[SciPy-user] Subject: Re: Scientific Python publications
Sun Nov 4 10:52:59 CST 2007
It's even worse. If you design a new algorithm with results that cannot be
verified with SPM, you can't ublish anything (worse : the neurologists do
not want to publish results with your algorithms).
The fact that SPM is GPL is not relevent for me. What bothers me is that
there is a conflict of interest between the SPM team and the editorial board
of some journals et the fact that even you demonstrated that your algorithms
are correct, you can't publish something that SPM cannot coroborate (knowing
that SPM relies on some heavy hypothesis that are not even correct).
PS : I really hope nipy will go on growing and that people at my lab will
collaborate, at last, even if it is not for mainstream algorithms (SPMs,
2007/11/4, Matthew Brett <email@example.com>:
> > > In my field, the same problem arises with a Matlab toolbox, SPM. You
> > > can't write an article without using this toolbox, especially if you
> > > want to publish it in NeuroImage (the editor in chief is one of the
> > > writter of the toolbox).
> > This is really SAD:
> > you're doing medical research, investigating and describing some
> > physiological phenomena,
> > well I can assume they are interested what algorithm you used,
> > to verify your conclusions,
> > but it's absolutely absurd, they make it obligatory that you write your
> > manuscript with a pen of a certain brand !!
> Hmm - I'm in the same field, and trying to work out a way to fix this
> The problem is not as silly as it seems. Neuroimaging is moderately
> complex, and it's difficult for reviewers to understand what has been
> done if you have used a variety of software packages. The advantage
> of SPM, in this case, is that the code for the neuroimaging part is
> open source (GPL), it covers the whole range of processing (more or
> less), and it's fairly easy to extend. The disadvantage is that - you
> need matlab - and that matlab is so clunky as a programming language
> that it deals very badly with the increasing need for complexity,
> meaning it is harder and harder to develop in SPM as time goes by.
> Our thought was that the only way out of this was to develop a system
> that would allow you to call the core algorithms of SPM within python,
> and develop new ones that you could validate against SPM (and other
> tools) as the standard. But it's hard work getting that right,
> because our community is so fragmented.
> SciPy-user mailing list
French PhD student
Website : http://miles.developpez.com/
Blogs : http://matt.eifelle.com and http://blog.developpez.com/?blog=92
LinkedIn : http://www.linkedin.com/in/matthieubrucher
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