[Neuroimaging] Contributing

Ariel Rokem arokem at gmail.com
Wed Sep 14 14:22:29 EDT 2016

Hi Ruy,

On Wed, Sep 14, 2016 at 10:11 AM, Ruy Valle via Neuroimaging <
neuroimaging at python.org> wrote:

> 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.
One way to go about this is to start by making your analysis code publicly
available on Github, and then see whether it fits in with some of the other
work that people are doing. It would already be useful to people, even if
it isn't in one of the already existing packages.



> Cheers,
> Ruy
> 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> 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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