YoVDO

Principles of fMRI 1

Offered By: Johns Hopkins University via Coursera

Tags

Health Care Courses Data Analysis Courses Biostatistics Courses Neuroscience Courses Experimental Design Courses Generalized Linear Models Courses

Course Description

Overview

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.

Syllabus

  • Week 1
    • This week we will introduce fMRI, and talk about data acquisition and reconstruction.
  • Week 2
    • This week we will discuss the fMRI signal, experimental design and pre-processing.
  • Week 3
    • This week we will discuss the General Linear Model (GLM).
  • Week 4
    • The description goes here

Taught by

Martin Lindquist and Tor Wager

Tags

Related Courses

Generalized Linear Models in Python
DataCamp
Generalized Linear Models in R
DataCamp
Multiple and Logistic Regression in R
DataCamp
FA19: Statistical Modeling and Regression Analysis
Georgia Institute of Technology via edX
Advanced SAS Programming for R Users, Part 1
LinkedIn Learning