LI1001SF Imaging in Neuroscience: with a Focus on Functional Magnetic Resonance Imaging, 7.5 credits

The course is aimed at PhD students with a background in a humanistic discipline where neuroimaging is used as an experimental tool, cognitive sciences, psychology, medicine, biomedicine, biology, medical imaging, computational biology or similar.

Content

The course focuses on experimental design and analysis of fMRI data. We will briefly introduce the basis of the blood-oxygen-level dependent (BOLD) signal and how it is measured. The image processing steps, before statistical analysis, will be explained. The application of general linear model analysis to fMRI data will be explained, including random effects analysis and correction for multiple comparisons. We will discuss experimental designs for fMRI studies. The study of functional connectivity using fMRI data will be explained. We will also introduce machine learning techniques for analysis of fMRI data. Finally, structural measures of gray and white matter will be introduced as well as other techniques to measure functional and metabolic brain activity non-invasively.

Forms of instruction

The course consists of lectures, hands-on sessions, individual assignments, group discussions and student presentations. Teaching and examination language is English.

Download syllabus LI1001SF 7,5 pdf, 397.7 kB.

A part of this course, corresponding to 1,5 higher education credits, is overlapping with the course LI1002SF: Imaging in neuroscience, 1.5 credits as well as with the course 5522 Imaging in neuroscience: 1,5 credits offered by Karolinska Institutet.

This 7.5 HEC course offers a more extensive practical training in individual assignments and a deeper understanding of the practical use of different methods.