Syllabus

Topics covered fall into one of four categories:

• Biophysical mechanisms (from textbook)

• Paradigms of system identification

• Minimal computer skills needed for projects (MATLAB, etc).

• Programming neural models with the high level language NEURON. (Using tutorials available on Web).

Individual topics (in the order planned, follow):

• NIA2 (Neurons in Action, 2) Introductory Tutorial

• NIA2 Membrane Tutorial

• NIA2 Equilibrium Potential Tutorial

• NIA2 Sodium Action Potential Tutorial

• NIA2 Voltage Clamping a Patch Tutorial

• Differential equations and basic concepts of numerical analysis of differential equations. Discretizing a continuous model (RC-circuit) with Euler's method. A Matlab primer. (Possibly more than one class)

• Identifying an RC-circuit with time domain methods and an injected current. Two cell network of RC circuits with linear graded synapse. Phase plane analysis. Parameter estimation when model structure is wrong. (Possibly more than one class)

• Multiple compartment modeling with active conductance. The model structures we will use for projects.

• Maximum likelihood estimation (several classes)

• Bayesian filtering and using my fitting software: PROJECT PROPOSAL ASSIGNED.

• NIA2 The Passive Axon Tutorial

• Model Selection with the Akaike Information Criterion (less than one class, 20 minutes maximum)

• NIA2 The Unmyelinated Axon: PROJECT PROPOSALS DUE

• NIA2 Sodium and Potassium Channel Kinetics Tutorial

• NIA2 Axon Diameter Change

• NIA2 Nonuniform Channel Densities

• NEURON Programming (Several classes -- topics to be decided)

• More NIA2 Tutorials (Several classes -- topics to be decided)