Course catalogue doctoral education - VT21

  • Ansökan kan ske mellan 2020-10-15 och 2020-11-16
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Title Imaging in Neuroscience: with a Focus on Structural MRI Methods
Course number 3064
Programme Neurovetenskap
Language English
Credits 1.5
Date 2020-11-23 -- 2020-11-27
Responsible KI department Institutionen för neurobiologi, vårdvetenskap och samhälle
Specific entry requirements
Purpose of the course The main purpose of the course is to provide the students with a solid understanding of the tools available to analyze brain structural data measured with structural magnetic resonance imaging (sMRI). 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.
Intended learning outcomes After attending the course the student should be able to:
- Explain how MR images are generated, what causes artifacts and how to control for them.
- Describe how MRI is used today for dementia investigations.
- Formulate the basics of surface-based analysis and voxel-based morphometry (differences, similarities, quality control etc.).
- Formulate the basis for multivariate data analysis using structural data in combination with other type of data.
- Formulate the basis for network analysis (using graph theory) using structural data in combination with other types of data.
- Give an overview of different methods for analyzing diffusion tensor imaging (DTI) data as well as other imaging modalities.
Contents of the course The course focuses on neurodegenerative disorders and in vivo measurements of brain structure. The fundamentals of image processing will be introduced together with an overview of basic MRI physics, including noise and inhomogeneities as well as optimization of pulse sequences. The course covers the methodological approach to computerized segmentation of MRI anatomy using both surface-based and voxel-based methods. We will also present how MRI is used today in clinical practice to aid the diagnosis of dementia. Further, we will discuss methods for studying the integrity of the white matter (for example, DTI). We will discuss various approaches to assess the validity and reliability of the gained results. We will also cover advanced methods (multivariate data analysis and graph theory) to analyze structural data in combination with other type of data (functional MRI, demographic, cognitive and other biomarker data).
Teaching and learning activities Lectures, seminars and workshops for 5 full consecutive days. The students will perform group projects including a critical assessment of relevant scientific literature.
Compulsory elements All parts of the course are mandatory. Absence from lectures can be compensated for by a written assignment. A missed seminar or workshop has to be compensated for at a later course occasion.
Examination The examination takes the form of a critical, in-depth discussion of the group project works, where a topic relevant to brain morphometry has been studied via a review of the scientific literature. Students will be individually assessed regarding their ability to discuss their own and others' group work in relation to the intended learning outcomes of the course.
Literature and other teaching material Recommended:

Basic MRI

Neuroimaging in Dementia
Barkhof, F., Fox, N.C., Bastos-Leite, A.J., Scheltens, P.
ISBN 978-3-642-00818-4

Brain Mapping The Systems
Arthur W. Toga & John C. Mazziotta
ISBN 0-12-692545-3
Number of students 15 - 20
Selection of students Selection will be based on 1) the relevance of the course syllabus for the applicant's doctoral project (according to written motivation), 2) start date of doctoral studies (priority given to earlier start date)
More information The course will be in Campus Flemingsberg, KI, every day of the week (23/11 - 27/11 - 2020) from 9.00 to 16.00. The exact location will be announced before the course starts.
Additional course leader
Latest course evaluation Course evaluation report
Course responsible Daniel Ferreira Padilla
Institutionen för neurobiologi, vårdvetenskap och samhälle
Contact person Maria Klein
Institutionen för neurobiologi, vårdvetenskap och samhälle

Daniel Ferreira Padilla
Institutionen för neurobiologi, vårdvetenskap och samhälle