High Resolution Intracellular Recordings?

KP_PC k.p.collins at worldnet.att.net
Mon Sep 8 06:15:36 EST 2003


"yan king yin" <y.k.y at lycos.com> wrote in message
news:72de81ae.0309031548.39b66b2d at posting.google.com...
| Hi Everyone =)
|
| I'm trying to find intracellular recordings of the soma of
| in vivo neurons, with *temporal* resolutions in the sub-ms
| range (the finer the better). What I want to see is how the
| spatial and temporal integration actually take place in action.
| Any web page, paper etc...?
| [...]

The problem is 'difficult' only because it
is big - not because there's 'exotic mystery'
in there.

Its bigness stems from the fact that it's
fractal-like - as one peers into it, one soon
becomes aware that it goes on forever -
literally be-cause, at the level of the ionic
conductances, the dynamics are infinitely-
divisible.

So a necessary approach is to =begin=
with a modelling architecture that is
inherently factal-like commensurately-
scaleable.

Then add detail progressively, integrating
the proven experimental results, studying
all ramifications with respect to convergence
as the depth of detail increases.

This is doable because, at the 'level' of its
integration, any 'element' is an 'independent'
entity - that is, while the functionality of every
'element' does incorporate the activation of
everything that's happening around it, it
reacts to this "everything" in accord with its
own intrinsic functionality.

So the fractal-like problem becomes a
'simple' data-driven databasing with respect
to the functional properties of each 'element'
at the fractal-like depth that has currently
been achieved, with the overall goal of, simply,
increasing the fractal-like depth.

The "bigness" of the problem stems from the
fact that the fractal-like depth is infinite, extend-
ing from the 'level' of the macroscopic neural
architecture of the global system to the
infinitely-divisible ionic Couloumb fields which
comprise the ionic conductances.

The most-common mistake that most folks
make consists of looking at this or that micro-
scopic 'element' sans its context within the
'big picture' - which is why I've discussed
the problem as a data-driven databasing
problem. When the problem is approached
as a data-driven databasing problem, it's
OK to look at an 'element' because the pre-
viously-created database takes care of the
larger integration that is commonly 'forsaken'.

You've received much good discussion of
particulars from other psters. To their dis-
cussion, I'll add that neural glial functionality
must be incorporated.

Gotta run - strapped for 'time' these days.

ken [k. p. collins]





More information about the Neur-sci mailing list