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.
This course is part of the Neuroscience and Neuroimaging Specialization
Offered By
Neuroscience and Neuroimaging SpecializationJohns Hopkins UniversityAbout this Course
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- Statistics
- Statistical Analysis
- Statistical Model
- Preprocessor
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Syllabus - What you will learn from this course
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Reviews
- 5 stars72.23%
- 4 stars21.85%
- 3 stars4.49%
- 2 stars0.89%
- 1 star0.51%
TOP REVIEWS FROM PRINCIPLES OF FMRI 1
Very clear introductory course about fMRI. It touches almost every concept needed to understand an MRI experiment. Many complex topics were explained in a very clear and concise way.
Amazing course. More advanced than I thought it would be, which was excellent. Interested students should know that it has a lot of statistics in it.
A very well structured course starting from the basics of fMRI. It is of great help in understanding what goes into fMRI analysis
A very good introduction, but you would need some decent knowledge in statistics to fully understand the methods part. Standard undergrad psychology courses in statistics should be enough.
About the Neuroscience and Neuroimaging Specialization
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