This course provides a solid theoretical foundation for the analysis and processing …
This course provides a solid theoretical foundation for the analysis and processing of experimental data, and real-time experimental control methods. Topics covered include spectral analysis, filter design, system identification, and simulation in continuous and discrete-time domains. The emphasis is on practical problems with laboratory exercises.
Systems Neuroscience Laboratory consists of a series of laboratories designed to give …
Systems Neuroscience Laboratory consists of a series of laboratories designed to give students experience with basic techniques for conducting systems neuroscience research. It includes sessions on anatomical, neurophysiological, and data acquisition and analysis techniques, and the ways these techniques are used to study nervous system function. Training is provided in the art of scientific writing with feedback designed to improve writing skills. Assignments include weekly preparation for lab sessions, two major research reports and a series of basic computer programming tutorials (MATLAB®). The class involves the use of experimental animals. Enrollment is limited.
This activity is part of a larger module that introduces students to …
This activity is part of a larger module that introduces students to two different ways to model chemical diffusion in minerals: 1) 1D diffusion in Excel using finite differences and 2) 1D diffusion in MATLAB using the same equations. It is designed to help students apply diffusion equations derived previously in class to understand natural zonation of elements in minerals. The students build the model first in Excel, and then in MATLAB to obtain the timescales of diffusive re-equilibration related to magma storage and transport at KÃÂlauea Volcano, Hawai'i. The major goals are to help students transition from visual platforms (e.g., Excel) to writing computer code (e.g., in MATLAB), implementing for loops for iterative calculations, and thinking about how the geologic parameters (temperature, pressure, fO2) affect the model results.
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