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Opiniones y comentarios de aprendices correspondientes a Principles of fMRI 1 por parte de Universidad Johns Hopkins

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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:

Principales reseñas


8 de ene. de 2023

Taken in concert, the lectures and the reading are thorough if complex. However, this is a complex topic. Probably should be listed as an intermediate course at least, but a very good introduction.


29 de ago. de 2020

It was a wonderful beginning to a topic details of which were unknown to me. Thank you to both the instructors for making the videos crisp, informative and understandable. Thank you very much.

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126 - 150 de 154 revisiones para Principles of fMRI 1

por Jérémy W

13 de mar. de 2017

It goes a bit too much into the details sometimes. Personal researches are sometimes required to understand what is explained.

por Asli E

23 de dic. de 2019

I wish this course had a bit more of a practical reasoning that explains us the concrete steps to take when analysing data

por Daniel G

21 de mar. de 2018

Solid introductory course on fMRI, but some kind of interactive assignments and discussions might be useful.

por Derrick L H

20 de ene. de 2022

A concise introduction to the statistical procedures used to process fMRI data and make causal inferences.

por Diane A F C F

18 de sep. de 2021

good information on the slides, but the instructors only reed the slides, not any additional information.

por Eduard V

14 de oct. de 2018

it does not incorporate a lot fo background information and the information is too succinct

por Nicolas D D

15 de abr. de 2017

It was a great course.However I expect more discussion in foro and the proffesors opinion

por wang l

25 de dic. de 2018

need some fundamental knowledge in stats and then you will get more from this course

por Xaver F

26 de mar. de 2020

High-quality information brought to the point. Instructors are a little stiff.

por Veronik S

26 de sep. de 2019

A basic understanding is necessary, sometimes it is complicated to understand.

por Jerry M

2 de may. de 2018

The phrasing of questions and answers in the quizzes are sometimes awkward.

por Rodrigo F G

5 de may. de 2017

Great course! Though a bit of more examples through cases would be great.

por Elvina G

30 de abr. de 2020

Very good and interesting course, although misses practical exercises.

por Zikou L

27 de oct. de 2020

Maybe more examples to help understand and to remember the terms.

por JOEL B

13 de may. de 2020

Thank you sir for sharing your valuable knowledge with us ...

por Tiago A

18 de sep. de 2017

Very good material but questions not answered in the forums

por Allwyn .

2 de sep. de 2017

Contents were very good and useful!

por Ying-Qiu Z

14 de feb. de 2016

can add some detail, i.e. proofs

por José d J d L S H

14 de ago. de 2020

Encantado de seguir aprendiendo

por Kanika B

6 de mar. de 2016

Terrific learning experience!

por Diego S R

15 de nov. de 2017


por �ADITI P

22 de ago. de 2020


por Gabriela M F

8 de abr. de 2018





por Vatsal P

8 de jun. de 2022

The course is a good theoritical introduction to the concept of fMRI analysis. However, there is a lot of room for upgrading its content. I have the following suggestions:

1. Many times I felt that the course assumed that the readers has advance knowledge with respect to mathematical notations and statistical notations.

2. The most anoying part was that it was all theory with very little glimpse of how to conduct those analysis on any of the available software packages.

por Laine D

2 de jul. de 2017

Very stats based course if that is your focus. Could use some more real world examples in a few places. I would have liked more clinical application and physiology but perhaps that is included in part 2 of the course.