Stathis: (from reply to Brent):
"I return to my question about what would happen if there were a
discontinuity in a sequence of states,..."
There IS discontinuity if the state "transits'(?) from s1 to s2.
Do you have any idea how one can observe a changed state by only continuous
transitions? Where do you pick the limit to call it the 'next' state? Isn't
such 'arbitrary'? (I have similar questions with astronomy - what I never
studied - how do they calculate the planatary movement markers (year?) into
(fractional?) seconds? but they do).
Same question to Bruno's 'integers: there is no transition between 2 and 3.
Even putting fractals in between only extends the question to smaller scale.
"Infinite small" I would not consider at our present level of cognition.
In your reply to me:
I find the rat-related IBM publication wanting:
"...Each of its microchips has been programmed to act just like a real
neuron in a real brain...."
How much we know about a 'real neuron' and its function is a matter of the
present level of R&D. We know more than a decade ago and less than a decade
hence. And the 'rat' discloses only its movements - evaluated and
understood(?) at the complexity of the human brain. Would you draw valid
conclusions on - say - personality by a silent film of only the movements of
a person - even at matching complexity?
I may write some distracting stories to follow 'movements'.
A rat doesn't communicate with researcher. Rat-shrink?
I wouldn't use Terry Seynowski's critical word that the brain is too
'mystrerious': it is too *complex* and poorly followable by our present
level of our 2009 cognitive inventory. We can know just 'that' much and most
likely there is much 'more' to it. (my 'enrichment' remark of past and
future knowledge).
Markram's work is glorious. That's the way we can proceed in widening our
knowledge 10,000 'neurons' is a good start.
But their fundamental tenet:
"*Every brain is made* of the same basic parts...." -
means a restriction to our ongoing physical/physiological observational
capabilities which have shown incredible enlargement in the past (still
within the 'physical world' figment). Frequencies, methods, evaluations are
all limited.
I keep it open that penetrating the Hard Problem we may find new phenomena
unassignable to our present knowledge of the known tissue and physics.
Nobody has diversified amp or MRI data to distinguish whether a blood-surge
refers to a political opinion, love, boredom, financial expectation, or
whatever, in a mentally-topical distinction.
Thanks for that brilliant article. It says honestly:
"When listening to Markram speculate, it's easy to forget that the Blue
Brain simulation is still just a single circuit, confined within a silent
supercomputer. The machine is not yet alive. "
Neuroscience is heroic and 'explains' lots of tenets into open "somehow'-s.
Their assumptions are within our conventional sciences. Digitally computed.
Computing analogue ideational meanings?

I wish to look further - especially on this list.

On Wed, Jan 14, 2009 at 4:40 AM, Stathis Papaioannou <>wrote:

> 2009/1/14 John Mikes <>:
> > Stathis,
> >
> > common sense, not always applicable to math-related topics
> > is startled before a task on a REGULAR contraption-type Turing machine
> > (binary, electrically driven finite hardware etc.) can emulate ALL the
> > potentials of 11+billion neurons in unrestricted groupings and unlimited
> > connectivities as to the complexity of all the codes/details
> > (un!)imaginable.
> > (Maybe if you change to Bruno's infinite Loebian vs. Turing machine...??
> I
> > doubt if you can do that, since there are different brains (eg for
> genetical
> > etc. reasons) and I cannot figure so many (although limited number)
> > variables in the 'unrestricted' (all encompassing?) Loebian machines.)
It is possible to calculate how much computing power it would take to
> simulate a brain at a particular level. For simulations at the
> cellular level, there is for example this work by IBM researchers
> simulating a rat neocortical column:
> It's still a long way from simulating an entire brain and observing
> ratlike behaviour, but it does show that computational neuroscience is
> now beyond the philosopher's thought experiment stage.
> --
>  Stathis Papaioannou
> >

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