What you'll learn

Skills you'll gain

Specialization - 4 course series

Learners will go from fMRI data design, structure and acquisition to using the R programming language (https://cran.r-project.org/) and its associated package to perform manipulation, processing, and analysis of neuroimaging data. Specifically, you will learn how to read/write images of the brain in NIfTI format, visualize and explore these images, perform inhomogeneity correction, brain extraction, and image registration (within a subject and to a template).

Neuroimaging methods are used with increasing frequency in clinical practice and basic research. Designed for students and professionals, this course will introduce the basic principles of neuroimaging methods as applied to human subjects research and introduce the neuroscience concepts and terminology necessary for a basic understanding of neuroimaging applications. Topics include the history of neuroimaging, an introduction to neuroimaging physics and image formation, as well as an overview of different neuroimaging applications, including functional MRI, diffusion tensor imaging, magnetic resonance spectroscopy, perfusion imaging, and positron emission tomography imaging. Each will be reviewed in the context of their specific methods, source of signal, goals, and limitations. The course will also introduce basic neuroscience concepts necessary to understand the implementation of neuroimaging methods, including structural and functional human neuroanatomy, cognitive domains, and experimental design.

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.

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 analysis of Functional Magnetic Resonance Imaging (fMRI) data. It is a continuation of the course “Principles of fMRI, Part 1”.

By the end of this course, you will be able to: Read/write images of the brain in the NIfTI (Neuroimaging Informatics Technology Initiative) format Visualize and explore these images Perform inhomogeneity correction, brain extraction, and image registration (within a subject and to a template).

Principles of fMRI 1

Principles of fMRI 2

Introduction to Neurohacking In R