Syllabus

This course is a survey of techniques and topics related to the analysis of brain-scan images from a medical imaging technique called “diffusion MRI”. We will read papers from the current research literature, as well as working from notes that I (Jadrian) prepare. Along the way we'll learn a little biology, a little physics, a little math, and a lot of computer science, in addition to the arcana of the sub-field of diffusion MRI analysis. These are the things I intend for you to learn / get experience with during this class:

• A broad perspective on the field of diffusion MRI analysis
• How to read and critique scientific papers
• How to design and refine scientific papers and research
• How to execute scientific research

In broad strokes, here's how the course is going to go:

• During the first five weeks:
  • We'll read a bunch of papers and discuss them in class. You will be expected to read each paper in a group (which I will assign), outside of class time, before we discuss it in class. See also the instructions for readings.
  • Some classes will just be regular lectures, with no assigned reading.
  • Some classes will take place in a lab, so we can work with data and code.
• The latter half of the class will be taught mostly by your classmates:
  • At the end of week 3, everyone will be matched with a partner and a paper to work on.
  • You and your partner will read your paper, give a presentation on it, conduct a small bit of research in response to the paper, and write up your results as a paper of your own.
  • The draft of your response paper is due at the end of week 5.
  • Weeks 6 and 7 are for workshopping the papers, in-class lab time, short update presentations, and covering any other material that would be helpful.
  • Each pair will lead a discussion of their paper during weeks 8 and 9.
  • Final papers are due in the middle of the exam period.

For more details, please see the schedule page, which will be kept up-to-date as we decide on topics together throughout the course.

This course is structured as a research-oriented seminar. There's no book, and the format is very open-ended; we have the flexibility to explore all kinds of subjects related to medical image analysis. The class is very little more than a bunch of people sitting in a room and learning from each other. This means that what you get out of it will depend strongly on what you put into it.

Given these observation, here are some requirements for the course:

• Readings. Most class sessions will be built around discussion of academic papers that you will be assigned to read. It is critical that you do the reading before the class in which we discuss it (see the instructions). Some discussions may span multiple days; in this case, I will expect you to re-read the paper before the second day of discussion as well. Keep in mind that the readings may be rather difficult; set aside plenty of time to do them, take your time, and really dig in. You will learn a lot by grappling with the material, but it won't be easy.
• Attendance. I expect that you will attend every class meeting — there are no excused absences except under extraordinary circumstances. The percentage of classes that you attend will factor directly into your grade. Note that minor illnesses, job interviews, sports, and conferences are not extraordinary circumstances. Keep things in perspective, though: there are 28 class meetings, which means that each class counts for 3.6% of a portion of your final grade. If you belong in bed or out getting a dream job, then do it!
• Presence. Being present is more than just physically being there. Turn off your phone, do not text during class, do not use a laptop for non-note-taking purposes, etc. We've only got a short time together, so let's make the most of it.
• Asking Questions. That's right, you are required to ask questions if you have them! (Not that I can enforce that.) Raise your hand, interrupt me if you need to, but don't stay silent! If you have a question, your classmates are probably wondering about it too. The flow of this class is largely going to be dictated by the things that people have questions about, so if you don't ask, there's nothing to talk about!
• Participating in Discussion. As I said, this class is basically just a bunch of us sitting in a room and discussing. I expect everyone to participate in that discussion. If you feel like you didn't get part of the reading, ask questions. If you feel like you did, chime in with your interpretation. If you thought some part was stupid or flawed, that's a valid response too: say why!

• Yourself. If you're stuck on something, take a break and think about something else for a few hours and then try a fresh start. Break down tricky sentences word-by-word; academic writing is often obnoxiously dense. Draw diagrams to help you figure out what's going on. Sometimes it helps to write things up in code, too.
• Your reading group. You will never be assigned to read something on your own. You are each other’s best resource: talking through the course material with someone else who is also trying to master it is a great way for you both to learn. (And don’t discount the learning that you will do while trying to explain to a classmate an idea covered during class that you think you understand! Teaching to others really shows you where the gaps in your knowledge are.)
• Other papers, or textbooks, or Wikipedia. Sometimes, understanding a single paper involves reading six other things. Look up the papers cited by the one you're reading, and check Google Scholar or other databases for related work. Ask for help at the library if you're having trouble finding a citation. Terms not exclusively related to diffusion MRI are often covered quite well in textbooks or even on Wikipedia.
• A teddy bear (or imaginary expert). Seriously! This idea is also known as rubber ducking. When you have trouble thinking through something, describe it out loud to a teddy bear, or draft an email to a smart person you respect. You'll have to explain the context and particulars of the problem at hand, how you've tried to figure it out, and why you're still confused. In the case of the teddy bear, this is because teddy bears don't generally know a lot of computer science (or medical imaging); in the case of the expert, you'll want to be sure to avoid wasting their time by asking about something you haven't really thought through. 90% of the time, you'll find that in the process of explaining your problem to someone else, you realize exactly how to move forward. I still use this trick pretty often, and it's very reliable.
• The course forum. Our Moodle has a forum set up; if you've written a teddy-bear explanation and you're still confused, go ahead and post it to the course forum. Don't worry about being too verbose in your writing; better to be really clear than to leave things out.
• Your colleagues. Like your reading group, but bigger! You're free to discuss your work with your classmates and other students. However, doing each other's work is off limits. I would encourage you to try to work in small groups as much as possible, and only seek outside help from other classmates when absolutely necessary; working habitually in big groups is counterproductive for your learning. Please pay close attention to the Collaboration Policy below.
• Me. I set aside four hours during the week when you can drop by to see me at my office, CMC 320. They're listed in the “The Essentials” box at the top of the page.

  Though I am generally around except on Tuesdays, please don't drop by my office outside of office hours. If you’d like to meet with me outside of my office hours, please check my calendar, email me as far in advance as possible (24 hours would be nice), and propose at least two different meeting times that would work for you. I reserve Tuesdays and the weekends for research, so while I’ll try to answer any emails in a timely fashion during those times, I won’t be available for in-person meetings.

• Other college resources. In this class, as with all classes at Carleton, there are a number of college-wide resources that can be of help. Use the library. Use the Write Place. Feel free to talk to the lab assistants in the CS labs on the 3rd floor of the CMC in the evenings. The Math Skills Center may be able to help you with some aspects of the course too. Finally, the college has a tutoring program available, which you can investigate if required.

Your grade will be computed as follows:

Using the above weights, a total of 90% and up will earn you some level of A, 80% and up at least some level of B, 70% and up at least some level of C, 60% and up at least some level of D.

Assignments turned in up to 24 hours late will be marked off by 50%. Assignments turned in more than 24 hours late will be given a zero grade. I intend to be very strict about this policy, so it will almost always benefit you to turn in incomplete work on time, if the only alternative is to turn in complete work late.

You are expected to maintain the utmost level of academic integrity in the course. Any violation of the code of academic integrity will result in severe punishment, which may include receiving a failing grade in the course or even dismissal from the college. Academic dishonesty has no place in an institute of higher learning; it wastes my time and yours.

Please familiarize yourself, if you haven't already, with the College's academic integrity policy and the Dean of the College's detailed guide to academic integrity.

In addition to that, there is a specific collaboration policy in place for this course:

I am obligated by the Faculty Handbook to report any suspected violations to the Dean’s office. Any student who is found responsible for academic dishonesty in this class will receive an F for the course.

If you have any doubt about any aspect of this policy, ask beforehand!