Matlab for Neuroscience

Period (from - till): 7 January - 30 January 2025 (BMS_P2_A)

Faculty
Mariana P. Branco, UMCU Brain Center, Department Neurosurgery and Neurology

Course description
This course introduces MATLAB as a programming environment to solve basic neuroscience problems involving signal analysis, plotting and statistics. This course also teaches how to do troubleshooting, debug and use specific external toolboxes.
Students attending this course should have competed the Introduction to Programming using MATLAB course (BMB530421) or have a programming background. In particular knowledge about indexing and slicing of multidimensional arrays, logic, conditions, loops and basics of algebra. Students must have a laptop with an installation of MATLAB 2024a or later before the start of the course. MATLAB with a student’s license can be obtained fromhttps://students.uu.nl/gratis-software.

Literature/study material used :
Lecture slides and assignment will be provided by the docent. No book is required, but one is recommended: MATLAB for Brain and Cognitive Scientists, by Mike X Cohen. All course related information including slides, exercises and assignments will be made available in MSTeams.

Course Design:
There are eight sessions in total from 10.00 till 13.00. Each session comprises of a lecture 10h-12h (mandatory presence ) and a tutorial hour 12h-13h (not mandatory) . Self-study is expected from 14h-17h. For latest info about place of the session please check MSTeams.
Session Date Time
(lecture + tutorial hour) Place 1 07-01-2025 10h-13h HVDB - 2.30 2 09-01-2025 10h-13h HVDB - 4.33 3 14-01-2025 10h-13h HVDB - 2.06 4 16-01-2025 10h-13h HVDB - 2.70 5 21-01-2025 10h-13h HVDB - 3.71 6 23-01-2025 10h-13h HVDB - 2.05 7 28-01-2025 10h-13h HVDB - 2.05 8 30-01-2025 10h-13h HVDB - 4.52

Course content:
Session 1 MATLAB basics
Session 2 Loops and functions
Session 3 Errors and debugging
Session 4 Input-Output, visualizing data
Session 5 Statistics and visualization
Session 6 Neural data analysis
Session 7 Advanced topics and toolboxes
Session 8 The MATLAB Master Hackathon

Assessment (3 EC)
Students are expected to attend lectures, do self-study and solve home-assignments every day after each session. The deadline to submit home-assignments is the same day at midnight. To pass the course the student must complete and submit 6 home-assignments distributed in the end of session 1 to 6. Submission of the home-assignments in MSTeams is mandatory but these will not the graded. Assessment consists of the submission of the 6 home-assignments, the submission of one final group assignment and an oral exam, both of which will be graded:

Final Grade = 0.60 x (group assignment) + 0.40 x (oral exam)

*Deadline for group Assignment: *
February 6th 2025, 9:00am

*Oral Exam: *
February 7th 2025 (online)

During the first lecture you will be asked to divide yourself into groups. The exact time of your oral exam (1 hour) will be determined after the first lecture and communicated with you.

Credits-hours calculator
3 ECTS = 84 hours

Lectures 2 hours x 8 = 16 hours
Self-study and assignments = 68 hours

In case of questions feel free to reach us at:
Mariana Branco M.PedrosoBranco@umcutrecht.nl

Registration :
You can register for this course via here on the Students' site.
Any questions can be asked to Mariana Branco (m.pedrosobranco@umcutrecht.nl). Maximun participants is 45

Mandatory for students in Master’s programme :
No.

Registration open for students from other programme's:
Yes

Prerequisite knowledge
Basic knowledge of programming or completion of** Introduction to Programming using Matlab course.**

After finishing this course, the student will:

1. Learn about the MATLAB environment, its programming language and how to use it to solve problems related to neuroscience.
2. Use MATLAB (or its toolboxes) to solve a real-life neuroscience problem.
3. Translate a neuroscience problem to MATLAB programming language.
4. Provide MATLAB solutions for some neuroscience problems.
5. Associate the examples given in class with real-life problems related to other courses or internships.
6. Be able to interpret, translate, troubleshooting and solve MATLAB problems in an efficient manner.
7. Master the MATLAB environment and learn how to look for help documents, existing solutions and how to use toolboxes.

Je wordt ingeschreven voor deze cursus door de administratie van de opleiding van de cursus.