[Neuroimaging] Contributing

Ruy Valle ruyvalle at yahoo.ca
Wed Sep 14 13:11:23 EDT 2016

Hi Matthew,

Thank you for your response. I guess if there is enough of an incentive for me to translate the analyses I am working on to Nipy, then yes that seems like a natural path to follow. I am uncertain if this will be the case however. Regardless, I will contribute what I can.


> On Sep 14, 2016, at 12:24 PM, Matthew Brett <matthew.brett at gmail.com> wrote:
> Hi,
> On Tue, Sep 13, 2016 at 9:40 AM, Ruy Valle via Neuroimaging
> <neuroimaging at python.org <mailto:neuroimaging at python.org>> wrote:
>> Hi Ariel,
>> Thank you for your response. I am doing fMRI analysis, mostly task-based up until now but I will be getting into resting-state analysis sooner or later. I will probably also start looking at EEG and TMS, but I am not sure how relevant that is for Nipy. I learned to use AFNI at their bootcamp and FSL through my supervisor at work. I recently (yesterday) started working on a project of mine through which I am hoping to clarify what the effect of including motion parameters (estimates of head motion calculated during volume registration/motion correction) in regression models used in fMRI software is. I would say that I have a fair amount of experience in Java but have not used it much as of late, am comfortable enough with Python, R, and MATLAB to really dive into them as much as needed, and have been learning C and Go recently.
>> A colleague of mine introduced me to Nipy/Nipype around 5 months ago and I really liked the idea of it. I was still in college at the time and graduated this last semester from McGill University. I have been reading a book on modeling techniques and learning about statistics more generally, so contributing on that side could be nice. I also enjoy learning about algorithms (I implemented a heap sort algorithm in C a few weeks ago). To be honest, I find I still lack enough experience (both in software and in life in general) to pinpoint my preferences, and am open to trying new things, hopefully discovering what most appeals to me, increasing my skills, and making useful contributions along the way.
> I find that the most productive way, is to start doing some analysis
> I'm interested in, and then look to see how to do it in nipy (or dipy,
> nibabel or nipype etc).  That gets me reading the code.   I start to
> use the code, and that points out bugs, or documentation that could be
> improved, or features I'd like.  That makes me look at the code and
> maybe ask for help if it's hard to follow.  Then I make some edits and
> put up a work-in-progress pull request.
> Is that a practical path for you?
> Cheers,
> Matthew

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