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| BME 665 / 565 Students - Spring 2004 | Class home page | ||
| Basic background for the course | |||
| 30% | I have taken a basic cellular neurophysiology course recently | ||
| 90% | I have taken linear algebra, calculus, and ordinary differential equations | ||
| 100% | I have taken probability and statistics | ||
| Interest in the course | |||
| 70% | I am interested in doing biophysical modeling of neurons | ||
| 90% | I am interested in information coding in the brain | ||
| 70% | I want a better understanding of the biological principles underlying neural network modeling | ||
| 80% | I am generally interested in modeling biological systems | ||
| 100% | I want to better understand what role computational methods can play in neuroscience | ||
| 60% | I want to be able to read the computational neuroscience literature more effectively | ||
| 30% | It is required for my degree | ||
| Familiarity with course material | |||
| 5 - Expert 4 - Comfortable with the concept 3 - Can define it 2 - Have heard of it 1 - Say what? | |||
| 2.3 | Hodgkin-Huxley model | ||
| 3.3 | Action potentials | ||
| 2.9 | Calcium, potassium and sodium channels | ||
| 2.3 | PSP's, PSC's | ||
| 2.3 | Integrate-and-fire neurons, spike response model | ||
| 2.2 | Stochastic firing and rate models | ||
| 1.6 | Neuronal oscillations, central pattern generators | ||
| 2.5 | Hebbian learning | ||
| 2.0 | Orientation selectivity, ocular dominance | ||
| 2.4 | Temporal coding | ||
| 2.8 | Synaptic plasticity | ||
| 1.8 | Patch clamping, intra- and extra-cellular recording | ||
| 2.0 | Optical imaging | ||
| 3.6 | MATLAB programming | ||
| 3.1 | Bayes' theorem | ||
| 3.2 | Ordinary differential equations | ||
| 3.5 | Fourier transforms | ||