| SES # | LECTURES | LABS | DISCUSSIONS | KEY DATES |
|---|---|---|---|---|
| Overview (Primary faculty: Randy Gollub) | ||||
| 1 | Introduction to the course (Gollub) Introduction to fMRI (Rosen) | |||
| Functional neural systems (Primary faculty: Brad Dickerson) | ||||
| 2 | MRI safety training (Gollub) Lab 1: fMRI acquisition labs I, II (S. Gabrieli, Triantafyllou) | Problem set 1 out | ||
| 3 | Neural systems I, II (Dickerson) | |||
| 4 | Neural systems III (Dickerson) | Lab 2: intro to fMRI data and analysis (Bolar) | ||
| Imaging physiology (Primary faculty: Randy Gollub) | ||||
| 5 | Respiratory and cardiovascular physiology impact on fMRI (Banzett) | Human subject safety issues (Gollub) | Problem set 1 due Problem set 2 out | |
| 6 | Cerebrovascular anatomy and neural regulation of CNS blood flow (Dickerson) | Concurrrent learning and imaging (J. Gabrieli) | ||
| 7 | Neurovascular coupling; global vs. regionally specific changes in CBF and metabolism (Dickerson) | Lab 3: improving fMRI signal detection using physiological data (Melcher) | Lab 2 due | |
| Physics of image acquisition (Primary faculty: Larry Wald, Karl Helmer) | ||||
| 8 | MRI physics I (Helmer) | Parallel imaging (Sodickson) | ||
| 9 | MRI physics II and III (Wald) | Problem set 2 due Problem set 3 out | ||
| 10 | Physics of diffusion weighted imaging (Helmer) | Lab 4: the life cycle of medical imaging data (Pujol) | ||
| 11 | Clinical applications of perfusion weighted imaging (Sorensen) | Understanding the issues in the controversial papers on face perception in autism (Hadjikhani) | Lab 3 due | |
| 12 | Lab 5: MRI physics lab I, II (Wald, Triantafyllou) | |||
| 13 | Quantitative fMRI: CBV, CBF, and ASL (Mandelville) | Modeling the BOLD signal: CBV/CBF methods and applications (Mandeville) | ||
| Experimental design (Primary faculty: Robert Savoy) | ||||
| 14 | General principles of experimental design I (Savoy) | Lab 6: diffusion weighted imaging workshop (Pujol) | Lab 4 due | |
| 15 | General principles of experimental design II (Savoy) | fMRI investigation of memory (Buckner) | ||
| 16 | Psychological state variables in imaging (Savoy) | Primer: matrix algebra for fMRI data (Greve) | Problem set 3 due | |
| Mid-term exam | ||||
| Statistical analysis (Primary faculty: Doug Greve, Mark Vangel, Anastasia Yendiki) | ||||
| 17 | Stats I (Greve) | Lab 7: statistical analysis of fMRI data, part I (Yendiki) | Problem set 4 out | |
| 18 | Stats II (Greve) | Reconciling discrepent fMRI findings (Manoach) | Lab 5 due | |
| 19 | Stats III (Greve) | Lab 7: statistical analysis of fMRI data, part II (Yendiki) | Lab 6, 7 part I due | |
| 20 | Beyond the GLM; exploring connectivity in fMRI data (Vangel, Greve) | Linking blood flow to neural activity (Moore) | ||
| 21 | Stats IV (Greve) | Lab 7: statistical analysis of fMRI data, part III (Yendiki) | ||
| 22 | Stats V (Vangel) | fMRI evaluation of neural plasticity in somatosensory cortical representation (Napadow) | Problem set 4 due | |
| Structural and functional analysis (Primary faculty: David Salat) | ||||
| 23 | Spatial normalization for anatomical analysis (Kennedy) | Lab 7: statistical analysis of fMRI data, part IV (Yendiki) | Lab 7 part II, part III due | |
| 24 | Diffusion tensor imaging applications (Gollub) | fMRI investigation of visual processing (Kanwisher) | Problem set 4 due Lab 7 part IV due after two days | |
| 25 | Surface based anatomical analysis (Salat) | Final exam preparation (Bolar) | ||
| 26 | Future directions in functional neuroimaging (Gollub) | Extra TA office hours (Bolar) | ||
| Final exam | ||||
Table of Contents
Syllabus
Syllabus
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This page includes the course calendar.
Course Overview
This team taught, multidisciplinary course covers the fundamentals of magnetic resonance imaging relevant to the conduct and interpretation of human brain mapping studies. The challenges inherent in advancing our knowledge about brain function using fMRI are presented first to put the work in context. The course then provides in depth coverage of the physics of image formation, mechanisms of image contrast, and the physiological basis for image signals. Parenchymal and cerebrovascular neuroanatomy and application of sophisticated structural analysis algorithms for segmentation and registration of functional data are discussed. Additional topics include fMRI experimental design including block design, event related and exploratory data analysis methods, building and applying statistical models for fMRI data. Human subjects issues including informed consent, institutional review board requirements and safety in the high field environment are presented.
Prerequisites
Linear Algebra (e.g. 18.06) and Differential Equations (e.g. 18.03). Introductory or college level courses in neurobiology (e.g. 9.01), physiology, probability (e.g. 6.041), and physics (e.g. 8.01 and 8.02) are preferred.
Required Textbook
Huettel, S. A., A. W. Song, and G. McCarthy. Functional Magnetic Resonance Imaging. Sunderland, MA: Sinauer Associates, Inc., 2004. ISBN: 9780878932887.
This book will be supplemented by readings in the research literature and other books.
Course Format
The course employs two 60 minutes lectures per week, along with weekly laboratory and recitation sessions. Laboratory sessions will include fMRI data acquisition sessions and data analysis workshops. Assignments include reading of the primary textbook chapters and primary literature, fMRI data analysis in the laboratory, and several problem sets.
The majority of the computer labs will be run using Neurolens fMRI Analysis software, Slicer software, and MATLAB®.