On Tue, 24 Feb 2004 10:29:37 GMT, "k p Collins"
<kpaulc@[----------]earthlink.net> wrote:
} Since you're posting from a Yale Medical School
} ID, I =presume= that it =may= be the case that
} you're in Neuroscience at Yale, so, I've Obligation
} with respect to your Education in Neuroscience(?)
If you feel so. I expect only the obligation of someone approaching
science in the proper manner.
} Yes, as I've stated before, in our discourse [and
} repeatedly, over the course of the 'years', here in b.n,
} unless I RETRACT or CLARIFY this or that that
} I've posted, I stand on everything I've ever posted.
}
} The nervous system is a neural Topology that is
} dynamically-configured.
I'm leaving your entire response, as well as the quoted material
intact here so that you can show me, where you see anything in the
question related to neuroscience.
There isn't anything in what he said that refers to anything in the
nervous system. For all we know he could be working with earthquake
data, or sunspot cycles, or an artificially constructed time series
made out of pseudorandom numbers. He was talking about an arbitrary
time series.
Perhaps you're correct and taking cerebellar topography into account
would improve things.
Would you care to share with us how to calculate a correlation
dimension from a time series, and how to improve upon that by taking
into account the topology of the cerelellum? Care to name any software
you might have or algorithms you'd use for doing so?
You can't, Ken. I doubt you could define a correlation dimension, much
less calculate one. I'll be more than happy to eat my words if you'd
show me I'm wrong.
Now, I can and do use that calculation in neuroscience. When you admit
you can't, I'll be glad to tell you some free software that can do it
for you.
I have never, nor would I ever, dream of messing up a cD calculation
by inserting such irrelevant data as "topology of the cerebellum". The
statement does is not even logical. It is like comparing apples and
gravitational lensing.
The cD of a time series does not require anything else. It is a well
known straight forward nonlinear calculation. To state that
calculating it in a certain subject requires additional information
that it most certainly does not in other subjects or as an arbitrary
example is to imply that mathematics acts differently according to the
subject matter, and it DOES NOT.
Face it, Ken. You shot your mouth off about something you know nothing
about, and happened to do so while someone who does understand the
subject, and has no fear of calling out those who run counter to clear
and unobstructed truth, and are going to have to admit it. We both
know you knew nothing of what the question was about, and that you
answered with wrong information.
I will never stand by and allow you to do that. People getting right
answers to their questions is too important for me to stand by and
watch you mess up. I will see to it that you stand on what you posted
and take responsibility for same, especially when the answer does
harm, and no good.
Expect this to continue every time you do the same in the future.
There's only one way to prevent it then.
} It's active 'circuitry' varies as a function of the 'mo-
} mentary' "supersystem configuration" [AoK, Ap5]
} that has been converged-upon via "TD E/I-mini-
} mization" [See AoK].
}
} So, to comprehend what's going-on =anywhere=
} within the nervous system, one must comprehend
} the neural Topology of the 'momentary' "super-
} system configuration" that has been converged-upon.
}
} This simply cannot be done via a method that re-
} sorts, exclusively, to 'time'-series analysis witnin
} any 'isolated' functional sub-system [e.g. the cere-
} bellum], be-cause the 'momentary' neural Topology
} is configured as a function of =globally= integrated
} TD E/I-minimization.
}
} If one looks solely at this or that sub-system [e.g.
} the cerebellum], one sees exactly nothing that
} addresses the globally-integrated neural Topology
} in a way that's sufficient to constitute anything other
} than a "pretty picture".
}
} Ever when one does a 'time'-series with respect to
} the globally-integrated neural Topology, what one
} is able to see in that 'time' =series= is insufficient,
} be-cause of the nervous system's massive parallel-
} ism. Looking at 'sequences' discloses exactly-no-
} thing.
}
} One must build-up the picture of the dynamics that
} are occurring within the nervous system's massive-
} parallelism. and the =only= way in which this can
} be accomplished is by sorting-out, and invoking,
} the neural Topology.
}
} Which is what I said when I responded to the OP.
}
} What I was doing, in that initial reply, was eliciting
} interest, with respect to a much-larger discussion.
}
} I do this, routinely, because I've Learned that it does
} no good to just discuss Larger concepts if there's no
} one who's accumulated sufficient "biological mass"
} through prior study - if that's the case, then the
} Larger discussion tends to 'pass-right-through', its
} stuff remaining 'undetected'.
}
} But, before anyone else had a chance to express-
} interest, you started 'bashing' my Person, which
} sent everything to Waste.
}
} And the Work that I'd've, otherwise accomplished,
} here in b.n, was left Undone, and my ability to Work,
} here in b.n, has, at this 'point', still not recovered
} from your 'shunting' it off into 'nothingness', =except=
} for one thing - I've been Working to use our 'inter-
} action' as an in-process example of the way that
} 'blindly'-automated TD E/I-minimization wreaks its
} havoc within Human interactive dynamics.
}
} The costs are always great, and, sometimes, they
} stretch all the way out to Infinity, encompassing
} all of Humanity.
}
} The 'present' case is such an Infinite case.
}
} I Forgive you, but I can only stand on what I've
} posted it is Truth - while 'mourning' that which has
} been Lost - that which could have Been.
}
} "It's a slip and not a fall." {Abraham Lincoln]
}
} As my Friend, K. W. Ford always said, "You got
} to go through what you been through to get to
} where you're goin'".
}
} I've given you Opportunity to Learn.
}
} What you do with it is up-to-you.
}
} K. P. Collins
}
} "Doktor DynaSoar" <targeting at OMCL.mil> wrote in message
} news:is0l30182sgrpuruft07ijlrdnej40u9v8 at 4ax.com...
} > On Mon, 23 Feb 2004 08:26:01 GMT, "k p Collins"
} > <kpaulc@[----------]earthlink.net> wrote:
} >
} > } I stand on what =I've= posted.
} >
} > All of it?
} >
} > "You're missing some crucial data that cross-correlates
} > your 'time' series to the cerebellar topology.
} >
} > The cerebellum is a topographically-mapped subsystem.
} >
} > Any analysis must preserve, and incorporate, that mapping
} > if the correlations are to be meaningful."
} >
} >
} >
} > From: "k p Collins" <kpaulc@[----------]earthlink.net>
} > Newsgroups:
} > sci.nonlinear,sci.bio.technology,sci.math,bionet.neuroscience,sci.fractals
} > References: <235b9607.0401210500.3ebedda5 at posting.google.com>
} > Subject: Re: Practical problems with correlation dimension
} > Lines: 68
} > Organization: sufficient
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} > Message-ID: <AhvPb.17594$q4.2672 at newsread3.news.atl.earthlink.net>
} > Date: Wed, 21 Jan 2004 13:38:40 GMT
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} > (Wed, 21 Jan 2004 05:38:40 PST)
} > NNTP-Posting-Date: Wed, 21 Jan 2004 05:38:40 PST
} >
} >
} > "Karl" <karlknoblich at yahoo.de> wrote in message
} > news:235b9607.0401210500.3ebedda5 at posting.google.com...
} > > Hallo!
} > >
} > > I want to calculate the correlation dimension of a time serie.
} > >
} > > What I have done
} > > I calculated the correlation integral C(r) (number of point having a
} > > distance smaller than r) for different embedding dimensions. Taking
} > > the slopes of the curve of log C(r) against log r for the different
} > > embedding dimensions and plotting them against the embedding dimension
} > > should result in a limes of the slopes: the correlation dimension.
} > >
} > > My problem
} > > Which slope shall I take?
} > >
} > > In examples I saw in text books there is a nice limit of the slopes
} > > with higher embedding dimensions. In my data I do not know which slope
} > > I should take because the slope of the curve varies. If I take the
} > > slope at a certain value of log r I can not get a limes.
} > >
} > > My curves (log C(r) against log r) can be seen in
} > > http://karlknoblich.4t.com/korrdim.jpg
} > >
} > >
} > > What to do? Does anybody knows such data and how to handle it?
} > >
} > > Hope somebody can help!
} > >
} > > Karl
} >
} > What I will say has not yet been accepted by others,
} > so keep that in mind as you consider it.
} >
} > You're missing some crucial data that cross-correlates
} > your 'time' series to the cerebellar topology.
} >
} > The cerebellum is a topographically-mapped subsystem.
} >
} > Any analysis must preserve, and incorporate, that mapping
} > if the correlations are to be meaningful.
} >
} > And, then, to continue, one has to follow this mapping into
} > the rest of the brain.
} >
} > It's a =big= problem, but the mapping is mapped :-] through
} > the efforts of Neuroscientists, and all one has to do is 'grind'
} > through it.
} >
} > There a couple of other things that make your analysis Difficult.
} >
} > One is that the data is virtually always, itself, a transformation.
} >
} > The other is that the activation that occurs within the cerebellum
} > is extremely-dynamic, with a =lot= of different inputs converging
} > and 'sliding' with respect to each other. There is such 'sliding'
} > stuff with respect to every joint in the skelleton. [These enter
} > into the way that the nervous system maintains it's 'awareness'
} > of the body's orientation in 3-D space [climbing fibers from
} > the inferior olive].] And this is only one set of such 'sliding-field'
} > stuff that occurs within the cerebellum. There are hundreds
} > [perhaps thousands] more.
} >
} > So your analysis is Hard.
} >
} >
}