Principles of fMRI 1
Master the fundamentals of functional MRI: from data acquisition to statistical analysis of brain imaging data.
Master the fundamentals of functional MRI: from data acquisition to statistical analysis of brain imaging data.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Neuroscience and Neuroimaging Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
4.6
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English
پښتو, বাংলা, اردو, 3 more
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What you'll learn
Understand fMRI data acquisition and reconstruction methods
Master experimental design principles for brain imaging studies
Learn pre-processing techniques for fMRI data
Apply statistical models for analyzing brain imaging data
Gain practical experience with General Linear Models
Skills you'll gain
This course includes:
5.8 Hours PreRecorded video
4 quizzes
Access on Mobile, Tablet, Desktop
FullTime access
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There are 4 modules in this course
This comprehensive course covers the design, acquisition, and analysis of Functional Magnetic Resonance Imaging (fMRI) data. Students learn about psychological inference, MR Physics, K-space, experimental design, pre-processing of fMRI data, and Generalized Linear Models (GLMs). The curriculum combines theoretical foundations with practical applications, making it suitable for researchers and practitioners from various disciplines including psychology, statistics, physics, computer science, and neuroscience.
Week 1
Module 1 · 2 Hours to complete
Week 2
Module 2 · 2 Hours to complete
Week 3
Module 3 · 2 Hours to complete
Week 4
Module 4 · 1 Hours to complete
Fee Structure
Instructors
Neuroimaging Statistics Expert and fMRI Research Pioneer at Johns Hopkins
Dr. Martin Lindquist serves as Professor of Biostatistics at Johns Hopkins University, specializing in mathematical and statistical applications in functional Magnetic Resonance Imaging (fMRI). His research encompasses the full spectrum of fMRI analysis, from developing new k-space sampling trajectories and reconstruction algorithms to creating innovative statistical methods for analyzing fMRI time series data. His work particularly focuses on advancing methods for studying brain connectivity and using neuroimaging data to predict psychological and disease states, making significant contributions to the field of neuroimaging statistics.
Distinguished Neuroscientist and Brain Research Leader
Dr. Tor Wager holds the prestigious position of Diana L. Taylor Distinguished Professor, with affiliations at both Johns Hopkins University and the University of Colorado Boulder. His groundbreaking research focuses on understanding brain mechanisms of pain, emotion, and human consciousness. Through his innovative work in neuroimaging and brain-behavior relationships, he has made significant contributions to our understanding of how the brain processes pain and emotions. His research has revolutionized our knowledge of placebo effects and brain-body connections, leading to important discoveries in pain management and emotional regulation. Dr. Wager's work combines advanced neuroimaging techniques with sophisticated analytical methods to explore how psychological processes influence physical health and well-being.
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4.6 course rating
819 ratings
Frequently asked questions
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