[Comp-neuro] Re: Attractors, variability and noise

james bower bower at uthscsa.edu
Fri Aug 22 00:49:33 CEST 2008


One thing that has always struck me about the difference between  
biology and physics, is that in physics department seminars, the  
resident Dons of the field  would stand up and walk out within several  
milliseconds of a speaker making a statement violating some well  
established physical principle (conservation law or something), while  
in biology, one finds oneself listening intently through most seminars  
to determine whether the story teller does or doesn't know what they  
are doing.  There are little signs (smiling gels, action potentials  
that don't overshoot, etc), but really one is often at sea.

So, there is clearly something different about the freedom to tell  
stories in both disciplines.

In biology, when you work on a new paper, the first thing you do is  
organize the figures (the story). In math you organize the equations.   
In biology the traces you pick for your figures are the best ones you  
can find (and photoshop can help) whereas physics and mathematics look  
for general solutions.

This is my problem with all for one and one for all -- somewhere,  
somehow, someway, neuroscience has to find a mechanism to better  
discriminate between efforts -- let alone force the development of  
some set of common definitions with which and on which to tell stories  
(and judge stories).  Otherwise, they are just stories and subject to  
all the politics, trends, fads, and social pressures that apply to all  
story tellers.  So a core part of this debate, I think, is how we  
advance the 'art' of storytelling in biology.

I would also be a little careful of the analogy to VISTA  :-)  -  
which, at least, is based on some formal system for coding its  
structure.  As far as I can tell, the only thing  predictable about  
vista, is that it isn't.


On Aug 21, 2008, at 1:51 PM, Walter Read wrote:

>   Just a couple notes in response to Jim's comment.
>> Obviously, the question of what we can and can't understand as
>> individuals, or groups of individuals is somewhere near the core of
>> this discussion.  Many would claim, as Brad does here, that of
>> necessity our descriptions of things (brains) can not exceed the
>> ability of humans to communicate what they understand.
>      First, the issue of "communicability" isn't the same as the  
> issue of "complexity". We
> constantly deal with systems that are too complex to allow any micro  
> description to reliably
> predict global behavior - the Roman Empire, crop forecasts, choosing  
> American Idol. For
> perhaps a more familiar example than Mirage jets, Windows XP ran to  
> about 40 million lines
> of code and Vista goes closer to 65 million. (I mentioned these  
> numbers in a class once and
> afterwards a student came up, apparently genuinely disturbed.  
> "Really?" "Yes." "Gee, then I
> guess Bill Gates *doesn't* read every line before software is  
> released!") But this doesn't mean
> we can't generally make policy or predictions based on our  
> collective, imperfect
> understandings. And any particular failure can usually be traced  
> back to a particular place.
>   Second, communicability is cultural and historical. At one time,  
> notions like gravity or
> unbounded space or limitations on the speed of light would have been  
> considered
> "paradoxical". We still refer metaphorically to "the fixed stars"  
> and "sunrise" but most people
> have a basic idea of the later ideas and can imagine and think about  
> a heliocentric world. Our
> ability to form new ways of thinking grows much more slowly than our  
> ability to generate
> data but it does grow, in response to the efforts of those who  
> explain the ideas or show their
> everyday usefulness, those who might be called storytellers. (Cf  
> Galileo's popular writings
> and John Donne's early poetry.)
>   The information systems people distinguish "data" and  
> "information". The data is
> fundamental but it has to get translated into news we can use.
> -Walt
> Walt Read
> Computer Science, MS ST 109
> CSU, Fresno
> Fresno, CA 93740
> Email: read at csufresno.edu
> Tel: 559 278 4307
>        559 278 4373 (dept)
> Fax: 559 278 4197
> http://www.csufresno.edu/csci/


Dr. James M. Bower Ph.D.

Professor of Computational Neuroscience

Research Imaging Center
University of Texas Health Science Center -
-  San Antonio
8403 Floyd Curl Drive
San Antonio Texas  78284-6240

Main Number:  210- 567-8100
Fax: 210 567-8152
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