Teaching: Resources
Computational Neuroscience course resources: This zip file includes homework, laboratory exercises, lecture slides, and the syllabus from my algebra-based Computational Neuroscience course. It includes everything except for the data file for Lab 10 (linked separately to make the main download faster). Please contact me (cgfink [at] owu.edu) if you are an instructor and would like solutions to the homework, lab, and exams.

Auto-associative memory interactive simulation: This is an "applet" for exploring computational models of memory formation, as inspired by Donald Hebb and John Hopfield. It is based on exercises from Tom Anastasio's Tutorial on Neural Systems Modeling. Simply download the zip file, unzip it, and open "memory_app.exe" to get started. Note that this file will only run on Windows machines. However, the Python source code is included in the download as well, so Linux and Mac users with Python can also run the program. Instructors are encouraged to use this in-class exercise to accompany the app. If you are an instructor interested in solutions to this exercise, contact me at cgfink [at] owu.edu.

Introduction to MATLAB: MATLAB (which stands for MATrix LABoratory) is a high-level programming language that is very useful for data analysis. This is a very brief introduction to getting started with MATLAB.

Introduction to filtering app: This MATLAB-based GUI enables students to apply basic filters to three different signals (data related to sunspots, the stock market, and brain waves). Students can also import their own time series and apply either low-pass, band-pass, or high-pass filters. This document walks students through some very basic filtering exercises.

Introduction to the NEURON simulator: This document walks you through running simple simulations in NEURON. You can either set up your own simulation or download and run previously written code from ModelDB. This short introduction is adapted from material presented at the NEURON Summer Course.