Course description
The main purpose of the course is to enable the students to acquire solid understanding of the tools available to analyze brain activity data measured with functional magnetic resonance imaging (fMRI). The students will develop the ability to critically review results provided by different methods, to select the most adequate tools and experimental designs to answer different questions and to compare their relative advantages.
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.
Prerequisites and Selection
Prerequisite courses, or equivalent
Background in cognitive sciences, psychology, medicine, biomedicine, biology, medical imaging, computational biology or any humanistic discipline where neuroimaging is used as an experimental tool.
Selection
Selection will be based on:
1) the relevance of the course syllabus for the applicant’s individual study plan/research (according to written motivation).
2) start date of doctoral studies (priority given to earlier start date).
Course director
Rita Almeida
Peter Fransson
Course syllabus
K8F5522
Department
Department of Clinical Neuroscience
Doctoral programme
Neuroscience
Type of course
**Other course
Keywords
neuroimaging, human brain imaging, fMRI, methods, cognitive neuroscience