Philip Sabes, PhD
|School||UCSF School of Medicine|
|Address||675 Nelson Rising Lane|
San Francisco CA 94158
The ability to flexibly and adaptively integrate information from a variety of sources is a fundamental feature of brain function, from higher cognition to sensory and motor processing. Even a simple behavior such as reaching to a target relies on the integration of multimodal sensory signals and, moreover, exhibits rapid adaptation in response to changes in these signals. Our research uses reaching and similar goal-directed movements as a model system for understanding these abilities and their underlying neural mechanisms and, ultimately, for harnessing these abilities to repair brain dysfunction.
Our lab employs a combination of complementary approaches:
Cortical Physiology. Cutting-edge physiological techniques allow us to study and manipulate large-scale activity in sensorimotor cortex during behavior. We record from multiple 96-channel electrode cortical arrays, allowing us to study neural activity at the level of the population responses and across cortical circuits. We are also developing techniques to control the activity of cortical populations, both with patterned electrical stimulation across many electrodes with and patterned light stimulation in tissue expressing light-sensitive ion channels ("optogenetics").
Computational and Theoretical Modeling. We use computational and theoretical models to link our understanding of brain and behavior. Two levels of modeling are used. We develop predictive models of behavior, typically cast in statistical or control-theoretical terms, in order to gain intuition about why the behavior is the way it is. We develop network models that approximation our behavioral models in order to gain intuition and about candidate neural mechanisms. These models generate testable hypotheses about the dynamics of cortical networks, and we use these models to design of our physiological experiments.
Human Psychophysics and Physiology. With human psychophysics (or quantitative behavioral studies), we identify behavioral phenomena that illustrate important features of sensorimotor processing. The goal of this component our work is to find phenomena that are experimentally tractable for human and animals and are amenable to theoretical/computational modeling. We also have access to a variety of human neurophysiological tools, including functional magnetic resonance imaging (fMRI) and electro-corticography (ECoG).
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