TEACHING

Computational Neuroscience Summer School at the University of Ottawa, Canada

http://www.neurodynamic.uottawa.ca/summer.html

Neural Systems and Behavior course at the Marine Biological Laboratory
(Woodshole, MA, USA).

http://www.mbl.edu/nsb/

Physiology 314: Integrative Neuroscience

An in-depth presentation of experimental results and hypotheses underlying our current understanding of how single neurons and ensembles of neurons encode sensory information, generate movement, and control cognitive functions such as emotion, learning, and memory, during voluntary behaviors.

Physiology 425: Analyzing Physiological Systems

With the invention of new technologies, biological research is rapidly becoming a quantitative science.  Two areas stand out: systems biology, the quantitative physiology of single cells, and computational neuroscience, connecting the brain’s biological machinery to information processing.  This course provides an introduction to quantitative physiology, a mode of thinking and a set of tools that allows accurate prediction of the behavior of biological systems.  Examples will range from oscillating genetic networks to understanding higher brain function.  Throughout, “hands on” modeling and data analysis through computer exercises will be emphasized.

Neurology 531-603: Introduction to Computational Neuroscience

This course will present an introduction to computational neuroscience.  Levels of analysis will span the range from dendrites and synapses to networks of neurons, with a particular focus on single-neuron models of sensory processing and motor control.  Students will learn how to model the relationship between sensory stimuli and neuron activity, and between neuronal activity and behavior.  These models will be introduced by the instructor in each lecture, and students will simulate the models during in-class programming labs.  Basic mathematical concepts will be presented during tutorial sessions, and more advanced concepts will be covered during lectures.