Neurohacking describes how to use the R programming language (https://cran.r-project.org/) and its associated package to perform manipulation, processing, and analysis of neuroimaging data. We focus on publicly-available structural magnetic resonance imaging (MRI). We discuss concepts such as inhomogeneity correction, image registration, and image visualization.
This course is part of the Neuroscience and Neuroimaging Specialization
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Neuroscience and Neuroimaging SpecializationJohns Hopkins UniversityAbout this Course
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Learner Career Outcomes
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started a new career after completing these courses
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got a tangible career benefit from this course
Flexible deadlines
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Shareable Certificate
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Course 4 of 4 in the
Intermediate Level
Approx. 18 hours to complete
English
Subtitles: French, Portuguese (European), Russian, English, Spanish
Skills you will gain
Image ProcessingBrainR ProgrammingNeurology
Learner Career Outcomes
20%
started a new career after completing these courses
10%
got a tangible career benefit from this course
Flexible deadlines
Reset deadlines in accordance to your schedule.
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Course 4 of 4 in the
Intermediate Level
Approx. 18 hours to complete
English
Subtitles: French, Portuguese (European), Russian, English, Spanish
Offered by
Johns Hopkins University
The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.
Syllabus - What you will learn from this course
1 hour to complete
Introduction
1 hour to complete
3 videos (Total 30 min), 1 reading, 1 quiz
4 hours to complete
Neuroimaging: Formats and Visualization
In this section, we will discuss different formats that brain images come in, as well as some of the commonly done magnetic resonance imaging (MRI) scans.
4 hours to complete
7 videos (Total 74 min)
6 hours to complete
Image Processing
In this section, we will discuss the steps done to process brain MRI data. We will discuss inhomogeneity correction, brain extraction or skull stripping, and various image registration techniques.
6 hours to complete
9 videos (Total 71 min)
7 hours to complete
Extended Image Processing
In this section, we will discuss the different types of registration and how one would go through processing a multi-sequence MRI scan, as well as wrapper functions that make the process much easier. We also cover interactive exploration of brain image data and tissue-level (white/gray matter and cerebrospinal fluid (CSF)) segmentation from a T1-weighted image.
7 hours to complete
11 videos (Total 101 min), 1 reading, 10 quizzes
Reviews
TOP REVIEWS FROM INTRODUCTION TO NEUROHACKING IN R
by BRFeb 8, 2017
I like that this course goes through most necessary steps, my only suggest would be to have one additional week where you go through everything all together, and then do some simple group analysis.
by SJMay 7, 2019
Thank you for the wonderful course. Especially useful when the team explains every new line of code. As a current undergraduate and aspiring neuroscience researcher, this is tremendously helpful.
by SGAug 28, 2020
The process of downloading packages on the virtual machine was very tiring. The documentation of it could have been provided more nicely. Like I was not aware about the 'sudo...'on LINUX.
by ANJul 17, 2017
Perfect! Precise to the subject and provides a lot of hands-on details, which is, unfortunately, something that most other similar courses don't do. Absolutely loved it!
About the Neuroscience and Neuroimaging Specialization
This specialization combines the strength of 4 different neuroscience courses into a cohesive learning experience. Taught by Johns Hopkins University, it begins with fundamental neuroscience concepts for neuroimaging. Neuroimaging methods are used with increasing frequency in clinical practice and basic research. Starting with the neuroanatomy of the brain, it then moves into principles of neuroimaging, including experimental design in neuroimaging, functional connectivity MRI, diffusion tensor imaging and spectroscopy imaging.
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