[MURG] homeostating despite rapid flux

Thu Jun 17 05:29:43 EST 2004

http://www.sci-con.org/articles/20040601.html

 [SCR 2004, June, No. 1]       Printer friendly version  Get Acrobat Reader

Do you know the half-life of a microtubule, the protein filaments that form
the internal scaffolding a cell? Just ten minutes. That's an average of ten
minutes between assembly and destruction.

Now the brain is supposed to be some sort of computer. It is an intricate
network of some 1,000 trillion synaptic connections, each of these synapses
having been lovingly crafted by experience to have a particular shape, a
particular neurochemistry. It is of course the information represented at
these junctions that makes us who we are. But how the heck do these synapses
retain a stable identity when the chemistry of cells is almost on the boil,
with large molecules falling apart nearly as soon as they are made?

The issue of molecular turnover is starting to hit home in neuroscience,
especially now that the latest research techniques such as fluorescent
tagging are revealing a far more frantic pace of
activity than ever suspected. For instance, the actin filaments in dendrites
can need replacing within 40 seconds, making microtubules look like positive
greybeards (Star et al, 2002). A turnover time of five days for NMDA
receptors seemed pretty steep when it was reported a few years back. (Shimizu
et al, 2000). But recently Michael Ehlers at Duke University Medical Center
in Durham, North Carolina, reported that the entire post-synaptic density
(PSD) . the proteinpacked zone that powers synaptic activity - is replaced,
molecule for molecule, almost by the hour. Ehlers had expected the turnover
to take days and when he found no labelled protein on his first 24 hour
assay, he thought he must have mucked up the experiment (Ehlers 2003).

Myelin and RNA molecules seem to last months. And DNA is of course fairly
hardy, though it still needs continual repair. But on the kinds of figures
that are coming out now, it seems like the whole brain must get recycled
about every other month. And certainly everything points to the synapses as
being about the most dynamic part of the whole system.

Clearly the shape of the synapses IS somehow maintained despite the molecular
turmoil. But there is an issue here that demands some specific theory. The
stability of brain circuits cannot simply be taken for granted. Princeton
University's Joe Tsien - famous for making mice smarter by splicing in
slower-closing NMDA receptors - is one of a number of researchers pursuing
the idea that synaptic structure may be stabilized by pressure from both
above and below.

Many people know about the emerging "below" picture of how shifts in gene
expression patterns could be necessary to underpin neural learning. Put
simply, the genes remember what kind of state a junction ought to be in and
so keep rebuilding the same old structure. As a relative oasis of calm in the
thermodynamic bustle of a cell, the genes could anchor the homeostatic
network needed to allow a given synaptic pattern to persist. Of course, this
story is complicated by evidence that RNA actually in the dendrites may do
the same job. But it seems to be a "loops within loops" mechanism with
short-loop local feedback nested in longloop feedback between synapses and
genes (Lisman and Fallon, 1999).

But Tsien says that as well as this shape-maintaining pressure from within,
synapses may be just as dependent on pressures from without - the old
"jangling trace" hypothesis. Back in the early 1990s it was discovered that
there is a kind of compressed replay of the day's accumulated memories during
slow wave sleep. The networks of cells active during learning would burst to
life again. This led to the theory that the hippocampus consolidates new
learning to the cortex when the brain is off-line. But Tsien feels this
spontaneous jangling of neural traces is probably a much more general
homeostatic mechanism that helps to keep labile synapses stabilized. And the
jangling probably goes on around the clock, in all areas of the brain, at
regular intervals to remind each synaptic connection of its place in the
great scheme of things (Wittenberg, Sullivan and Tsien, 2002).

All this Byzantine complexity does matter. To make sense of the brain as an
information processing system, clearly we must be physically able to locate
its information. And it's long been an almost unquestioned tenet of
neuroscience that neurons with their weighted junctions and crisp connection
patterns are devices for trapping information. The hardwired network is the
solid foundation for all the pretty patterns that play across it. Yet when we
zero in on these synapses, suddenly their "information" appears to scatter.
The synapses turn out to be merely reflecting a living confluence of top-down
and bottom-up pressures. The information is now out there in the system and
it is making the synaptic patterns we observe.

This kind of topsy-turvey picture can only be resolved by taking a more
holistic view of the brain as the organ of consciousness. The whole shapes
the parts as much as the parts shape the whole. No component of the system is
itself stable but the entire production locks together to have stable
existence. This is how you can manage to persist even though much of you is
being recycled by day if not the hour.

Copyright © John McCrone, 2004

John McCrone is the author of four books on the brain and consciousness.
More at: http://www.btinternet.com/~neuronaut/

References
Star EN, Kwiatkowski DJ and Murthy VN. Rapid turnover of actin in dendritic
spines and its regulation by activity, Nature Neuroscience 5:239-246 (2002)

Ehlers MD. Activity-dependent regulation of postsynaptic composition and
signaling by the ubiquitin-proteasome system. Nature Neuroscience 6:231-242
(2003)

Shimizu E, Tang YP, Rampon C and Tsien JZ. NMDA receptor dependent synaptic
reinforcement as a crucial process for memory consolidation. Science
290:1170-1174 (2000)

Lisman JE and Fallon JR. What maintains memories? Science 283:339-340 (1999)

Wittenberg GM, Sullivan MR and Tsien JZ. Synaptic Reentry Reinforcement
Based Network Model for Long-Term Memory Consolidation Hippocampus
12:637-647 (2002)

-- 
Eugen* Leitl <a href="http://leitl.org">leitl</a>
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