Functional Magnetic Resonance Imaging (fMRI) is the most widely used technique for investigating the living, functioning human brain as people perform tasks and experience mental states. It is a convergence point for multidisciplinary work from many disciplines. Psychologists, statisticians, physicists, computer scientists, neuroscientists, medical researchers, behavioral scientists, engineers, public health researchers, biologists, and others are coming together to advance our understanding of the human mind and brain. This course covers the design, acquisition, and analysis of Functional Magnetic Resonance Imaging (fMRI) data, including psychological inference, MR Physics, K Space, experimental design, pre-processing of fMRI data, as well as Generalized Linear Models (GLM’s). A book related to the class can be found here: https://leanpub.com/principlesoffmri.
Dieser Kurs ist Teil der Spezialisierung Spezialisierung Neuroscience and Neuroimaging
von
Spezialisierung Neuroscience and NeuroimagingJohns Hopkins UniversityÜber diesen Kurs
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- Statistics
- Statistical Analysis
- Statistical Model
- Preprocessor
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Lehrplan - Was Sie in diesem Kurs lernen werden
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Bewertungen
- 5 stars72,29 %
- 4 stars21,77 %
- 3 stars4,51 %
- 2 stars0,90 %
- 1 star0,51 %
Top-Bewertungen von PRINCIPLES OF FMRI 1
It is really easy going and interesting course. With good explanations that keep you on track easily. I really liked it since the begging and it gave me curiosity to undertake the second one
Great course which introduces one to the basic principles of fMRI and Statistical Analysis.
Some hands on exercises and projects might help to better understand some concepts.
It was a wonderful beginning to a topic details of which were unknown to me. Thank you to both the instructors for making the videos crisp, informative and understandable. Thank you very much.
Great course, would be better if it incorporated labs/practical assignments to practice or apply the principles of fMRI onto actual datasets.
Über den Spezialisierung Neuroscience and Neuroimaging
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