MA665: Introduction to Modeling and Data Analysis in Neuroscience

Course Webpage (Fall 2012)

Course Instructor: Mark Kramer (email, 3-4591)
Course Hours: 12:30-2 PM / TTh / MCS B23
Office Hours: 2:00-3:30 PM / TTh, or by appointment
Textbook: MATLAB for Neuroscientists
Handouts . . .

Course goals

In this course we will focus on the quantification and modeling of voltage data generated by the brain at a variety of spatial scales --- from single neurons to the EEG. The main goals of this course are: (1) To introduce mathematical concepts encountered in neuroscience research and more advanced neuroscience graduate courses. (2) To teach basic programming skills in MATLAB. (3) To think about neuroscience in a quantitative way.

Course Flyer



The plan - it's still flexible . . .

Labs, Reading, Homework

Week 1
Lecture: Introduction + two views of neuroscience + field trip.

Lab: Introduction to MATLAB, code.
Reading: MATLAB for Neuroscientists, Ch 2

Other introductory MATLAB resources:

Week 2
Lecture: Observations of spiking neurons and their quantification
Lab: code, d1.mat, d2.mat, d3.mat
Optional Reading:

Week 3
Lecture: Statistical models of spiking data
Lab: The Poisson model, code.
Optional Reading:

Week 4
Lecture: Simple biophysical models of spiking data
Lab: The integrate and fire model neuron and the leaky integrate and fire model neuron, code.
Here's the my_IF_model.m we wrote in lab.
Optional Reading:

Week 5
Lecture: More complicated biophysical models of spiking data
Lab: The Hodgkin Huxley neuron model code and HH0.m.
Optional Reading:

Week 6
Lecture: An introduction to Fourier series.
Lab: Analysis of rhythmic data. Lecture slides as pdf.
Download the lecture data set 6_data.mat and the M-file that includes MATLAB code to analyze these data.
This week's Challenge Problems.
Other data sets for challenges: lfp1.mat, lfp2.mat.
Optional Reading:


Week 7
Lecture: Networks in neuroscience
Lab: Analyzing and constructing networks code and make_small_world.m.
Lab figures: net1 and net2.
Optional Reading: