X-Message-Number: 25993
Date: Sat, 9 Apr 2005 03:16:00 EDT
Subject: Re: CryoNet #25984 Uploading

From: Daniel Crevier <>

> - detailed modelling: that's Maxwell's equations for power lines, and other 
> kinds of differential equations for neurons
> - recoil in awe: that's the psychological reaction after you've done a bit 
> of detailed modelling
> - simplification: that's when you extract the regularities and modes of 

> behavior of the system that are relevant to the problem you're trying to solve
> - eureka!. That's when you put your simplifications together, and eventually 
> build a feasible simulation that reproduces the aspects of system behaviour 
> that are important to you. 
> From Yvan's descriptions, and from what I understand about current efforts 
> in neural modelling, we seem to be at the "recoil in awe" stage right now. 
> Hopefully this won't last too long.

I broadly agree. Think for example about the axon, between two node of 

Ranvier, there may be 20 channels, each best described by a 9 element Markov 
model ( 
sorry, I have not yet introduced this in my theoretical modeling toolbox). 

Suffice to say that this is very complex. There may be hundreds of such segments
in an axon. This model is necessary to get at the end the good electrical 
pulse shape of the action potential.

Now, why is this shape so ? Is it because the biochemical conduction produce 
that anyway or is there some information in this shape ? The experimental data 
tell us that a simple square pulse produce the same effect on the synapse. 
So, a digital data from a computer is as good as the monstruous computing done 
for minicking a true axon conduction.

On the dendrite side yet, each branching works as an integrator, far less 

simplification can be done and each one will degrade the message. The solution 
then to know how the message has been disturbed and correct it from time to 

time. To make the correction table,  the full computation must be done at least
one time.

Yvan Bozzonetti.

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