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Introduction to Neurohacking In R

Ciprian M. Crainiceanu, Dr. Elizabeth Sweeney , and John Muschelli III

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.

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

Read more

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.

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).

Enroll now

What's inside

Syllabus

Introduction
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.
Read more

Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Provides foundational skills in data manipulation, processing, and analysis for neuroimaging research
Covers essential neuroimaging techniques such as inhomogeneity correction, brain extraction, and image registration
Leverages the widely used R programming language and associated neuroimaging packages
Taught by experienced instructors with expertise in neuroimaging research
Applicable for both academic and industry settings where neuroimaging data analysis is required
May require additional prerequisites in programming and neuroimaging concepts for optimal learning experience

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Reviews summary

Introduction to neurohacking in r

According to learners, this course provides an excellent introduction to neurohacking using R. Many found the explanations of neuroimaging concepts clear and the application of R programming practical. Students particularly appreciated the demonstration of useful R packages and code, stating they gained practical skills for processing neuroimaging data like NIfTI files. However, some reviewers noted that the course assumes more prior R knowledge than expected, which could make parts challenging for true beginners in R. A few also felt the pace was sometimes too fast or that the course content is introductory rather than deeply advanced.
Good for beginners, less depth for advanced users.
"This is a great starting point for neurohacking, but it's just an introduction."
"Don't expect to become an expert, but you'll learn the essential basics and workflow."
"It's suitable for beginners in the field of neurohacking."
"Might be too basic if you already have experience with R neuroimaging packages."
Concepts are explained clearly by the instructor.
"The instructor explains complex ideas clearly and makes them understandable."
"Found the lectures easy to follow and well-structured."
"Concepts like image registration and inhomogeneity correction were well-explained."
"The teaching style was engaging and effective for learning."
Teaches useful techniques with R code examples.
"The hands-on R examples were extremely valuable for applying concepts."
"I learned practical ways to manipulate neuroimaging data like inhomogeneity correction and registration."
"The code provided is very useful for applying techniques immediately to my own data."
"This gave me the tools to start working with NIfTI files and common tasks."
Provides a clear and practical start in neurohacking.
"Excellent introduction to using R for neuroimaging."
"This course helped me get started with processing brain images."
"Covers the basics really well, giving a solid foundation."
"I found the practical examples in R very helpful to begin."
Assumes prior knowledge of the R language.
"Be aware that this course assumes you already know R and programming basics well."
"I struggled a bit because my R skills were weak going into this."
"Would recommend having a good grasp of R before starting this course."
"The course requires a decent understanding of R syntax and functions to follow along comfortably."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Introduction to Neurohacking In R with these activities:
Review: An Introduction to Neuroimaging
Review this book as a foundational reference text to provide a comprehensive understanding of neuroimaging techniques and their applications.
View Clinical Neuroanatomy: Brain Circuitry and Its... on Amazon
Show steps
  • Read the introductory chapters
  • Focus on sections relevant to the course
  • Take notes and highlight key concepts
Form a study group
Join or form a study group with classmates to review course materials, discuss concepts, and prepare for assessments.
Browse courses on Collaboration
Show steps
  • Find classmates willing to participate
  • Establish a regular meeting schedule
  • Prepare discussion topics and questions
Run code examples
Run through the code examples in the course materials to ingrain the syntax of the R programming language.
Browse courses on Programming
Show steps
  • Locate the code example
  • Run the code example
Two other activities
Expand to see all activities and additional details
Show all five activities
Practice image manipulation
Complete hands-on exercises and challenges to develop proficiency in image manipulation techniques using the R programming language.
Browse courses on Image Processing
Show steps
  • Obtain sample brain images
  • Write R code to perform image manipulation tasks
  • Experiment with different parameters and settings
Create diagrams
Create diagrams of the brain to visualize and understand the concepts of inhomogeneity correction, image registration, and image segmentation.
Show steps
  • Choose a brain image
  • Use an image processing tool to create a diagram
  • Annotate the diagram with relevant information

Career center

Learners who complete Introduction to Neurohacking In R will develop knowledge and skills that may be useful to these careers:
Data Scientist
Data Scientists play a key role in developing and applying neuroimaging techniques for understanding brain function and behavior. This course would build a foundation in image processing, analysis, and visualization techniques, which are essential for Data Scientists. Understanding inhomogeneity correction, brain extraction, and image registration will be particularly relevant to this role.
See salaries and explore the career path for Data Scientist
Statistician
Statisticians are involved in the collection, analysis, interpretation, and presentation of data. In neuroimaging, Statisticians play a key role in developing statistical methods for analyzing neuroimaging data. This course would provide a strong foundation in statistical concepts and techniques that are relevant to neuroimaging.
See salaries and explore the career path for Statistician
Quantitative Analyst
Quantitative Analysts use mathematical and statistical techniques to analyze data and make predictions. In neuroimaging, Quantitative Analysts use these techniques to analyze neuroimaging data to identify patterns and relationships. This course would provide a strong foundation in the mathematical and statistical techniques used in neuroimaging.
See salaries and explore the career path for Quantitative Analyst
Machine Learning Engineer
Machine Learning Engineers develop and implement machine learning algorithms to solve real-world problems. In neuroimaging, Machine Learning Engineers develop algorithms for analyzing and classifying neuroimaging data. This course would provide a strong foundation in machine learning algorithms and techniques that are relevant to neuroimaging.
See salaries and explore the career path for Machine Learning Engineer
Software Engineer
Software Engineers design, develop, and maintain software systems. In neuroimaging, Software Engineers develop software for acquiring, processing, and analyzing neuroimaging data. This course would provide a strong foundation in software development principles and practices that are relevant to neuroimaging.
See salaries and explore the career path for Software Engineer
Biomedical Engineer
Biomedical Engineers apply engineering principles and techniques to solve problems in biology and medicine. In neuroimaging, Biomedical Engineers develop and use neuroimaging technologies for diagnosing and treating brain disorders. This course would provide a strong foundation in the engineering principles and techniques used in neuroimaging.
See salaries and explore the career path for Biomedical Engineer
Neuroscientist
Neuroscientists study the nervous system, including the brain. They use a variety of techniques to study the structure and function of the brain, including neuroimaging. This course would provide a strong foundation in the principles and techniques of neuroimaging, which are essential for Neuroscientists.
See salaries and explore the career path for Neuroscientist
Radiologist
Radiologists use imaging techniques, such as MRI, to diagnose and treat diseases. In neuroimaging, Radiologists use MRI to diagnose and treat brain disorders. This course would provide a strong foundation in the principles and techniques of MRI, which are essential for Radiologists.
See salaries and explore the career path for Radiologist
Neurologist
Neurologists diagnose and treat disorders of the nervous system, including the brain. They use a variety of techniques to diagnose and treat brain disorders, including neuroimaging. This course would provide a strong foundation in the principles and techniques of neuroimaging, which are essential for Neurologists.
See salaries and explore the career path for Neurologist
Pediatrician
Pediatricians diagnose and treat diseases in children, including brain disorders. They use a variety of techniques to diagnose and treat brain disorders, including neuroimaging. This course may provide a foundation in the principles and techniques of neuroimaging, which can be helpful for Pediatricians.
See salaries and explore the career path for Pediatrician
Psychiatrist
Psychiatrists diagnose and treat mental disorders, including those that affect the brain. They use a variety of techniques to diagnose and treat mental disorders, including neuroimaging. This course may provide a foundation in the principles and techniques of neuroimaging, which can be helpful for Psychiatrists.
See salaries and explore the career path for Psychiatrist
Neuropsychologist
Neuropsychologists study the relationship between the brain and behavior. They use a variety of techniques to study the brain and behavior, including neuroimaging. This course may provide a foundation in the principles and techniques of neuroimaging, which can be helpful for Neuropsychologists.
See salaries and explore the career path for Neuropsychologist

Reading list

We've selected 12 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Introduction to Neurohacking In R.
Cover image
Principles of Neural Science, Fifth Edition
Save
Provides a comprehensive overview of neuroscience, including the structure and function of the brain, the development of the nervous system, and the neural basis of behavior.
Principles of Neural Science, Fifth Edition...
Hardcover
$$$$
Principles of Neural Science, Fifth Edition...
Kindle Edition
$$$
Cover image
Probabilistic Machine Learning
Save
Provides a comprehensive overview of probabilistic machine learning, including supervised and unsupervised learning.
Probabilistic Machine Learning: Advanced Topics...
Hardcover
$$$$
Pattern Recognition and Machine Learning
Save
Provides a comprehensive overview of pattern recognition and machine learning, including supervised and unsupervised learning, and deep learning.
Pattern Recognition and Machine Learning...
Hardcover
$$$
Pattern Recognition and Machine Learning...
Paperback
$$$
Pattern Recognition and Machine Learning (text...
Unknown Binding
$$$$
Cover image
Deep Learning
Save
Provides a comprehensive overview of deep learning, including convolutional neural networks and recurrent neural networks.
Deep Learning
Paperback
$$$
Deep Learning (Adaptive Computation and Machine...
Hardcover
$$$
Deep Learning (Adaptive Computation and Machine...
Kindle Edition
$$$
Cover image
Functional Magnetic Resonance Imaging
Save
A textbook that provides a comprehensive overview of the principles of neuroimaging, including both theoretical and practical aspects. Useful for gaining a strong foundation in neuroimaging.
Functional Magnetic Resonance Imaging
Hardcover
$$$$
Cover image
Data Science from Scratch
Save
Provides a comprehensive overview of data science, including data cleaning, transformation, modeling, and evaluation.
Data Science from Scratch: First Principles with...
Paperback
$$
Data Science from Scratch: First Principles with...
Kindle Edition
$$
Data Science from Scratch: First Principles with...
Paperback
$$
Cover image
Dyslexia and Hyperlexia
Save
Provides a comprehensive overview of neuropsychology, a field that studies the relationship between brain function and behavior. It covers a wide range of topics, including the assessment of neuropsychological disorders and the treatment of neuropsychological disorders
Dyslexia and Hyperlexia: Diagnosis and Management...
Paperback
$$$$
Cover image
Principles and Practice of Sleep Medicine E-Book
Save
A clinical guide to neuroimaging, covering a wide range of neurological and psychiatric disorders. Useful for gaining an understanding of the clinical applications of neuroimaging.
Principles and Practice of Sleep Medicine - E-Book:...
Kindle Edition
$$$$
Cover image
Python for Data Analysis
Save
Provides a comprehensive overview of Python for data analysis, including data manipulation, visualization, and machine learning.
Python for Data Analysis
Paperback
Check
Python for Data Analysis
Kindle Edition
Check
Cover image
The Elements of Statistical Learning
Save
Provides a comprehensive overview of statistical learning methods. It covers topics such as linear regression, logistic regression, tree-based methods, and support vector machines.
The Elements of Statistical Learning: Data Mining,...
Hardcover
$$$
The Elements of Statistical Learning: Data Mining,...
Hardcover
$$$
The Elements of Statistical Learning: Data Mining,...
Kindle Edition
$$$
Cover image
The Human Brain
Save
A popular science book that provides a fascinating overview of the human brain and its functions. Useful for gaining a general understanding of the brain and its relation to neuroimaging.
The Human Brain: A Guided Tour (SCIENCE MASTERS)
Paperback
$$
Brain Power: Working Out the Human Mind
Hardcover
$$
The Human Brain: A Guided Tour (Science Masters...
Kindle Edition
$
Cover image
Handbook of Functional MRI Data Analysis
Save
Provides a comprehensive overview of statistical methods for fMRI data analysis. It covers topics such as experimental design, data preprocessing, and statistical modeling.
Handbook of Functional MRI Data Analysis
Paperback
Check
Handbook of Functional MRI Data Analysis
Kindle Edition
Check

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Effort
4 weeks of study, 2-4 hours/week
Level
Intermediate
Via
Coursera
Institution
Johns Hopkins University
Instructors
Ciprian M. Crainiceanu
Dr. Elizabeth Sweeney
John Muschelli III
Language
English
Transcripts
Español Français Português Deutsch Italiano 中文 العربية 한국어 日本語 हिंदी Nederlands Svenska Pусский Türkçe Polski Ελληνικά українська мова magyar nyelv Bahasa Indonesia ไทย қазақша اُردُو, فارسی বাংলা پښتو آذربایجان دیلی
This course belongs to a collection called Neuroscience and Neuroimaging. It's comprised of four courses:
  1. Principles of fMRI 2
  2. Introduction to Neurohacking In R (viewing)
  3. Fundamental Neuroscience for Neuroimaging
  4. Principles of fMRI 1
Traffic lights
Read about what's good
what should give you pause
and possible dealbreakers
Provides foundational skills in data manipulation, processing, and analysis for neuroimaging research
Covers essential neuroimaging techniques such as inhomogeneity correction, brain extraction, and image registration
Leverages the widely used R programming language and associated neuroimaging packages
Taught by experienced instructors with expertise in neuroimaging research
Applicable for both academic and industry settings where neuroimaging data analysis is required
May require additional prerequisites in programming and neuroimaging concepts for optimal learning experience
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