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

[james bower]

>
> As I understand the  other end of the spectrum, we construct  
> increasingly realistic models and end up with a simulated brain  
> without a real understanding of how it works, which makes no sense  
> to me.  Understanding is what we're after, and that understanding  
> can only reside in the brains of the population of scientists, not  
> in their models.
>
> I suspect that I have created a straw man here, but I'm curious to  
> what extent I've abused your position.

Brad,

Haven't abused at all -- with one big exception -- realistic models  
are more likely to tell you how things work, than are models in which  
'how things work' is assumed.  In our experience, realistic modeling  
has consistently and steadfastly told us things that we didn't know  
before - problem is, those things fly in the face of many of the  
current 'theories" operating in the parts of the brain I study, making  
the publication of papers, getting grants, etc, much more difficult.

BTW, almost every time, the models have also made it clear that I was  
wrong in how I was thinking about the system:

The most recent example for those that are interested:

Santamaria, F., Tripp, P., and Bower, J.M. 2007  Feed-forward  
inhibition controls the spread of granule cell induced Purkinje cell  
activity in the cerebellar cortex. J. Neurophysiol. 97: 248-263.

Despite complaints by the reviewers, both the introduction the first  
part of the results section of this paper and the discussion, make it  
clear that the mechanism I had thought for 20 years was responsible  
for a particular physiological property of this circuit, was wrong.   
One of the paper's reviewers, complaining about the length of the  
paper, requested that we cut that part out, and just state what we now  
know to be true - I responded that I have no more certainty that what  
we now think is the case is true, than I did before -- it is just a  
new platform to move forward.

Why is this interesting in the larger sense?  (sorry to go into the  
details, but in biology the details matter). Because our current  
models combined with our physiological results continue to suggest  
that the 150,000 excitatory parallel fiber inputs to cerebellar  
Purkinje cells actually have no direct influence on the output of the  
neuron.  What's wrong with that?  Every top down model of cerebellar  
function assumes they do -- How come they continue to believe this?   
Because all the models that manifest these top down "ideas" ,  
implement Purkinje cells as integrate and fire "pattern recognizers".   
It would be  hard to imagine a cell in the nervous system less likely  
to be an IF neuron than the Purkinje cell.

Is it potentially significant for thinking about the rest of the brain  
that some, perhaps many, possibly even MOST of the excitatory  
connections on neurons may not have anything to do with their direct  
output? -- seems to me it could be.

How many abstract models of brain function assume excitatory synapses  
sum to produce outputs? -- lots, even  most.  How many neural network  
models are built on this assumption?  almost all.

Is the right approach then to build models that are so abstract that  
these details don't matter?  How can the nervous system tell you you  
are wrong if you do?

Do MOST cerebellar physiologists, modelers, theorists, think this view  
of cerebellar Purkinje cells is crazy? -- yes --  Why? they have too  
much invested in other ideas.

Is the Purkinje cell model available for others to examine, test,  
include in their models, explore, refute, etc?  you bet -- How many  
have?

Glory days - this is starting to happen.  :-)

In fact, it fills me with a great sense of hope that the Purkinje cell  
model is now being used in multiple laboratories around the world,  
MOST not connected in any way to my laboratory, as a basis for further  
study.  AND -- importantly, not all of those modelers reach the same  
conclusions we do -- BUT, equally importantly, we now have a  
quantiative substrate on which to discuss, argue and resolve.  THAT is  
progress in my view, WHATEVER the outcome.  Most of the time in  
neuroscience (as manifest abudendently in this ongoing conversation)  
we can't even agree on the definitions (a convenient way to avoid  
conflict -- and at the same time progress).

With the Purkinje cell, we can argue about K channel conductances  
(which were way off in our initial models), and other things that can  
actually be experimentally tested.

In fact,  I am extremely proud that the PC model has even been  
converted to Neuron for use in other laboratories, including several  
who don't believe what I believe at all.

This is one of the first times in history that a complex realistic  
model has spread across labs and opinions -- and speaks very well for  
the future - this is what the GENESIS project was about to begin with  
-- and now, more than 20 years later, it is starting to happen, not  
only with GENESIS but through Neuro-DB built by Michael Hines and the  
Neuron group at Yale as well.

There is hope


Jim



>
>
> -Brad
>
>
>
>




==================================

Dr. James M. Bower Ph.D.

Professor of Computational Neuroscience

Research Imaging Center
University of Texas Health Science Center -
-  San Antonio
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San Antonio Texas  78284-6240

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