Bachelor
2025/2026
Fundamentals of neuroimaging and Brain-computer Interface using MRI
Type:
Elective course (Cognitive Neurobiology)
When:
4 year, 1, 2 module
Open to:
students of one campus
Language:
English
Course Syllabus
Abstract
The course "MRI and Brain-Computer Interface, Neuroimaging Data Analysis" is one of the elective educational elements in the educational program "Cognitive Neuroscience". The course combines two main areas devoted to the basics of functional MRI and MRS methods, as well as real-time data processing and a brain-computer interface based on functional MRI. The course is conducted on the basis of fundamental theoretical knowledge and the latest scientific publications. It includes lectures, exercises and practical classes that allow students to apply and implement the knowledge gained. In particular, during the course on functional MRI and MRS methods, students will study the neurobiological foundations of a signal dependent on the level of oxygen in the blood, current prerequisites for the physics of MRI, types of contrasts and images possible on modern MRI scanners, learn to determine the quality of data, master standard pre-processing of functional data, computer modeling and statistical parametric mapping. Students will then learn how to build models for single-session analysis (Level 1), how to analyze data across a group of subjects (Level 2), and how to compare groups of subjects and repeated measures data. Students will also learn relevant aspects of cognitive neuroscience, assessing brain activity and connectivity outcomes, block- and event-related fMRI experiments, and examining behavioral measures using traditional statistical methods. Students will also learn how to perform preprocessing and spectral fitting. Hands-on sessions will include exercises in elements of traditional (pre)processing. At the end of the course, students will be expected to complete an independent data analysis exercise based on exemplary fMRI and fMRI datasets.