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Short Courses

An Overview of Statistical Methods for Neuroscience
Emery Brown and Rob Kass
Thursday, May 11, 9-12 am

We will provide a brief summary of the most important foundations for statistical methodology in neuroscience. Examples will be used throughout, and mathematical details will be discussed only where essential.
Part I: Propagation of Error: Maximum Likelihood, Bayesian Analysis, and the Bootstrap
Part II: Essential Ideas in Time Series, Spectral Analysis, and State-Space Modeling
An Overview of Neurophysiology, for Quantitative Analysts
Justin Crowley, Andrew Schwartz, and Bita Moghaddam
Thursday, May 11, 1:30-4:30 pm

These three lectures will each provide a brief introduction to a particular brain system, and will indicate very briefly some of the open problems, and how these might involve challenges in data analysis methodology.

Part I: The Visual System
(Justin Crowley)
Part II: The Motor System (Andrew Schwartz)
Part III: The Frontal Lobe and Cortical-Subcortical Interactions (Bita Moghaddam)