Neural Systems Engineering & Vision Science

Neural engineering applies quantitative engineering principles to understand and model circuit operations in the nervous system, to determine their relationship to behavior, and to design devices to interface with this circuitry. This emerging field draws from many disciplines, including computational neuroscience, neurobiology, electrophysiology, information theory, electronics, control systems, mathematical modeling, imaging, biomaterials and tissue engineering. Theoretical and computational approaches have become critical tools in the evaluation of the nervous system. Therefore, combined experimental and theoretical approaches are most promising to understand the operation of the brain and to explain behavior by the underlying neuronal mechanisms. Many faculty of the program are currently working on these aspects with the help of a significant number of bioengineering students.

The computational and experimental neuroscience in the program utilizes many approaches, including information-theoretic characterizations of neural coding and representation; nonlinear analysis of neural responses; and models of sensory and motor system. In addition, a variety of neuroscientific methods in animals and humans such as single-unit physiology, EEG, MEG, transcranial magnetic stimulation, and functional MRI are utilized. Modeling of neural systems focuses particularly on biologically relevant and plausible implementations that can be tested experimentally. Using these approaches, our students and faculty have made substantial progress in understanding the organization and function of neural circuits in sensory cortex (vision, audition, somato-sensation, vestibular), the neural mechanisms of motor planning, learning, and memory (e.g. in eye movements, in visually guided reaching, and in vocalization); learning and memory in the cerebral cortex; and development and plasticity in vision, somato-sensation and audition. Other applications in neuroscience abound, all hinge on innovative utilization of computational and quantitative approaches to neurobiology, exemplifying the interdisciplinary nature of our bioengineering training.

Scientific study of the visual system has always been heavily influenced by the perspective of bioengineering. The visual system is uniquely suited to an engineering approach because visual stimuli are easily quantified, and the the anatomy provides ready access to both the transducers (the retina) and the primary processing area (occipital cortex). For these reasons almost all classical and modern bioengineering tools can be applied to the visual system, and new experimental and mathematical techniques are constantly being developed in this area. Thus, this system provides a range of exciting opportunities for the motivated bioengineer: diagnostic instrumentation; minimally invasive surgical methods; engineered molecules to halt or reverse the course of disease; modeling of the cornea or other ocular tissue; studies of sensory coding; quantitative modeling of neuronal function; large-scale computer simulations of sensory networks; development of visual prostheses; modeling and analysis of eye movement control systems and accommodative changes; control-systems analysis of mechanisms of attention and intention; functional imaging of brain activity. Nearly a dozen different laboratories at UCSF and UCB offer chances to participate in cutting-edge research on vision.

The strong affiliation of the neuroscience and vision faculty in bioengineering with two of the strongest and best funded neuroscience and vision programs in the country, at UCSF and UCB, provides outstanding opportunities for incoming students to be involved in top notch, cutting-edge research.

Neural Systems Engineering & Vision Science faculty in the Graduate Group:

Martin Banks, UCB, Core Member
Biomedical Imaging; Neural Systems Analysis; Vision

Brian Barsky, UCB, Affiliate
Biomedical Imaging; Biomedical Instrumentation; BioMEMS, Nanotechnology, Robotics; Vision

Nancy Byl, UCSF, Affiliate
Neural Systems Analysis

Jose Carmena, UCB, Core Member
Neural Systems Analysis

Maurice Cohen, UCSF, Affiliate
Computational Biology, Bioinformatics, Genomics; Biomedical Imaging; Biomedical Instrumentation; Neural Systems Analysis

David R. Copenhagen, UCSF, Affiliate
Neural Systems Analysis; Vision

Mark D'Esposito, UCB, Affiliate
Biomedical Imaging; Neural Systems Analysis

Yang Dan, UCB, Core Member
Neural Systems Analysis; Vision

Robert Edwards, UCSF, Core Member
Neural Systems Analysis

Howard Fields, UCSF, Core Member
Neural Systems Analysis

Loren Frank, UCSF, Affiliate
Biomedical Instrumentation; Neural Systems Analysis

Ralph D. Freeman, UCB, Affiliate
Neural Systems Analysis; Vision

Robert Full, UCB, Core Member
Biomaterials; Biomechanics; BioMEMS, Nanotechnology, Robotics; Neural Systems Analysis

Jack Gallant, UCB, Core Member
Biomedical Imaging; Neural Systems Analysis; Vision

Xiaohua Gong, UCB, Core Member
Tissue Engineering; Vision

Gregory Hjelmstad, UCSF, Affiliate
Neural Systems Analysis

Donna Hudson, UCSF, Core Member
Computational Biology, Bioinformatics, Genomics; Biomedical Imaging; Biomedical Instrumentation; Neural Systems Analysis

Don L. Jewett, UCSF, Affiliate
Computational Biology, Bioinformatics, Genomics; Biomedical Imaging; Biomedical Instrumentation; Neural Systems Analysis; Vision

Edward L. Keller, UCB, Affiliate
Neural Systems Analysis

Stanley Klein, UCB, Core Member
Biomedical Imaging; Neural Systems Analysis; Vision

Robert Knight, UCB, Affiliate
Neural Systems Analysis

Patricia Leake, UCSF, Core Member
Biomaterials; Biomechanics; Drug Delivery; Neural Systems Analysis; Tissue Engineering

Luke Lee, UCB, Core Member
Biomaterials; Biomedical Imaging; Biomedical Instrumentation; BioMEMS, Nanotechnology, Robotics; Neural Systems Analysis; Vision

Steven L. Lehman, UCB, Affiliate
Biomechanics; Neural Systems Analysis

Dennis Levi, UCB, Affiliate
Vision

Edwin R. Lewis, UCB, Core Member
Biomedical Instrumentation; Neural Systems Analysis

Stephen Lisberger, UCSF, Affiliate
Neural Systems Analysis; Vision

Michael M. Merzenich, UCSF, Affiliate
Neural Systems Analysis; Vision

Pratik Mukherjee, UCSF, Core Member
Biomedical Imaging; Neural Systems Analysis

Srikantan Nagarajan, UCSF, Core Member
Biomedical Imaging; Neural Systems Analysis

Austin Roorda, UCB, Core Member
Biomedical Imaging; Biomedical Instrumentation; Vision

Boris Rubinsky, UCB, Affiliate
Computational Biology, Bioinformatics, Genomics; Biomedical Imaging; Biomedical Instrumentation; BioMEMS, Nanotechnology, Robotics; Drug Delivery; Neural Systems Analysis; Tissue Engineering

Philip Sabes, UCSF, Core Member
Biomechanics; Neural Systems Analysis; Vision

Julie Schnapf, UCSF, Affiliate
Neural Systems Analysis; Vision

Clifton Schor, UCB, Affiliate
Neural Systems Analysis; Vision

Christoph E. Schreiner, UCSF, Core Member
Neural Systems Analysis

Michael Silver, UCB, Affiliate
Biomedical Imaging; Neural Systems Analysis; Vision

David Sretavan, UCSF, Core Member
Biomedical Instrumentation; BioMEMS, Nanotechnology, Robotics; Neural Systems Analysis; Tissue Engineering; Vision

Michael Stryker, UCSF, Affiliate
Computational Biology, Bioinformatics, Genomics; Biomedical Imaging; Neural Systems Analysis; Vision

Kimberly Topp, UCSF, Affiliate
Biomechanics; Neural Systems Analysis

Frank Werblin, UCB, Affiliate
Vision