PRINCIPLES AND METHODS OF FUNCTIONAL NEUROIMAGING I Syllabus
Course Learning Objectives
Upon successfully completing this course, students will be able to:
- Describe key aspects of fMRI experimental design, and design and prepare a human subjects fMRI experiment.
- Explain the specific methods, source of MR signal, goals and limitations and research design issues for fMRI studies.
- Import and pre-process fMRI data including slice-timing correction, motion correction and registration.
- Perform individual subject and group-level univariate statistical analysis of fMRI data with appropriate thresholding and multiple comparison correction.
- Critically evaluate research methods and results of human subjects fMRI studies in published literature.
Course DescriptionIntroduces the principles of functional magnetic resonance imaging (fMRI) as applied to human subjects research. Presents a theoretical overview of human fMRI research and includes key aspects of the design, data collection, processing, analysis and publication of a human subjects fMRI experiment. Focuses on describing all aspects of an fMRI study from the initial experimental design, through data collection and pre-processing, to statistical analysis. Describes the goals and limitations for fMRI studies, the data format and how it is processed prior to statistical analysis. Focuses on preforming individual subject and group level univariate statistical analysis of fMRI data with appropriate thresholding and multiple comparison correction. Weekly labs provide a practical application of these concepts to sample datasets and prepares students for the analysis of fMRI data.
Intended AudienceGraduate students in the Schools of Medicine, and Public Health, medical residents, and postdoctoral fellows, and junior, as well as, senior faculty members who have an interest in using neuroimaging as a new method in their research.
Methods of AssessmentLab assignments (50%) and take-home final exam (50%)
PrerequisitesAn introductory statistics class and a working knowledge of regression
Please see the course Session for a full list of dates and items for this course.
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