Amazon logo When you click the Amazon logo to the left of any citation and purchase the book (or other media) from, MIT OpenCourseWare will receive up to 10% of this purchase and any other purchases you make during that visit. This will not increase the cost of your purchase. Links provided are to the US Amazon site, but you can also support OCW through Amazon sites in other regions. Learn more.

This page includes the course calendar.

Course Format

The course employs twice-weekly lectures and weekly laboratory and discussion sessions.

Laboratory includes fMRI data acquisition sessions and data analysis workshops. Assignments include reading of both textbook chapters and primary literature as well as fMRI data analysis in the laboratory. For each of the Discussion sections with an assigned article to read, students should post two questions to the class discussion forum at least 24 hours in advance.


Probability, linear algebra, differential equations, and introductory or college-level subjects in neurobiology, physiology, and physics are required.

Required Textbook

Amazon logo Huettel, S. A., A. W. Song, and G. McCarthy. Functional Magnetic Resonance Imaging. 1st edition. Sunderland, MA: Sinauer Associates, Inc., 2004. ISBN: 9780878932887.

Note: The 2nd edition of this book was published after the Fall 2008 term, and Dr. Gollub recommends its use. Amazon logo Huettel, S. A., A. W. Song, and G. McCarthy. Functional Magnetic Resonance Imaging. 2nd ed. Sunderland, MA: Sinauer Associates, Inc., 2009. ISBN: 9780878932863.

This book will be supplemented by readings in the research literature and other books.

Grading Policy

Problem sets 20%
Lab reports 30%
Midterm exam 20%
Final exam 30%

Problem sets are due one week after end of module. Lab reports are due one week after the analysis lab session.

Grades will be reduced by 10% per day until 1 week after due date, after which no assignments will be accepted.


Part 1. Overview

Introduction to the course (Gollub)

Introduction to fMRI (Rosen)

Part 2. Functional neural systems
2 Neural systems I (Dickerson)

MRI safety training

Lab 1: introduction to fMRI data and analysis (Bolar)

Problem set 1 out
3 Neural systems II (Dickerson) Human subject safety issues (Gollub)
4 Neural systems III (Dickerson) Lab 2: fMRI acquisition (Whitfield-Gabrieli, Triantafyllou) Lab 1 due
5 Cerebrovascular anatomy and neural regulation of CNS blood flow (Dickerson) The hemo-neural hypothesis (Moore)
Part 3. Physics of image acquisition
6 MRI physics I (Wald) Bottom-Up dependent gating of frontal signals in early visual cortex (Vanduffel) Problem set 1 due
7 MRI physics II (Wald) Lab 3: the life cycle of medical imaging data (Pujol) Lab 2 due
8 MRI physics III (Wald) Response monitoring in Autism Spectrum Disorders (ASD) (Manaoch) Problem set 2 out
Part 4. Imaging physiology
9 Imaging physiology I: brain at the baseline (Bolar) Lab 4a: MRI physics, part I (Trinatafyllou) Lab 3 due
10 Imaging physiology II: brain activation (Bolar) Visual topography of human intraparietal sulcus (Sommers)
11 Imaging physiology III: BOLD imaging (Bolar) Brain correlates of autonomic modulation (Napadow)

Problem set 2 due

Problem set 3 out

12 Imaging physiology IV: BOLD(cont.) and non-BOLD techniques (Bolar) Lab 5: diffusion weighted imaging workshop (Pujol) Lab 4a due

Quantitative perfusion and diffusion imaging biomarkers (Sorensen)

Physics of diffusion weighted imaging (Yendiki)

No discussion due to extra lecture content
Part 5. Experimental design
14 General principles of experimental design (Savoy) Lab 4b: MRI physics, part II (Triantafyllou) Lab 5 due
15 Phsychological state variables in imaging (Gabrieli) Primer on matrix algebra for fMRI data (Greve) Problem set 3 due
16 Overview of statistical analysis, preprocessing (Greve) Lab 6a: statistical analysis of fMRI data, part I (Yendiki) Lab 4b due
Mid-Term exam
Part 6. Statistical analysis
17 Stats 2: level 1 (Greve) Event-related single-shot volumetric functional magnetic resonance inverse imaging of visual processing (Polimeni) Problem set 4 out
18 Stats 3: level 1 (cont.) (Greve) Lab 6b: statistical analysis of fMRI data, part II (Yendiki) Lab 6a due
19 Stats 4: level 2 (Greve) How humans make inferences about self and others (Mitchell)
20 Stats 5: correction for multiple measures (Vangel) Lab 6c: statistical analysis of fMRI data, part III (Yendiki) Lab 6b due

Stats 6: exploratory analysis, PCA, ICA, fuzzy clustering (Vangel)

Stats 7: causality (Vangel)

No discussion due to extra lecture content
Part 7. Structure and functional analysis
22 Structural-functional integration (Salat) Lab 6d: statistical analysis of fMRI data, part IV (Yendiki)

Quantitative neuroimaging biomarkers (Helmer)

Surface-based anatomical analysis (Salat)

No discussion due to extra lecture content Problem set 4 due
24 Spatial normalization for group analysis (Sabuncu) Complete work on labs 6c, 6d as needed Labs 6c, 6d due
25 Granger causality analysis for fMRI (Vangel) Neurohumoral hypothesis - redoux (Moore)
Final exam