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.
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Principles of fMRI 1
This course is part of Neuroscience and Neuroimaging Specialization
Instructors: Martin Lindquist, PhD, MSc
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There are 4 modules in this course
This week we will introduce fMRI, and talk about data acquisition and reconstruction.
What's included
8 videos2 readings1 assignment
This week we will discuss the fMRI signal, experimental design and pre-processing.
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9 videos1 assignment
This week we will discuss the General Linear Model (GLM).
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8 videos1 assignment
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7 videos1 assignment
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