Methods in Computational Neuroscience

3 Credits.

This course introduces techniques to characterize and model real-world neuronal time series data. Students will apply quantitative methods and scientific computing to develop modeling and data-analysis skills. Models will consist of biological spiking neurons, artificial neural systems, and applied statistical models. Applications and methods will focus on rhythmic brain activity - including spectral methods, analysis of coupled rhythms, and mechanistic rhythm modeling - and techniques to characterize and model arhythmic activity in the brain.