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About this course

The course is designed to provide students and researchers with a solid understanding of functional Near-Infrared Spectroscopy (fNIRS) as a relatively new tool to measure brain activity and will emphasize both theoretical knowledge and practical skills of fNIRS. The students will gain expertise in the underlying principles of fNIRS, its instrumentation, and various analytical approaches. The primary goal is to empower students with the knowledge of this additional neuroimaging tool to design and execute advanced experiments, interpret fNIRS data effectively, and contribute to cutting-edge research in neuroscience and related fields.

The course overlaps with the course Imaging in neuroscience: with a focus on fNIRS, offered at Karolinska Institute and The Swedish School of Sport and Health Sciences (GIH). The sessions will be a mix of in person and virtual meetings with practical sessions held at uMOVE - Gävlegatan 55, Solna and at the BMC-lab at GIH – Lidingövägen 1, Stockholm

Learning outcomes

The primary goal is to empower students with the knowledge of this additional neuroimaging tool to design and execute advanced experiments, interpret fNIRS data effectively, and contribute to cutting-edge research in neuroscience and related fields.

Prerequisites for participation

Educational background or research experience in relevant fields such as neurosciences, psychology, medicine, biomedicine, medical physics, medical imaging, computational biology, or any humanistic discipline employing neuroimaging as an experimental tool.  Although not a prerequisite, it is an advantage to have a basic understanding of different statistical methods and programming skills in MATLAB, Python and R.

SELECTION

The selection process will consider:
1) the alignment of the course syllabus with the applicant's doctoral project or research (as articulated in the written motivation), and
2) the commencement date of the applicant's doctoral studies, with preference given to those who began their studies at an earlier date.



 

Necessary language skill
English
Semester(s) in which the module takes place
Autumn Semester 2024
Course level
Doctoral
Course start date
11 Nov 2024
Course end date
15 Nov 2024
Apply between
Application start date
15 Apr 2024
-
Application end date
30 May 2024
Teaching mode
Hybrid
Workload in ECTS
1.5
Person in charge of module
Lucian Bezuidenhout
Email address
lucian.bezuidenhout@ki.se
Local module ID
C4F5573
Link to the course
Link to detailed course description and registration
Documents