Nonlinear Dynamics

Bifurcation theory, dynamical diseases

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Latest Activity: Oct 31, 2013

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"Dynamical Neuroscience" wiki entry 1 Reply

Started by Zao Man. Last reply by Zao Man Jul 28, 2010.

Killer waves of depolarization 9 Replies

Started by Markus A. Dahlem. Last reply by Zao Man Jul 22, 2010.

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Comment by Markus A. Dahlem on August 6, 2009 at 5:22pm
In principal I can agree to Ruben.

I would say CN and mathematical modeling are different approaches
but non is superior to the other. I like both types of work, mathematical
modeling is sometimes for me more satisfying because you really have
the feeling of having gained deep understanding, in particular if you get
analytical results, while CN can bring more concrete knowledge as this is more bottom up (or more detailed, realistic, ....). And programming can be fun, too.
Comment by Ruben A. Tikidji-Hamburyan on August 5, 2009 at 5:59am
First of all, sorry for my English. The languages (including my native and excepting any computer one) are not my strong point.

I think there is not battle-line between computational neuroscience(CNS) and mathematical modeling. My colleagues at the technical department of our university try to model the human consciousness via multiciphered logic, but I prefer more detailed approaches. In any case, we formalize something in Nature by mathematical equations, and it does not matter what the object is: ion channel or mind. The method is idem and the question is “which scale would be better?”.

In my honest opinion, the detailed modeling may bring more new knowledge then pure theoretical one. I believe that CNS is a principal new way of science! First time we have unique situation then a complexity of studied object equals to researcher's complexity. We try to study brain by means of our brains. Therefore we might analyze the nerve tissue, but we can not synthesize all these data to new knowledge, there is only one way: to synthesize these data out of our brain. So CNS is based on the simple idea which is clearly formalized by Bert Sakmann: “I have all this data - cell types, firing properties, connectivity, dendritic excitability, synaptic dynamics, but I don't understand it. I need to model it”
Comment by Markus A. Dahlem on July 29, 2009 at 7:52am
I recently watched an interview with Jack Cowan, which summarizes quite
well the principal idea I have in mind for a group "nonlinear dynamics":

The full interview can be seen here:

Being asked: "Do you have a simple explanation, something your
mother could understand, to sort of explain what you’ve been doing
these past 40 years?" Prof. Cowan answered:

"Well I’ve just been trying to apply the methods of mathematical
physics to thinking about how the brain works. By that I mean that
there is a way in which physicists approach the world, theoretical
physicists, that I think really, really works and is really
interesting. They don’t try to put in every detail of what the
phenomenon is like. They, if they have good taste, they select only
those details that are really important for the questions they want to
answer. And they construct what are sometimes called toy models, which
aren’t facing reality, to quote the title of a book by a friend of
mine, Sir John Eccles, but they abstract from reality just what is
needed to understand something. And I think that’s what I’ve been
trying to do with respect to brain mechanisms: try to make toy models
that contain enough details to answer questions about and give you
ways to think about what’s going on in the brain. It’s not, I mean,
it’s not something that’s commonly done. A lot of the time people do
computational neuroscience where they put in a lot of details and make
simulations and study what goes on. I don’t do that. I tend to put in
as few details as possible and say things that are interesting with
few details rather than put in a lot of details."

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