Research topics: We want to understand how the brain controls movement and recovers from injury.
Techniques: We primarily use multielectrode arrays in animal models and human clinical studies.
Seeking undergrads for: Summer
Required skills: Programming experience
1) A realtime computational platform for systems neuroscience and brain-machine interfaces
This project will continue development on LiCoRICE (Linux comodular realtime interactive computation engine) which was developed as REU projects over the past five summers. LiCoRICE is a flexible platform that implements model-based design in realtime with Python, and is used as the central data processing and collection tool for the neuroelectrophysiology and brain-machine interface work in the group. Student will continue to develop platform, addressing outstanding bugs, and adding features based on need and interest. More information about platform is available at http://licorice.stanford.edu
No required courses. These are useful: programming (CS106A/B), systems
(CS107 , CS110), algorithms (CS161), embedded systems (EE 107/109),
signal processing (EE102A/102B/264), networking (CS144), numerical
methods (CME103/200/108), and compilers (CS143).
Student must be fearless and willing to climb a steep learning curve.
This platform is challenging and will stretch the knowledge learned from
coursework into new territory. Student must also be willing to work
independently to solve problems.
2) Neuroelectrophysiology laboratory development using a Linux-based realtime computational platform
This project will utilize LiCoRICE (Linux comodular realtime interactive computation engine - http://licorice.stanford.edu ) to develop several invertebrate neuroelectrophysiology and closed-loop systems neuroscience laboratory experiments which will be deployed as part of the first offering of a lab course the following year (BIOE 248). The projects span single and dual electrode neuroelectrophysiology recording with crickets, roaches, earthworms; and also human-controlled closed-loop
neural decoding experiments. Student will develop and test labs in LiCoRICE, spanning experimental setup, data acquisition, and analysis.
No required courses, but familiarity with programming is helpful
(CS106A), circuits (EE101A/101B), signal processing (EE102A/102B), and
numerical computing (Python, CME 193/108) is helpful.
Student must be independent, creative, and willing to persevere in the
face of failure. Experiments fail often before succeeding, and student
must be both attentive to detail and comfortable with uncertainty.