Andersen discovered gain-fields, the method the brain uses to transform signals between spatial representations. He also discovered neural signals of intention, proving that they are not sensory in nature but rather reflect the planning of the subject. He has applied this discovery of intention coding to advance research in brain-machine interfaces, showing that paralyzed patients' intentions can be decoded from brain activity to control assistive devices such as computers and robotic limbs. Andersen is a member of the National Academy of Sciences, the National Academy of Medicine, and the American Academy of Arts and Sciences.
      • Member of Professional Staff, Director of Engineering, T&C Brain-Machine Interface Center, Division of Biology and Biological Engineering, California Institute of Technology
        Biography
          Spencer Kellis received the B.S. degree in electrical engineering from Brigham Young University in 2006, and the M.S. and Ph.D. degrees, both in electrical engineering, from the University of Utah in 2009 and 2012 respectively. In 2012 he joined Prof. Richard Andersen's lab at the California Institute of Technology as a postdoctoral scholar where he helped to build the hardware, software, and regulatory requirements for human clinical trials of brain-machine interfaces in persons with tetraplegia. In 2016, he was appointed a Member of the Professional Staff at the California Institute of Technology, and in 2017 was appointed Research Assistant Professor of Neurological Surgery, Keck School of Medicine, University of Southern California. His research interests include neural signal processing, neural stimulation for sensory and therapeutic applications, and shared biological-machine intelligent systems.
        • Professor of Neurosurgery, Director of the USC Neurorestoration Center, Keck School of Medicine, University of Southern California, Chair of Neurosurgery and Orthopedics
          Biography
            Charles Liu completed his undergraduate education in chemical engineering at the University of Michigan, Ann Arbor and his PhD in chemical/bioengineering at Rice University. He then attended medical school at Yale University before completing his neurosurgical training at the University of Southern California affiliated hospitals. Dr. Liu is engaged in a broad spectrum of efforts that brings together the fields of engineering and clinical medicine to develop systems-level solutions to neurological disabilities. He is currently a professor of neurosurgery, neurology, urology, biomedical engineering, and biokinesiology and physical therapy at the University of Southern California, where he also serves as the Director of the USC Neurorestoration Center. He is also the Chair of Neurosurgery and Orthopedics at Rancho Los Amigos National Rehabilitation Center and serves as Chief Innovation Officer.

          Abstract

          Brain machine interfaces (BMIs) aim to help patients with paralysis to use their recorded brain activity to control assistive devices.  BMI research requires the collaboration of neuroscientists, engineers, computational neuroscientists, and clinicians.  Generally motor cortex has been used as a source of control signals.  With our U01 BRAIN Initiative grant and other NIH grant support, we have examined a different area of cortex for BMI control, the posterior parietal cortex (PPC).  The PPC forms the intentions and plans to make movements.  Richard Andersen will discuss the finding that PPC represents many intended movement variables over essentially the entire body.  Cognitive variables include goals, cognitive strategies, action observation, and action semantics.  So many variables can be decoded from just a few hundred PPC neurons because they are represented in a clever, partially mixed structure.  Spencer Kellis will describe how intracortical microstimulation of primary somatosensory cortex produces cutaneous and proprioceptive sensations in the limb of a tetraplegic subject.  Being able to provide this naturalistic feedback is important for dexterous robotic control.  Tyson Aflalo will discuss a study in which microelectrode arrays are implanted in both PPC and primary motor cortex.  This study establishes different motor functions for these two areas that can complement brain control and maintain their basic functional differences even after many months of BMI sessions.  Charles Liu will describe the clinical aspects that guide every step of human BMI studies from recruitment, to surgery, to long term care of the participants.  He will highlight the importance of surgical techniques and the support of rehabilitation hospitals.

          Learning Objectives:

          1. Explain how mixed selectivity allows the posterior parietal cortex to represent so many action variables with a small number of neurons

          2. Identify why restoring somatosensory feedback is important for brain-machine interfaces that control robotic hands.

          3. Account for why the lack of functional restructuring of the posterior parietal cortex and motor cortex with brain-machine interface usage makes it important to select the right cortical areas for recording brain signals.

          4. Enumerate ways that human brain-machine interface research benefits from having multidisciplinary research teams.


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