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Introduction to Neurohacking In R

Introduction to Neurohacking In R

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8.6/10 (Our Score)
Product is rated as #19 in category R

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).

Instructor Details

Dr. Elizabeth Sweeney earned her PhD from the Biostatistics department at the Johns Hopkins Bloomberg School of Public Health, under the supervision of Dr. Ciprian Crainiceanu at Johns Hopkins and Dr. Russell Shinohara at the University of Pennsylvania. Elizabeth’s PhD research has made contributions to the improved analysis of neuroimaging data, as evidenced by numerous publications, presentations, and patents. Elizabeth’s interest in this area began with a traineeship at the Nation Institute of Neurological Disease and Stroke, where she did research in Dr. Daniel Reich’s lab on image analysis in multiple sclerosis. Elizabeth is passionate about both research and teaching. Elizabeth has co-taught a number of tutorials and courses on neuroimage data analysis. She also taught and introductory biostatistics course to masters of public health students at the American University of Armenia. Elizabeth now works on imaging in Alzheimer's disease at Rice University as a Rice Academy Postdoctoral Fellow. With mentors Dr. Genevera Allen of Rice Statistics and Dr. Joshua Shulman of the Baylor College of Medicine Neurology, Elizabeth is working to develop neuroimaging, epidemiological, and genetic biomarkers in Alzheimer's disease.

Specification: Introduction to Neurohacking In R

Duration

12 hours

Year

2016

Level

Intermediate

Certificate

Yes

Quizzes

Yes

36 reviews for Introduction to Neurohacking In R

4.4 out of 5
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  1. Ana–Maria N S

    This course offers a comprehensive description of all the steps required for the analysis of brain images. The notes are clear, concise, and contain a lot of helpful information about reading medical images, pre–processing them, and visualizing them. I’m a statistics researcher, and had very limited prior experience on this topic; but feel that this course has helped me tremendously to acquire the knowledge necessary to dive into research in this area, in a very short time. However, the benefits of taking this class go beyond this. Specifically, I was thrilled to be able to apply the techniques described here to read and visualize in R, medical images (MRI) concerning a patient–friend diagnosed with brain tumor, obtained directly from the doctor’s office !!! And this, I thought, was amazing!

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  2. Spyridon S

    An excellent introduction to neuroimaging analysis! Tank you.

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  3. Fernando M

    Very good as introduction to this area of implementation , It will be very interesting to create another course with more advanced topics.

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  4. mohammed o

    Really nice!

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  5. JM S

    It would have been better if there were practical exercises, nevertheless it was very comprehensive for basic procedures of fMRI analysis.

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  6. Brandy R

    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.

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  7. Navchetan A

    Good course for the basics of neurohacking.

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  8. Malte G

    Really good introduction.

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  9. Aman M

    All the lecture were thorough and good.

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  10. Freeman

    Wonderful course. I have mastered much about neurohacking using R programming, and learned about the preprocess step in neuroimaging analysis.

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  11. Chandan V

    Great course….medical imaging techniques at its best 🙂

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  12. salvador g d l

    It was a really good course, thank you!

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  13. Anna N

    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!

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  14. Lara P

    Very comprehensive step–by–step introduction to imaging analyses using R. Also includes helpful information on the nature of files and processes. I am not sure that I will do my imaging analyses using R but still found this to be a very useful introduction to the topic.

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  15. KJ B

    Very basic, could be clearer.

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  16. Srihari S

    Perhaps links to some materials regarding explanation of the data could be provided.

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  17. Ankit S

    I am really appreciate this course. Its good to have a structured course on these complex topics.

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  18. Tiago A

    Nice contents but: questions not being answered in the forums. Online content from github (where in fact are the scripts and data) is somewhat confusing

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  19. Miriam M

    fxhfg

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  20. Jonathan G

    this course was misleading and boring as hell! You’re supposed to learn the function of an MRI and what diseases to look for that would’ve been a more relevant course. It just talked about different computer systems and how an MRI functions.

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  21. ANSHAY A

    Should have more practical work

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  22. Brion J

    Student presenters are not as good as professors.

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  23. Mehdi N T

    Great concise walk–through of neuro–imaging techniques. Low quality audio and a lot of background noise though.

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  24. Al–Rashid J

    Great course. Learned quite a lot from the course. Only problem was the difficulty at first with the software and libraries stubbornly refusing to get setup. But, after realizing there was a VM provided with all intended software installed, everything was smooth sailing from there.

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  25. Jinyi K

    Great intro class. Recommended.

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  26. Zaeem H

    I was expecting teaching but they are simply reading code from slides. Big let down.

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  27. Sim W K J

    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.

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  28. Fidel G

    It was a great experience going through the processes of ways of viewing, manipulating and extracting data from brain scan images. With few bumps on the way I keep focusing on the knowledge that I gain which I may apply into a future project of machine learn.

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  29. syed m a

    it would be great if can create a specialization for this course going in more depth like making your own dti films etc.

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  30. Dan S

    Thank you to the team for setting up this course! I learned a lot about manipulation of imaging data within R, which is something I previously executed at the command line within FSL. These formats will provide more reproducible code within my publications.

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  31. Lydia D H

    A nice introduction to neurohacking in R. I would recommend this course for beginners.

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  32. Alexander J

    thank you!

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  33. Hanem E

    A very useful and informative course. An organized, well prepared, and focused course. Thanks to the fabulous team. I learned a lot of stuff related to neuroimaging.

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  34. Sreenivasulu U

    This course was very useful for me to kick start working with brains and NeuroImaging this course gave me a deep insight into types of brain data that is available for use and also how to read them. Previously I had a fear of where to kick start now after completing this course I got an idea of how to work with brain data and do Neurohacking ;p

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  35. Belfin

    Thanks for the course. It was a nice course with good explanation. I enjoyed learning.

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  36. Aleksandr S

    Great course! Just please delete the 10 second introduction before each video. It makes the most horrible sound. Other than that, amazing course

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