Neural Engineers Convene in San Diego for IEEE Neural Engineering Conference
by James Cavuoto, editor
Several hundred neural engineers, clinicians, and researchers attended the 2013 6th International IEEE EMBS Conference on Neural Engineering, held in San Diego, CA earlier this month. Conference chairs were Bin He from the University of Minnesota and Metin Akay from the University of Houston.
In a symposium devoted to brain-machine interfaces, Tim Denison from Medtronic gave a talk on translational research tools for investigating neurological diseases. He outlined Medtronic’s background in developing flexible-closed loop architecture neural systems, such as optimizing the delivery of spinal cord stimulation based on the user’s posture.
Denison urged attendees to balance the excitement of science with the practicality of meeting unmet medical needs and healthcare economics. He suggested that researchers could embed a scientific payload within an existing commercial stimulation system. He also discussed ways that a BCI using visual signals could exploit communications theory. For example, a researcher could use a time-division multiple access strategy by introducing multiple visual targets in different time slots. Alternatively, each target could be assigned a frequency or its own code.
Also in that session, Paul Sajda from Columbia University spoke of an “opportunistic” BCI that exploits naturally evoked signals. In an immersive environment, Sajda’s team takes advantage of EEG, saccadic, and pupillary data from subjects as they move through a 3D virtual city.
In a session on neural prostheses, Ted Berger from USC gave attendees an update on his team’s work on a hippocampal prosthesis. After testing his model in 23 animals, Berger teamed up with a group from Wake Forest University to begin human studies in 10 patients.
Nigel Lovell from the University of New South Wales gave an update on recent Australian efforts to construct a retinal prosthesis. His team has designed a 98-channel electrode array implanted in the suprachoroidal space. The device includes an ocular implant which attaches to the outside of the globe of the eye and a transcutaneous wireless link. Lovell stressed a design philosophy that favors long-term stability over proximity to the retina. The NSW team uses a pseudo monopolar waveform and current steering techniques to increase localization of multiple perceived phosphenes while reducing activation thresholds.
Gregoire Courtine from EPFL in Switzerland described his team’s efforts to restore function after spinal cord injury. The EPFL team uses a combination of intrathecal drug delivery, spinal electrode arrays, and closed-loop control systems to reactivate postural and locomotor circuits in the spinal cord. Combining the electrochemical prosthesis with robot-assisted training allowed the team to restore a foot trajectory in paralyzed animals that could be fine-tuned with stimulation frequency. Courtine believes that this neural remodeling process demonstrates plasticity not only at the site of the spinal cord lesion, but also at the level of the brainstem and motor cortex.
Continuing this theme of learning in the spinal cord, Reggie Edgerton from UCLA argued that there was no clear distinction between autonomic, automatic, or voluntary control of movement. He said there needs to be a reengagement of spinal circuitry after a spinal cord injury and stressed that stimulation in conjunction with sensory input can significantly enhance motor performance.
Warren Grill from Duke University described his group’s work recording evoked potentials during DBS. Grill said that the evoked compound action potential could act as a potential feedback signal that can be used to adjust stimulation parameters such as voltage, frequency, or pulsewidth. The Duke team recorded ECAPs from the thalamus of anesthetized cats and later participated in trials with human DBS patients during IPG replacement surgery. He said the effect is variable from person to person.
Todd Kuiken from the Rehabilitation Institute of Chicago gave an update on the use of targeted muscle reinnervation to control a powered motor prosthesis. Kuiken’s team is developing a bidirectional neural interface that not only exploits residual motor nerves in amputees but also the transfer of residual sensory nerves that can be remapped to the skin of the chest or arm. This targeted sensory reinnervation technique can potentially restore sensation of touch, pressure, and thermal stimuli.
Justin Sanchez, program manager at the Defense Science Office, gave attendees an update on DARPA’s new Systems-Based Neurotechnology for Emerging Therapies (SUBNETS) program. Though some attendees balked at the aggressive schedule—proposals are due on December 17 of this year—Sanchez encouraged research teams to recognize the unique opportunity that the $70 million program presents and to act expeditiously.
SUBNETS seeks to create new interventions based on new insights that can be gained from the intersection of neuroscience, neurotechnology, and clinical therapy. DARPA is specifically interested in evaluating the underlying systems which contribute to post-traumatic stress disorder, major depression, borderline personality disorder, and general anxiety disorder. DARPA also seeks to evaluate the representation in the central nervous system of traumatic brain injury, substance abuse/addiction, and fibromyalgia/chronic pain.
Sanchez also introduced the Restoring Active Memory (RAM) program, which will seek to restore active memory in individuals with memory disorders and develop a computational model of neurological mechanisms. DARPA seeks new methods for analysis and decoding of neural signals in order to understand how neural stimulation could be applied to facilitate recovery of memory encoding following brain injury. Ultimately, the agency hopes to develop a prototype implantable neural device that enables recovery of memory in a human clinical population. The program also hopes to develop quantitative models of complex, hierarchical memories and explore the neurobiological and behavioral distinctions using the implantable device vs. natural learning and training.