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 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.
Prerequisites
Probability, linear algebra, differential equations, and introductory or college-level 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 (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 | |
| 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 | |
| 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 | |
| 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 | Structural-functional integration (Salat) | Lab 6d: statistical analysis of fMRI data, part IV (Yendiki) | ||
| 23 |
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 | ||||