Course Syllabus
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PSYCH 204A | 3 units | UG Reqs: None | Class # 14950 | Section 01 | Grading: Letter or Credit/No Credit | SEM | Session: 2021-2022 Winter 1 | In Person |
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Magnetic resonance imaging (MRI) has become an important scientific tool for measuring living human brain structure and function. This course is for students who would like to learn the physical basis of MRI and how the method is used to make anatomical images of brain structures (sMRI and dMRI), measure quantitative tissue properties (qMRI), and assess brain activity (fMRI). The course is designed to be helpful to people beginning to use MRI in their research and who would like to understand the strengths and limits of the methods when reading journal articles, listening to talks, or working with a collaborator. We aim to accommodate students from various backgrounds (e.g., engineering, neuroscience, psychology). This year the class lectures will be recorded and available online. We will also have regular meetings at the scheduled class time to discuss lecture material, talk over homework questions, and also talk over research papers of broad interest. In the past, class discussions have been lively and I hope we can achieve the same interaction this year, which will at least partially be online! The course work comprises a series of short homeworks (often including small programming examples and tutorials), and two longer homeworks that review the material in the first and then second half of the class. This course leads naturally to Psych 204b. Course assistant: Insub Kim (insubkim@stanford.edu) Textbook: Huettel et al., FMRI (Third Edition, Oxford). Lecture recordings (previous years)
Github sites for course tutorials and software (Matlab) To download Matlab at no charge, follow these instructions.
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00 Course Information (videos):
How to download the Matlab tutorials, navigate the Canvas page, and a course overview. These are available view prior to the first lecture (1/4).
The schedule below lists the videos in the approximate time that you should watch them. The online meetings will be devoted to discussing the videos from the prior lecture. For example, on Thursday 1/6 we will discuss the general instrumentation videos. I hope you understand that the complexity of navigating the online class under these circumstances will require some flexibility on all our parts.
| Week/Day | Date |
Topic |
Reading | Homework | Videos |
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| 1.1 |
1/4 |
Introduction: The Instrument |
Chapters 1 01 MR Physics |
01 Instrument and MR terms MR Instrumentation playlist. |
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| 1.2 | 1/6 |
MR signals I |
Chapter 2 |
02 MR Signals MR Signals playlist 1 -6
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| 2.1 |
1/11 |
MR signals II |
Chapter 3 (Conceptual) 01 MR Physics (Slide 65 or so) |
HW1 released mrTut01_MR |
02 MR Signals MR Signals playlist 7 - 9 |
| 2.2 | 1/13 |
MR signals III |
Chapter 4 (Conceptual) 01 MR Physics (Slide 110 or so) |
02 MR Signals MR Signals playlist 10 -11 03 Image Formation |
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| 3.1 | 1/18 |
Image formation I |
Chapter 5 |
HW1 due HW2 released mrTut02_Imaging |
03 Image Formation playlist 3 - 7 |
| 3.2 | 1/20 |
Image formation II |
Chapter 5 |
03 Image Formation playlist 8 - 11 | |
| 4.1 | 1/25 |
BOLD I |
Chapters 6, 7 |
HW2 due HW3 released mrTut03_LinearSystems |
04 BOLD Functional MRI playlist 1 - 5 |
| 4.2 | 1/27 |
BOLD II |
Wandell and Winawer |
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04 BOLD Functional MRI playlist 6 - 12 |
| 5.1 | 2/1 |
Computational neuroimaging, linearity tests, HRF |
HW3 due MIDTERM released |
05 Computational Neuroimaging playlist |
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| 5.2 | 2/3 |
BOLD contrast |
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05 Computational Neuroimaging playlist |
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| 6.1 | 2/8 |
Statistical reasoning |
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MIDTERM must be completed by 11:59 HW4 released |
05 Computational Neuroimaging playlist |
| 6.2 | 2/10 | Visual field maps, PRFs |
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05 Computational Neuroimaging |
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| 7.1 | 2/15 |
Diffusion Imaging: Principles and applications |
Chapter 5 |
HW4 due mrTut04_Diffusion |
06 Diffusion |
| 7.2 | 2/17 |
Modeling diffusion data I – |
Wandell review |
06 Diffusion 06-10 |
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| 8.1 | 2/22 |
Fiber tractography principles |
HW5 released mrTut05_Visualization
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07 Tractography 01-04 |
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| 8.2 | 2/24 |
Quantitative MRI measures. Ensemble tractography |
This one goes to 11. |
07 Tractography 06 - Tractography as a model 08 Quantitative MRI
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| 9.1 | 3/1 |
Topics in perception and memory |
Wandell, Chial, Backus; Pestilli self-potraits of the brain Dale, Fischl & Sereno |
HW5 due HW6 released
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08 Quantitative MRI |
| 9.2 | 3/3 |
Potential topics: |
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08 Quantitative MRI
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| 10.1 | 3/8 |
Functional connectivity (resting state) |
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HW6 due
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08 Quantitative 09 Visualization and reproducibility |
| 10.2 | 3/10 | Data and computational management tools |
You can't have enough of the big picture (1). Big picture. It's really big (2)
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We discuss topics that came up in class that need more attention, or read a new paper or two. |
09 Wrap up discussion |
Homework can be done over the course of a week.
Discuss with others, but complete the homework (and exams) on your own.
The midterm must be completed during a 24 hour time period (of your choosing) within the week.
Note: Grades are due 3/22.
Course Summary:
| Date | Details | Due |
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