Connectionists: Best practices in model publication

[Brad Wyble]

Thanks for your input John, I appreciate it extremely.  One of the points
that I think is perhaps most important to improve on in our field is the
scope of the predictions.  In physics, predictions seem to occur on a much
grander scale, and very inspiring, and this itself engenders respect for
the theoretical work.

In neuroscience, the predictions are expected to be easily testable, which
leads necessarily to predictions that are smaller in scope, and testable
with technology that is already at hand.

-Brad



On Wed, Jan 29, 2014 at 5:33 PM, John Collins <collins at phys.psu.edu> wrote:

> As a physics colleague of Brad's, I'll take his hint to give a perspective
> on his questions.  Of course, current practice at one period in one area of
> science may be totally inappropriate in another situation.  I'll refer
> primarily to elementary particle physics.
>
> Some differences between what Brad describes and what I see in physics
> are:  1. In physics, theorists are notably self-consciously interested in
> ideas that are general rather than just the modeling of a particular
> phenomenon.  Good ideas can relate many experimental situations, and the
> predictivity of a theoretical idea may greatly exceed the initial
> expectations of its author.  Some of these (e.g., the Standard "Model") are
> amazingly successful. 2. Both theory and experiment are so difficult that
> specialization is inevitable.  3. Some of the time scales for making
> experimental measurements are long: well over a decade.  4. In many modern
> physics theories, a lot hangs on self-consistency of the theoretical
> framework.  Given an initial idea (induced from data) much work is
> sometimes needed to convert it to an implementable theory or method.   This
> can proceed almost autonomously from day-to-day contact with real data.
>  (String theory is a well-known extreme example of this.)
>
> (N.B. Interesting gaps can remain in well-established theoretical work and
> can be unperceived by many practitioners, as Randy found.)
>
> Another tendency is for theorists to provide software for simulations
> rather than simply computing predictions.  Then experimentalists apply
> these to make theoretical predictions to compare with their own actual
> data.  This is in addition to the simulations the experimental groups
> themselves construct to model their complicated detectors.  For a recent
> example, see the article at http://arxiv.org/abs/1312.5353, and search in
> the pdf file for "simulation".  (It's a long paper, I'm afraid.)
>
> John Collins
>
>
>
>
> On 01/28/2014 08:25 AM, Brad Wyble wrote:
>
>> Thanks Randal, that's a great suggestion.  I'll ask my colleagues in
>> physics for their perspective as well.
>>
>> -Brad
>>
>>
>> On Mon, Jan 27, 2014 at 11:54 PM, Randal Koene <randal.a.koene at gmail.com
>> <mailto:randal.a.koene at gmail.com>> wrote:
>>
>>     Hi Brad,
>>     This reminds me of theoretical physics, where proposed models are
>>     expounded in papers, often without the ability to immediately carry
>>     out empirical tests of all the predictions. Subsequently,
>>     experiments are often designed to compare and contrast different
>> models.
>>     Perhaps a way to advance this is indeed to make the analogy with
>>     physics?
>>
>
>


-- 
Brad Wyble
Assistant Professor
Psychology Department
Penn State University

http://wyblelab.com
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