Course Meeting Times
Lectures: 2 sessions / week, 1 hour / session
Labs: 1 session / week, 1.5 hours / session
Discussions: 1 session / week, 1 hour / session
Course Format
The course employs twiceweekly 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.
Prerequisites
Probability, linear algebra, differential equations, and introductory or collegelevel subjects in neurobiology, physiology, and physics are required.
Required Textbook
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. 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
ACTIVITIES  PERCENTAGES 

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.
Calendar
SES #  LECTURES  LABS  DISCUSSIONS  KEY DATES 

Part 1. Overview  
1 
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 (WhitfieldGabrieli, Triantafyllou)  Lab 1 due  
5  Cerebrovascular anatomy and neural regulation of CNS blood flow (Dickerson)  The hemoneural hypothesis (Moore)  
Part 3. Physics of image acquisition  
6  MRI physics I (Wald)  BottomUp 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 nonBOLD techniques (Bolar)  Lab 5: diffusion weighted imaging workshop (Pujol)  Lab 4a due  
13 
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  
MidTerm exam  
Part 6. Statistical analysis  
17  Stats 2: level 1 (Greve)  Eventrelated singleshot 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  
21 
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  Structuralfunctional integration (Salat)  Lab 6d: statistical analysis of fMRI data, part IV (Yendiki)  
23 
Quantitative neuroimaging biomarkers (Helmer) Surfacebased 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 