Can anyone recommend a good Linux course? Like the Matlab for psychologists course in Matlab, ideally. And/or can anyone recommend a Linux book that is a good guide to using Linux for processing neuroimaging data (perhaps like the book Matlab for Behavioural Scientists). Thank you!
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@antonio.schettino might have thoughts? And perhaps @dbernt have any thoughts on at least Bonni’s first question?
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Am I understanding it correctly that you are going to run somebody’s neuroimaging processing code which is made to run on Linux but don’t know what to do or where to start? Can you provide a link to the thing you want to run?
Echoing @dbernt, could you please provide more details on the software you want to run? For example, you can find info on how to install FSL here. If you plan to use MNE, it should work seamlessly within Anaconda. There is also an interesting project called NeuroDebian, basically a Linux distribution including popular neuroimaging software by default. Perhaps you could install NeuroDebian on a virtual machine and see if you like it?
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Thank you both. I have used FSL before with no problems (as there are GUIs). It’s not that I want to use a particular script, it’s that I would like to be better at scripting (e.g. loops to do slightly more sophisticated things than simply re-naming files/directories, or querying the number of dicoms in a directory, which is basically the extent of my Linux scripting skills) and data management more generally in Linux. I went to an in+house Linux course, but it was aimed at too broad an audience, and didn’t cover what I want to learn - which, in a nutshell, is how to manage and process neuroimaging data more efficiently, by having greater knowledge of Linux, especially scripting.
A course like Antonia Hamilton’s excellent MATLAB for psychologists (http://www.antoniahamilton.com/matlab.html) and/or a book like David Rosenbaum’s MATLAB for behavioural scientists (https://books.google.co.uk/books/about/MATLAB_for_Behavioral_Scientists.html?id=FGtLP1ckp44C&printsec=frontcover&source=kp_read_button&redir_esc=y) is ideally what I’m looking for.
My apologies but I still don’t understand why you are looking for a Linux book. Based on what you wrote, you wish to learn “how to manage and process neuroimaging data more efficiently”, but this can be accomplished in MATLAB or python even if you have almost no knowledge of the operating system you are running. I am an electrophysiologist and use MATLAB to batch the preprocessing of my EEG data all the time, and this works great both in Windows and Linux.
I regularly share my MATLAB scripts on the OSF and gave a workshop at my former university about using MATLAB to analyze EEG data in batch (see here). I have also worked with colleagues who estimated the neural sources of EEG signal using SPM (I guess you are familiar with it). See scripts here and here.
Please feel free to browse these repositories, I hope you’ll find them useful!
Well, a good reason to use something else than MATLAB is that it’s proprietary. Open source alternatives (that apparently can be run on several OS, not only Linux):
http://www.openhealthnews.com/story/2016-08-01/3-open-source-alternatives-matlab
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Thank you
Thank you for this. I do use Matlab (in Linux or Windows) for a lot of data analysis, but for some things, because the data comes off the MRI scanners in my institute to Linux directories, it would be more convenient to manage the data using Linux scripts. I could do the directory moves etc. in Matlab, but some data processing would just be more efficient if I could do it straight from the Linux terminal rather than via Matlab.
For scripting-stuff-in-general on Linux use Python. It’s easy to learn, yet both convenient and powerful. And useful on other operating systems too. https://www.python.org/about/gettingstarted/
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If you want to have an overview of one of the most popular Linux distros you could start from A Practical Guide to Ubuntu Linux by Mark Sobell.
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Hah, and that I believe, might finally have been the type of response that @crawfordbk1 actually was looking for. 
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That’s brilliant, thank you